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.
2D ESR image reconstruction from 1D projections using the modulated field gradient method
NASA Astrophysics Data System (ADS)
Páli, T.; Sass, L.; Horvat, L. I.; Ebert, B.
A method for the reconstruction of 2D ESR images from 1 D projections which is based on the modulated field gradient method has been explored. The 2D distribution of spin-labeled stearic acid in oriented and unoriented dimyristoyl phosphatidylcholine multilayers on a flat quartz support was determined. Such samples are potentially useful for the determination of lipid lateral diffusion in oriented multilayers by monitoring the spreading of a sharp concentration profile in one or two dimensions. The limitations of the method are discussed and the improvements which are needed for dynamic measurements are outlined.
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.
Single particle 3D reconstruction for 2D crystal images of membrane proteins.
Scherer, Sebastian; Arheit, Marcel; Kowal, Julia; Zeng, Xiangyan; Stahlberg, Henning
2014-03-01
In cases where ultra-flat cryo-preparations of well-ordered two-dimensional (2D) crystals are available, electron crystallography is a powerful method for the determination of the high-resolution structures of membrane and soluble proteins. However, crystal unbending and Fourier-filtering methods in electron crystallography three-dimensional (3D) image processing are generally limited in their performance for 2D crystals that are badly ordered or non-flat. Here we present a single particle image processing approach, which is implemented as an extension of the 2D crystallographic pipeline realized in the 2dx software package, for the determination of high-resolution 3D structures of membrane proteins. The algorithm presented, addresses the low single-to-noise ratio (SNR) of 2D crystal images by exploiting neighborhood correlation between adjacent proteins in the 2D crystal. Compared with conventional single particle processing for randomly oriented particles, the computational costs are greatly reduced due to the crystal-induced limited search space, which allows a much finer search space compared to classical single particle processing. To reduce the considerable computational costs, our software features a hybrid parallelization scheme for multi-CPU clusters and computer with high-end graphic processing units (GPUs). We successfully apply the new refinement method to the structure of the potassium channel MloK1. The calculated 3D reconstruction shows more structural details and contains less noise than the map obtained by conventional Fourier-filtering based processing of the same 2D crystal images.
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
Bindu, G; Semenov, S
2013-01-01
This paper describes an efficient two-dimensional fused image reconstruction approach for Microwave Tomography (MWT). Finite Difference Time Domain (FDTD) models were created for a viable MWT experimental system having the transceivers modelled using thin wire approximation with resistive voltage sources. Born Iterative and Distorted Born Iterative methods have been employed for image reconstruction with the extremity imaging being done using a differential imaging technique. The forward solver in the imaging algorithm employs the FDTD method of solving the time domain Maxwell's equations with the regularisation parameter computed using a stochastic approach. The algorithm is tested with 10% noise inclusion and successful image reconstruction has been shown implying its robustness.
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
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.
Hou, Gary Y; Provost, Jean; Grondin, Julien; Wang, Shutao; Marquet, Fabrice; Bunting, Ethan; Konofagou, Elisa E
2014-11-01
Harmonic motion imaging for focused ultrasound (HMIFU) utilizes an amplitude-modulated HIFU beam to induce a localized focal oscillatory motion simultaneously estimated. 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. A single divergent transmit beam 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 with frame rates up to 15 Hz, a 100-fold increase compared to conventional CPU-based processing. The real-time feedback rate does not require interrupting the HIFU treatment. Results in phantom experiments showed reproducible HMI images and monitoring of 22 in vitro HIFU treatments using the new 2-D system demonstrated reproducible displacement imaging, and monitoring of 22 in vitro HIFU treatments using the new 2-D system showed a consistent average focal displacement decrease of 46.7 ±14.6% during lesion formation. Complementary focal temperature monitoring also indicated an average rate of displacement increase and decrease with focal temperature at 0.84±1.15%/(°)C, and 2.03±0.93%/(°)C , respectively. These results reinforce the HMIFU capability of estimating and monitoring stiffness related changes in real time. Current ongoing studies include clinical translation of the presented system for monitoring of HIFU treatment for breast and pancreatic tumor applications.
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
NASA Astrophysics Data System (ADS)
Ahmed, M. F.; Schnell, E.; Ahmad, S.; Yukihara, E. G.
2016-10-01
The objective of this work was to develop an image reconstruction algorithm for 2D dosimetry using Al2O3:C and Al2O3:C,Mg optically stimulated luminescence (OSL) films imaged using a laser scanning system. The algorithm takes into account parameters associated with detector properties and the readout system. Pieces of Al2O3:C films (~8 mm × 8 mm × 125 µm) were irradiated and used to simulate dose distributions with extreme dose gradients (zero and non-zero dose regions). The OSLD film pieces were scanned using a custom-built laser-scanning OSL reader and the data obtained were used to develop and demonstrate a dose reconstruction algorithm. The algorithm includes corrections for: (a) galvo hysteresis, (b) photomultiplier tube (PMT) linearity, (c) phosphorescence, (d) ‘pixel bleeding’ caused by the 35 ms luminescence lifetime of F-centers in Al2O3, (e) geometrical distortion inherent to Galvo scanning system, and (f) position dependence of the light collection efficiency. The algorithm was also applied to 6.0 cm × 6.0 cm × 125 μm or 10.0 cm × 10.0 cm × 125 µm Al2O3:C and Al2O3:C,Mg films exposed to megavoltage x-rays (6 MV) and 12C beams (430 MeV u‑1). The results obtained using pieces of irradiated films show the ability of the image reconstruction algorithm to correct for pixel bleeding even in the presence of extremely sharp dose gradients. Corrections for geometric distortion and position dependence of light collection efficiency were shown to minimize characteristic limitations of this system design. We also exemplify the application of the algorithm to more clinically relevant 6 MV x-ray beam and a 12C pencil beam, demonstrating the potential for small field dosimetry. The image reconstruction algorithm described here provides the foundation for laser-scanned OSL applied to 2D dosimetry.
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.
Garcia, Jaime; Olariu, Radu; Dindoyal, Irving; Le Huu, Serge
2012-01-01
Background Producing a rich, personalized Web-based consultation tool for plastic surgeons and patients is challenging. Objective (1) To develop a computer tool that allows individual reconstruction and simulation of 3-dimensional (3D) soft tissue from ordinary digital photos of breasts, (2) to implement a Web-based, worldwide-accessible preoperative surgical planning platform for plastic surgeons, and (3) to validate this tool through a quality control analysis by comparing 3D laser scans of the patients with the 3D reconstructions with this tool from original 2-dimensional (2D) pictures of the same patients. Methods The proposed system uses well-established 2D digital photos for reconstruction into a 3D torso, which is then available to the user for interactive planning. The simulation is performed on dedicated servers, accessible via Internet. It allows the surgeon, together with the patient, to previsualize the impact of the proposed breast augmentation directly during the consultation before a surgery is decided upon. We retrospectively conduced a quality control assessment of available anonymized pre- and postoperative 2D digital photographs of patients undergoing breast augmentation procedures. The method presented above was used to reconstruct 3D pictures from 2D digital pictures. We used a laser scanner capable of generating a highly accurate surface model of the patient’s anatomy to acquire ground truth data. The quality of the computed 3D reconstructions was compared with the ground truth data used to perform both qualitative and quantitative evaluations. Results We evaluated the system on 11 clinical cases for surface reconstructions and 4 clinical cases of postoperative simulations, using laser surface scan technologies showing a mean reconstruction error between 2 and 4 mm and a maximum outlier error of 16 mm. Qualitative and quantitative analyses from plastic surgeons demonstrate the potential of these new emerging technologies. Conclusions We
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.
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 Four-Channel Perfect Reconstruction Filter Bank Realized with the 2D Lattice Filter Structure
NASA Astrophysics Data System (ADS)
Sezen, S.; Ertüzün, A.
2006-12-01
A novel orthogonal 2D lattice structure is incorporated into the design of a nonseparable 2D four-channel perfect reconstruction filter bank. The proposed filter bank is obtained by using the polyphase decomposition technique which requires the design of an orthogonal 2D lattice filter. Due to constraint of perfect reconstruction, each stage of this lattice filter bank is simply parameterized by two coefficients. The perfect reconstruction property is satisfied regardless of the actual values of these parameters and of the number of the lattice stages. It is also shown that a separable 2D four-channel perfect reconstruction lattice filter bank can be constructed from the 1D lattice filter and that this is a special case of the proposed 2D lattice filter bank under certain conditions. The perfect reconstruction property of the proposed 2D lattice filter approach is verified by computer simulations.
Stereo radar: reconstructing 3D data from 2D radar
NASA Astrophysics Data System (ADS)
Schmerwitz, Sven; Döhler, Hans-Ullrich; Peinecke, Niklas; Korn, Bernd
2008-04-01
To improve the situation awareness of an aircrew during poor visibility, different approaches emerged during the past couple of years. Enhanced vision systems (EVS - based upon sensor images) are one of those. They improve situation awareness of the crew, but at the same time introduce certain operational deficits. EVS present sensor data which might be difficult to interpret especially if the sensor used is a radar sensor. In particular an unresolved problem of fast scanning forward looking radar systems in the millimeter waveband is the inability to measure the elevation of a target. In order to circumvent this problem effort was made to reconstruct the missing elevation from a series of images. This could be described as a "Stereo radar"-attempt and is similar to the reconstruction using photography (angle-angle images) from different viewpoints to rebuilt the depth information. Two radar images (range-angle images) with different bank angles can be used to reconstruct the elevation of targets. This paper presents the fundamental idea and the methods of the reconstruction. Furthermore, experiences with real data from EADS's "HiVision" MMCW radar are discussed. Two different approaches are investigated: First, a fusion of images with variable bank angles is calculated for different elevation layers and picture processing reveals identical objects in these layers. Those objects are compared regarding contrast and dimension to extract their elevation. The second approach compares short fusion pairs of two different flights with different nearly constant bank angles. Accumulating those pairs with different offsets delivers the exact elevation.
A 3D Freehand Ultrasound System for Multi-view Reconstructions from Sparse 2D Scanning Planes
2011-01-01
Background A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. Methods We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes. For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Results Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better
Reconstructing 2-D/3-D Building Shapes from Spaceborne Tomographic Synthetic Aperture Radar Data
NASA Astrophysics Data System (ADS)
Shahzad, M.; Zhu, X. X.
2014-08-01
In this paper, we present an approach that allows automatic (parametric) reconstruction of building shapes in 2-D/3-D using TomoSAR point clouds. These point clouds are generated by processing radar image stacks via advanced interferometric technique, called SAR tomography. The proposed approach reconstructs the building outline by exploiting both the available roof and façade information. Roof points are extracted out by employing a surface normals based region growing procedure via selected seed points while the extraction of façade points is based on thresholding the point scatterer density SD estimated by robust M-estimator. Spatial clustering is then applied to the extracted roof points in a way such that each roof cluster represents an individual building. Extracted façade points are reconstructed and afterwards incorporated to the segmented roof cluster to reconstruct the complete building shape. Initial building footprints are derived by employing alpha shapes method that are later regularized. Finally, rectilinear constraints are added to yield better geometrically looking building shapes. The proposed approach is illustrated and validated by examples using TomoSAR point clouds generated from a stack of TerraSAR-X high-resolution spotlight images from ascending orbit only covering two different test areas with one containing relatively smaller buildings in densely populated regions and the other containing moderate sized buildings in the city of Las Vegas.
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.
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)
High-resolution reconstruction for terahertz imaging.
Xu, Li-Min; Fan, Wen-Hui; Liu, Jia
2014-11-20
We present a high-resolution (HR) reconstruction model and algorithms for terahertz imaging, taking advantage of super-resolution methodology and algorithms. The algorithms used include projection onto a convex sets approach, iterative backprojection approach, Lucy-Richardson iteration, and 2D wavelet decomposition reconstruction. Using the first two HR reconstruction methods, we successfully obtain HR terahertz images with improved definition and lower noise from four low-resolution (LR) 22×24 terahertz images taken from our homemade THz-TDS system at the same experimental conditions with 1.0 mm pixel. Using the last two HR reconstruction methods, we transform one relatively LR terahertz image to a HR terahertz image with decreased noise. This indicates potential application of HR reconstruction methods in terahertz imaging with pulsed and continuous wave terahertz sources.
2D hexagonal quaternion Fourier transform in color image processing
NASA Astrophysics Data System (ADS)
Grigoryan, Artyom M.; Agaian, Sos S.
2016-05-01
In this paper, we present a novel concept of the quaternion discrete Fourier transform on the two-dimensional hexagonal lattice, which we call the two-dimensional hexagonal quaternion discrete Fourier transform (2-D HQDFT). The concept of the right-side 2D HQDFT is described and the left-side 2-D HQDFT is similarly considered. To calculate the transform, the image on the hexagonal lattice is described in the tensor representation when the image is presented by a set of 1-D signals, or splitting-signals which can be separately processed in the frequency domain. The 2-D HQDFT can be calculated by a set of 1-D quaternion discrete Fourier transforms (QDFT) of the splitting-signals.
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.
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.
2D electron cyclotron emission imaging at ASDEX Upgrade (invited)
Classen, I. G. J.; Boom, J. E.; Vries, P. C. de; Suttrop, W.; Schmid, E.; Garcia-Munoz, M.; Schneider, P. A.; Tobias, B.; Domier, C. W.; Luhmann, N. C. Jr.; Donne, A. J. H.; Jaspers, R. J. E.; Park, H. K.; Munsat, T.
2010-10-15
The newly installed electron cyclotron emission imaging diagnostic on ASDEX Upgrade provides measurements of the 2D electron temperature dynamics with high spatial and temporal resolution. An overview of the technical and experimental properties of the system is presented. These properties are illustrated by the measurements of the edge localized mode and the reversed shear Alfven eigenmode, showing both the advantage of having a two-dimensional (2D) measurement, as well as some of the limitations of electron cyclotron emission measurements. Furthermore, the application of singular value decomposition as a powerful tool for analyzing and filtering 2D data is presented.
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.
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.
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.
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
Improving VERITAS sensitivity by fitting 2D Gaussian image parameters
NASA Astrophysics Data System (ADS)
Christiansen, Jodi; VERITAS Collaboration
2012-12-01
Our goal is to improve the acceptance and angular resolution of VERITAS by implementing a camera image-fitting algorithm. Elliptical image parameters are extracted from 2D Gaussian distribution fits using a χ2 minimization instead of the standard technique based on the principle moments of an island of pixels above threshold. We optimize the analysis cuts and then characterize the improvements using simulations. We find an improvement of 20% less observing time to reach 5-sigma for weak point sources.
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.
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
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.
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.
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.
Fast iterative image reconstruction of 3D PET data
Kinahan, P.E.; Townsend, D.W.; Michel, C.
1996-12-31
For count-limited PET imaging protocols, two different approaches to reducing statistical noise are volume, or 3D, imaging to increase sensitivity, and statistical reconstruction methods to reduce noise propagation. These two approaches have largely been developed independently, likely due to the perception of the large computational demands of iterative 3D reconstruction methods. We present results of combining the sensitivity of 3D PET imaging with the noise reduction and reconstruction speed of 2D iterative image reconstruction methods. This combination is made possible by using the recently-developed Fourier rebinning technique (FORE), which accurately and noiselessly rebins 3D PET data into a 2D data set. The resulting 2D sinograms are then reconstructed independently by the ordered-subset EM (OSEM) iterative reconstruction method, although any other 2D reconstruction algorithm could be used. We demonstrate significant improvements in image quality for whole-body 3D PET scans by using the FORE+OSEM approach compared with the standard 3D Reprojection (3DRP) algorithm. In addition, the FORE+OSEM approach involves only 2D reconstruction and it therefore requires considerably less reconstruction time than the 3DRP algorithm, or any fully 3D statistical reconstruction algorithm.
Interactive 2D to 3D stereoscopic image synthesis
NASA Astrophysics Data System (ADS)
Feldman, Mark H.; Lipton, Lenny
2005-03-01
Advances in stereoscopic display technologies, graphic card devices, and digital imaging algorithms have opened up new possibilities in synthesizing stereoscopic images. The power of today"s DirectX/OpenGL optimized graphics cards together with adapting new and creative imaging tools found in software products such as Adobe Photoshop, provide a powerful environment for converting planar drawings and photographs into stereoscopic images. The basis for such a creative process is the focus of this paper. This article presents a novel technique, which uses advanced imaging features and custom Windows-based software that utilizes the Direct X 9 API to provide the user with an interactive stereo image synthesizer. By creating an accurate and interactive world scene with moveable and flexible depth map altered textured surfaces, perspective stereoscopic cameras with both visible frustums and zero parallax planes, a user can precisely model a virtual three-dimensional representation of a real-world scene. Current versions of Adobe Photoshop provide a creative user with a rich assortment of tools needed to highlight elements of a 2D image, simulate hidden areas, and creatively shape them for a 3D scene representation. The technique described has been implemented as a Photoshop plug-in and thus allows for a seamless transition of these 2D image elements into 3D surfaces, which are subsequently rendered to create stereoscopic views.
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.
Weighted iterative reconstruction for magnetic particle imaging
NASA Astrophysics Data System (ADS)
Knopp, T.; Rahmer, J.; Sattel, T. F.; Biederer, S.; Weizenecker, J.; Gleich, B.; Borgert, J.; Buzug, T. M.
2010-03-01
Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.
KPLS-RWBFNN model for MFL 2D defect profile reconstruction
NASA Astrophysics Data System (ADS)
Xu, Chao; Wang, Changlong; Ji, Fengzhu
2013-03-01
Kernel partial least squares (KPLS) is normally very efficient for tackling nonlinear systems by mapping an original input space into a high-dimensional feature space and creating a linear PLS model in the feature space. Unlike other nonlinear PLS techniques, KPLS does not entail any nonlinear optimisation procedures. However, due to the linear inner model of PLS, KPLS is still inappropriate for describing the significant nonlinear characteristic data structure while dealing with complex physical systems in practical situations. Under this circumstance, radial wavelet basic function neural network (RWBFNN) can replace the linear inner model of PLS in the nonlinear kernel-based algorithm. Thus, KPLS-RWBFNN model is proposed in this paper and applied to multi-resolution approximation reconstruction of 2D defect profiles in magnetic flux leakage testing. The reconstructions of 2D defect profiles by this method are implemented, and the comparisons among reconstructions by KPLS, RWBFNN and the proposed approach are also undertaken. Meanwhile, the reconstructions of 2D defects by RWBFNN and the proposed approach at different SNR are also executed. The results indicate that KPLS-RWBFNN model could simplify the structure of the network while holding well-behaved generalisation and multi-resolution approximation and predict the 2D defect profiles accurately and rapidly with good robustness.
3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.
Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua
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
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
SAR imaging via modern 2-D spectral estimation methods.
DeGraaf, S R
1998-01-01
This paper discusses the use of modern 2D spectral estimation algorithms for synthetic aperture radar (SAR) imaging. The motivation for applying power spectrum estimation methods to SAR imaging is to improve resolution, remove sidelobe artifacts, and reduce speckle compared to what is possible with conventional Fourier transform SAR imaging techniques. This paper makes two principal contributions to the field of adaptive SAR imaging. First, it is a comprehensive comparison of 2D spectral estimation methods for SAR imaging. It provides a synopsis of the algorithms available, discusses their relative merits for SAR imaging, and illustrates their performance on simulated and collected SAR imagery. Some of the algorithms presented or their derivations are new, as are some of the insights into or analyses of the algorithms. Second, this work develops multichannel variants of four related algorithms, minimum variance method (MVM), reduced-rank MVM (RRMVM), adaptive sidelobe reduction (ASR) and space variant apodization (SVA) to estimate both reflectivity intensity and interferometric height from polarimetric displaced-aperture interferometric data. All of these interferometric variants are new. In the interferometric contest, adaptive spectral estimation can improve the height estimates through a combination of adaptive nulling and averaging. Examples illustrate that MVM, ASR, and SVA offer significant advantages over Fourier methods for estimating both scattering intensity and interferometric height, and allow empirical comparison of the accuracies of Fourier, MVM, ASR, and SVA interferometric height estimates.
2D/3D image (facial) comparison using camera matching.
Goos, Mirelle I M; Alberink, Ivo B; Ruifrok, Arnout C C
2006-11-10
A problem in forensic facial comparison of images of perpetrators and suspects is that distances between fixed anatomical points in the face, which form a good starting point for objective, anthropometric comparison, vary strongly according to the position and orientation of the camera. In case of a cooperating suspect, a 3D image may be taken using e.g. a laser scanning device. By projecting the 3D image onto a 2D image with the suspect's head in the same pose as that of the perpetrator, using the same focal length and pixel aspect ratio, numerical comparison of (ratios of) distances between fixed points becomes feasible. An experiment was performed in which, starting from two 3D scans and one 2D image of two colleagues, male and female, and using seven fixed anatomical locations in the face, comparisons were made for the matching and non-matching case. Using this method, the non-matching pair cannot be distinguished from the matching pair of faces. Facial expression and resolution of images were all more or less optimal, and the results of the study are not encouraging for the use of anthropometric arguments in the identification process. More research needs to be done though on larger sets of facial comparisons. PMID:16337353
Iterative 2D deconvolution of portal imaging radiographs.
Looe, Hui Khee; Harder, Dietrich; Willborn, Kay C; Poppe, Björn
2011-01-01
Portal imaging has become an integral part of modern radiotherapy techniques such as IMRT and IGRT. It serves to verify the accuracy of day-to-day patient positioning, a prerequisite for treatment success. However, image blurring attributable to different physical and geometrical effects, analysed in this work, impairs the image quality of the portal images, and anatomical structures cannot always be clearly outlined. A 2D iterative deconvolution method was developed to reduce this image blurring. The affiliated data basis was generated by the separate measurement of the components contributing to image blurring. Secondary electron transport and pixel size within the EPID, as well as geometrical penumbra due to the finite photon source size were found to be the major contributors, whereas photon scattering in the patient is less important. The underlying line-spread kernels of these components were shown to be Lorentz functions. This implies that each of these convolution kernels and also their combination can be characterized by a single characteristic, the width parameter λ of the Lorentz function. The overall resulting λ values were 0.5mm for 6 MV and 0.65 mm for 15 MV. Portal images were deconvolved using the point-spread function derived from the Lorentz function together with the experimentally determined λ values. The improvement of the portal images was quantified in terms of the modulation transfer function of a bar pattern. The resulting clinical images show a clear enhancement of sharpness and contrast.
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
2D optoacoustic array for high resolution imaging
NASA Astrophysics Data System (ADS)
Ashkenazi, S.; Witte, R. S.; Kim, K.; Huang, S.-W.; Hou, Y.; O'Donnell, M.
2006-02-01
An optoacoustic detector denotes the detection of acoustic signals by optical devices. Recent advances in fabrication techniques and the availability of high power tunable laser sources have greatly accelerated the development of efficient optoacoustic detectors. The unique advantages of optoacoustic technology are of special interest in applications that require high resolution imaging. For these applications optoacoustic technology enables high frequency transducer arrays with element size on the order of 10 μm. Laser generated ultrasound (photoacoustic effect) has been studied since the early observations of A.G. Bell (1880) of audible sound generated by light absorption . Modern studies have demonstrated the use of the photoacoustic effect to form a versatile imaging modality for medical and biological applications. A short laser pulse illuminates a tissue creating rapid thermal expansion and acoustic emission. Detection of the resulting acoustic field by an array enables the imaging of the tissue optical absorption using ultrasonic imaging methods. We present an integrated imaging system that employs photoacoustic sound generation and 2D optoacoustic reception. The optoacoustic receiver consists of a thin polymer Fabry-Perot etalon. The etalon is an optical resonator of a high quality factor (Q = 750). The relatively low elasticity modulus of the polymer and the high Q-factor of the resonator combine to yield high ultrasound sensitivity. The etalon thickness (10 μm) was optimized for wide bandwidth (typically above 50 MHz). An optical scanning and focusing system is used to create a large aperture and high density 2D ultrasonic receiver array. High resolution 3D images of phantom targets and biological tissue samples were obtained.
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.
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.
Multiple 2D video/3D medical image registration algorithm
NASA Astrophysics Data System (ADS)
Clarkson, Matthew J.; Rueckert, Daniel; Hill, Derek L.; Hawkes, David J.
2000-06-01
In this paper we propose a novel method to register at least two vide images to a 3D surface model. The potential applications of such a registration method could be in image guided surgery, high precision radiotherapy, robotics or computer vision. Registration is performed by optimizing a similarity measure with respect to the pose parameters. The similarity measure is based on 'photo-consistency' and computes for each surface point, how consistent the corresponding video image information in each view is with a lighting model. We took four video views of a volunteer's face, and used an independent method to reconstruct a surface that was intrinsically registered to the four views. In addition, we extracted a skin surface from the volunteer's MR scan. The surfaces were misregistered from a gold standard pose and our algorithm was used to register both types of surfaces to the video images. For the reconstructed surface, the mean 3D error was 1.53 mm. For the MR surface, the standard deviation of the pose parameters after registration ranged from 0.12 to 0.70 mm and degrees. The performance of the algorithm is accurate, precise and robust.
Compressed Sensing Reconstruction of Ultrafast 2D NMR Data: Principles and Biomolecular Applications
Shrot, Yoav; Frydman, Lucio
2016-01-01
A topic of active investigation in 2D NMR relates to the minimum number of scans required for acquiring this kind of spectra, particularly when these are dictated by sampling rather than by sensitivity considerations. Reductions in this minimum number of scans have been achieved by departing from the regular sampling used to monitor the indirect domain, and relying instead on non-uniform sampling and iterative reconstruction algorithms. Alternatively, so-called “ultrafast” methods can compress the minimum number of scans involved in 2D NMR all the way to a minimum number of one, by spatially encoding the indirect domain information and subsequently recovering it via oscillating field gradients. Given ultrafast NMR’s simultaneous recording of the indirect- and direct-domain data, this experiment couples the spectral constraints of these orthogonal domains –often calling for the use of strong acquisition gradients and large filter widths to fulfill the desired bandwidth and resolution demands along all spectral dimensions. This study discusses a way to alleviate these demands, and thereby enhance the method’s performance and applicability, by combining spatial encoding with iterative reconstruction approaches. Examples of these new principles are given based on the compressed-sensed reconstruction of biomolecular 2D HSQC ultrafast NMR data, an approach that we show enables a decrease of the gradient strengths demanded in this type of experiments by up to 80%. PMID:21316276
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
Exercises in PET Image Reconstruction
NASA Astrophysics Data System (ADS)
Nix, Oliver
These exercises are complementary to the theoretical lectures about positron emission tomography (PET) image reconstruction. They aim at providing some hands on experience in PET image reconstruction and focus on demonstrating the different data preprocessing steps and reconstruction algorithms needed to obtain high quality PET images. Normalisation, geometric-, attenuation- and scatter correction are introduced. To explain the necessity of those some basics about PET scanner hardware, data acquisition and organisation are reviewed. During the course the students use a software application based on the STIR (software for tomographic image reconstruction) library 1,2 which allows them to dynamically select or deselect corrections and reconstruction methods as well as to modify their most important parameters. Following the guided tutorial, the students get an impression on the effect the individual data precorrections have on image quality and what happens if they are forgotten. Several data sets in sinogram format are provided, such as line source data, Jaszczak phantom data sets with high and low statistics and NEMA whole body phantom data. The two most frequently used reconstruction algorithms in PET image reconstruction, filtered back projection (FBP) and the iterative OSEM (ordered subset expectation maximation) approach are used to reconstruct images. The exercise should help the students gaining an understanding what the reasons for inferior image quality and artefacts are and how to improve quality by a clever choice of reconstruction parameters.
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.
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
Electron Microscopy: From 2D to 3D Images with Special Reference to Muscle.
Franzini-Armstrong, Clara
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
Crystallographic image reconstruction problem
NASA Astrophysics Data System (ADS)
ten Eyck, Lynn F.
1993-11-01
The crystallographic X-ray diffraction experiment gives the amplitudes of the Fourier series expansion of the electron density distribution within the crystal. The 'phase problem' in crystallography is the determination of the phase angles of the Fourier coefficients required to calculate the Fourier synthesis and reveal the molecular structure. The magnitude of this task varies enormously as the size of the structures ranges from a few atoms to thousands of atoms, and the number of Fourier coefficients ranges from hundreds to hundreds of thousands. The issue is further complicated for large structures by limited resolution. This problem is solved for 'small' molecules (up to 200 atoms and a few thousand Fourier coefficients) by methods based on probabilistic models which depend on atomic resolution. These methods generally fail for larger structures such as proteins. The phase problem for protein molecules is generally solved either by laborious experimental methods or by exploiting known similarities to solved structures. Various direct methods have been attempted for very large structures over the past 15 years, with gradually improving results -- but so far no complete success. This paper reviews the features of the crystallographic image reconstruction problem which render it recalcitrant, and describes recent encouraging progress in the application of maximum entropy methods to this problem.
The 2dF Galaxy Redshift Survey: Wiener reconstruction of the cosmic web
NASA Astrophysics Data System (ADS)
Erdoǧdu, Pirin; Lahav, Ofer; Zaroubi, Saleem; Efstathiou, George; Moody, Steve; Peacock, John A.; Colless, Matthew; Baldry, Ivan K.; Baugh, Carlton M.; Bland-Hawthorn, Joss; Bridges, Terry; Cannon, Russell; Cole, Shaun; Collins, Chris; Couch, Warrick; Dalton, Gavin; De Propris, Roberto; Driver, Simon P.; Ellis, Richard S.; Frenk, Carlos S.; Glazebrook, Karl; Jackson, Carole; Lewis, Ian; Lumsden, Stuart; Maddox, Steve; Madgwick, Darren; Norberg, Peder; Peterson, Bruce A.; Sutherland, Will; Taylor, Keith
2004-08-01
We reconstruct the underlying density field of the Two-degree Field Galaxy Redshift Survey (2dFGRS) for the redshift range 0.035 < z < 0.200 using the Wiener filtering method. The Wiener filter suppresses shot noise and accounts for selection and incompleteness effects. The method relies on prior knowledge of the 2dF power spectrum of fluctuations and the combination of matter density and bias parameters, however the results are only slightly affected by changes to these parameters. We present maps of the density field. We use a variable smoothing technique with two different effective resolutions: 5 and 10 h-1 Mpc at the median redshift of the survey. We identify all major superclusters and voids in the survey. In particular, we find two large superclusters and two large local voids. The full set of colour maps can be viewed on the World Wide Web at http://www.ast.cam.ac.uk/~pirin.
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)
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.
Microsecond time-resolved 2D X-ray imaging
NASA Astrophysics Data System (ADS)
Sarvestani, A.; Sauer, N.; Strietzel, C.; Besch, H. J.; Orthen, A.; Pavel, N.; Walenta, A. H.; Menk, R. H.
2001-06-01
A method is presented which allows to take two-dimensional X-ray images of repetitive processes with recording times in the sub-microsecond range. Various measurements have been performed with a recently introduced novel two-dimensional single photon counter which has been slightly modified in order to determine the exact arrival time of each detected photon. For this purpose a special clock signal is synchronized with the process and is digitized contemporaneously with each event. This technique can be applied even with rate limited detectors and low flux sources, since—unlike in conventional methods, where chopped beams or gated read out electronics are used—all photons are used for the image formation. For the measurements, rapidly moving mechanical systems and conventional X-ray sources have been used, reaching time resolutions of some 10 μs. The technique presented here opens a variety of new biological, medical and industrial applications which will be discussed. As a first application example, three dimensional tomographic reconstructions of rapidly rotating objects (4000 turns/min) are presented.
Viewing effects of 3-D images synthesized from a series of 2-D tomograms by VAP and HAP approaches
NASA Astrophysics Data System (ADS)
Zhai, H. C.; Wang, M. W.; Liu, F. M.; Hsu, Ken Y.
We report, for the first time, the experimental result and its analysis of synthesizing a series of simulating 2-D tomograms into a 3-D monochromatic image. Our result shows clearly the advantage in monochromaticity of a vertical area-partition (VAP) approach over a horizontal area-partition (HAP) approach during the final white-light reconstruction. This monochromaticity will ensure a 3-D image synthesis without any distortion in gray level or positional recovery.
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...
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
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.
Low, Gavin; Owen, Nicola E.; Joubert, Ilse; Patterson, Andrew J.; Graves, Martin J.; Glaser, Kevin J.; Alexander, Graeme J.M.; Lomas, David J.
2015-01-01
PURPOSE To evaluate the reliability of MRE using a spin-echo echo-planar imaging (SE-EPI) renal MRE technique in healthy volunteers MATERIALS AND METHODS Institutional review board approved prospective study in which all participants provided written informed consent. Sixteen healthy volunteers comprising seven males and nine females with a median age of 35 years (age range: 23 to 59 years) were included. Coronal 90-Hz and 60-Hz MRE acquisitions were performed twice within a 30-minute interval between examinations. Renal MRE reliability was assessed by i) test-retest repeatability, and ii) inter-rater agreement between two independent readers. The MRE-measured averaged renal stiffness values were evaluated using: intraclass correlation coefficient (ICC), Bland-Altman and the within-subject coefficient of variation (COV). RESULTS For test-retest repeatability, Bland-Altman showed a mean stiffness difference between examinations of 0.07 kPa (95% limits of agreement: −1.41, 1.54) at 90-Hz and 0.01 kPa (95% limits of agreement: −0.51, 0.53) at 60-Hz. Coefficient of repeatability was 1.47 kPa and 0.52 kPa at 90-Hz and 60-Hz, respectively. The within-subject COV was 13.6% and 7.7% at 90-Hz and 60-Hz, respectively. ICC values were 0.922 and 0.907 for test-retest repeatability and 0.998 and 0.989 for inter-rater agreement, respectively (p < 0.001). CONCLUSION SE-EPI renal MRE is a reliable technique PMID:25537823
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.
Plane-wave transverse oscillation for high-frame-rate 2-D vector flow imaging.
Lenge, Matteo; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Liebgott, Hervé
2015-12-01
Transverse oscillation (TO) methods introduce oscillations in the pulse-echo field (PEF) along the direction transverse to the ultrasound propagation direction. This may be exploited to extend flow investigations toward multidimensional estimates. In this paper, the TOs are coupled with the transmission of plane waves (PWs) to reconstruct high-framerate RF images with bidirectional oscillations in the pulse-echo field. Such RF images are then processed by a 2-D phase-based displacement estimator to produce 2-D vector flow maps at thousands of frames per second. First, the capability of generating TOs after PW transmissions was thoroughly investigated by varying the lateral wavelength, the burst length, and the transmission frequency. Over the entire region of interest, the generated lateral wavelengths, compared with the designed ones, presented bias and standard deviation of -3.3 ± 5.7% and 10.6 ± 7.4% in simulations and experiments, respectively. The performance of the ultrafast vector flow mapping method was also assessed by evaluating the differences between the estimated velocities and the expected ones. Both simulations and experiments show overall biases lower than 20% when varying the beam-to-flow angle, the peak velocity, and the depth of interest. In vivo applications of the method on the common carotid and the brachial arteries are also presented. PMID:26670852
Plane-wave transverse oscillation for high-frame-rate 2-D vector flow imaging.
Lenge, Matteo; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Liebgott, Hervé
2015-12-01
Transverse oscillation (TO) methods introduce oscillations in the pulse-echo field (PEF) along the direction transverse to the ultrasound propagation direction. This may be exploited to extend flow investigations toward multidimensional estimates. In this paper, the TOs are coupled with the transmission of plane waves (PWs) to reconstruct high-framerate RF images with bidirectional oscillations in the pulse-echo field. Such RF images are then processed by a 2-D phase-based displacement estimator to produce 2-D vector flow maps at thousands of frames per second. First, the capability of generating TOs after PW transmissions was thoroughly investigated by varying the lateral wavelength, the burst length, and the transmission frequency. Over the entire region of interest, the generated lateral wavelengths, compared with the designed ones, presented bias and standard deviation of -3.3 ± 5.7% and 10.6 ± 7.4% in simulations and experiments, respectively. The performance of the ultrafast vector flow mapping method was also assessed by evaluating the differences between the estimated velocities and the expected ones. Both simulations and experiments show overall biases lower than 20% when varying the beam-to-flow angle, the peak velocity, and the depth of interest. In vivo applications of the method on the common carotid and the brachial arteries are also presented.
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)
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
Image Reconstruction for a Partially Collimated Whole Body PET Scanner.
Alessio, Adam M; Schmitz, Ruth E; Macdonald, Lawrence R; Wollenweber, Scott D; Stearns, Charles W; Ross, Steven G; Ganin, Alex; Lewellen, Thomas K; Kinahan, Paul E
2008-06-01
Partially collimated PET systems have less collimation than conventional 2-D systems and have been shown to offer count rate improvements over 2-D and 3-D systems. Despite this potential, previous efforts have not established image-based improvements with partial collimation and have not customized the reconstruction method for partially collimated data. This work presents an image reconstruction method tailored for partially collimated data. Simulated and measured sensitivity patterns are presented and provide a basis for modification of a fully 3-D reconstruction technique. The proposed method uses a measured normalization correction term to account for the unique sensitivity to true events. This work also proposes a modified scatter correction based on simulated data. Measured image quality data supports the use of the normalization correction term for true events, and suggests that the modified scatter correction is unnecessary.
List-mode likelihood: EM algorithm and image quality estimation demonstrated on 2-D PET.
Parra, L; Barrett, H H
1998-04-01
Using a theory of list-mode maximum-likelihood (ML) source reconstruction presented recently by Barrett et al., 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.
Ultra-slim 2D- and depth-imaging camera modules for mobile imaging
NASA Astrophysics Data System (ADS)
Brückner, Andreas; Oberdörster, Alexander; Dunkel, Jens; Reimann, Andreas; Wippermann, Frank
2016-03-01
In this contribution, a microoptical imaging system is demonstrated that is inspired by the insect compound eye. The array camera module achieves HD resolution with a z-height of 2.0 mm, which is about 50% compared to traditional cameras with comparable parameters. The FOV is segmented by multiple optical channels imaging in parallel. The partial images are stitched together to form a final image of the whole FOV by image processing software. The system is able to acquire depth maps along with the 2D video and it includes light field imaging features such as software refocusing. The microlens arrays are realized by microoptical technologies on wafer-level which are suitable for a potential fabrication in high volume.
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); 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,
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,
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.
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
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.
Stöbe, Stephan; Tarr, Adrienn; Pfeiffer, Dietrich; Hagendorff, Andreas
2014-01-01
Comparison of 3D and 2D speckle tracking performed on standard 2D and triplane 2D datasets of normal and pathological left ventricular (LV) wall-motion patterns with a focus on the effect that 3D volume rate (3DVR), image quality and tracking artifacts have on the agreement between 2D and 3D speckle tracking. 37 patients with normal LV function and 18 patients with ischaemic wall-motion abnormalities underwent 2D and 3D echocardiography, followed by offline speckle tracking measurements. The values of 3D global, regional and segmental strain were compared with the standard 2D and triplane 2D strain values. Correlation analysis with the LV ejection fraction (LVEF) was also performed. The 3D and 2D global strain values correlated good in both normally and abnormally contracting hearts, though systematic differences between the two methods were observed. Of the 3D strain parameters, the area strain showed the best correlation with the LVEF. The numerical agreement of 3D and 2D analyses varied significantly with the volume rate and image quality of the 3D datasets. The highest correlation between 2D and 3D peak systolic strain values was found between 3D area and standard 2D longitudinal strain. Regional wall-motion abnormalities were similarly detected by 2D and 3D speckle tracking. 2DST of triplane datasets showed similar results to those of conventional 2D datasets. 2D and 3D speckle tracking similarly detect normal and pathological wall-motion patterns. Limited image quality has a significant impact on the agreement between 3D and 2D numerical strain values. PMID:26693303
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
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.
Clinical applications of 2D and 3D CT imaging of the airways--a review.
Salvolini, L; Bichi Secchi, E; Costarelli, L; De Nicola, M
2000-04-01
Hardware and software evolution has broadened the possibilities of 2D and 3D reformatting of spiral CT and MR data set. In the study of the thorax, intrinsic benefits of volumetric CT scanning and better quality of reconstructed images offer us the possibility to apply additional rendering techniques to everyday clinical practice. Considering the large number and redundancy of possible post-processing imaging techniques that we can apply to raw CT sections data, it is necessary to precisely set a well-defined number of clinical applications of each of them, by careful evaluation of their benefits and possible pitfalls in each clinical setting. In diagnostic evaluation of pathological processes affecting the airways, a huge number of thin sections is necessary for detailed appraisal and has to be evaluated, and information must then be transferred to referring clinicians. By additional rendering it is possible to make image evaluation and data transfer easier, faster, and more effective. In the study of central airways, additional rendering can be of interest for precise evaluation of the length, morphology, and degree of stenoses. It may help in depicting exactly the locoregional extent of central tumours by better display of relations with bronchovascular interfaces and can increase CT/bronchoscopy sinergy. It may allow closer radiotherapy planning and better depiction of air collections, and, finally, it could ease panoramic evaluation of the results of dynamic or functional studies, that are made possible by increased speed of spiral scanning. When applied to the evaluation of peripheral airways, as a completion to conventional HRCT scans, High-Resolution Volumetric CT, by projection slabs applied to target areas of interest, can better depict the profusion and extension of affected bronchial segments in bronchiectasis, influence the choice of different approaches for tissue sampling by better evaluation of the relations of lung nodules with the airways, or help
3D/2D convertible projection-type integral imaging using concave half mirror array.
Hong, Jisoo; Kim, Youngmin; Park, Soon-gi; Hong, Jong-Ho; Min, Sung-Wook; Lee, Sin-Doo; Lee, Byoungho
2010-09-27
We propose a new method for implementing 3D/2D convertible feature in the projection-type integral imaging by using concave half mirror array. The concave half mirror array has the partially reflective characteristic to the incident light. And the reflected term is modulated by the concave mirror array structure, while the transmitted term is unaffected. With such unique characteristic, 3D/2D conversion or even the simultaneous display of 3D and 2D images is also possible. The prototype was fabricated by the aluminum coating and the polydimethylsiloxane molding process. We could experimentally verify the 3D/2D conversion and the display of 3D image on 2D background with the fabricated prototype.
Surface reconstruction from microscopic images in optical lithography.
Estellers, Virginia; Thiran, Jean-Philippe; Gabrani, Maria
2014-08-01
This paper presents a method to reconstruct 3D surfaces of silicon wafers from 2D images of printed circuits taken with a scanning electron microscope. Our reconstruction method combines the physical model of the optical acquisition system with prior knowledge about the shapes of the patterns in the circuit; the result is a shape-from-shading technique with a shape prior. The reconstruction of the surface is formulated as an optimization problem with an objective functional that combines a data-fidelity term on the microscopic image with two prior terms on the surface. The data term models the acquisition system through the irradiance equation characteristic of the microscope; the first prior is a smoothness penalty on the reconstructed surface, and the second prior constrains the shape of the surface to agree with the expected shape of the pattern in the circuit. In order to account for the variability of the manufacturing process, this second prior includes a deformation field that allows a nonlinear elastic deformation between the expected pattern and the reconstructed surface. As a result, the minimization problem has two unknowns, and the reconstruction method provides two outputs: 1) a reconstructed surface and 2) a deformation field. The reconstructed surface is derived from the shading observed in the image and the prior knowledge about the pattern in the circuit, while the deformation field produces a mapping between the expected shape and the reconstructed surface that provides a measure of deviation between the circuit design models and the real manufacturing process.
Wang, Xiuhong; Mao, Xingpeng; Wang, Yiming; Zhang, Naitong; Li, Bo
2016-01-01
Based on sparse representations, the problem of two-dimensional (2-D) direction of arrival (DOA) estimation is addressed in this paper. A novel sparse 2-D DOA estimation method, called Dimension Reduction Sparse Reconstruction (DRSR), is proposed with pairing by Spatial Spectrum Reconstruction of Sub-Dictionary (SSRSD). By utilizing the angle decoupling method, which transforms a 2-D estimation into two independent one-dimensional (1-D) estimations, the high computational complexity induced by a large 2-D redundant dictionary is greatly reduced. Furthermore, a new angle matching scheme, SSRSD, which is less sensitive to the sparse reconstruction error with higher pair-matching probability, is introduced. The proposed method can be applied to any type of orthogonal array without requirement of a large number of snapshots and a priori knowledge of the number of signals. The theoretical analyses and simulation results show that the DRSR-SSRSD method performs well for coherent signals, which performance approaches Cramer–Rao bound (CRB), even under a single snapshot and low signal-to-noise ratio (SNR) condition. PMID:27649191
Wang, Xiuhong; Mao, Xingpeng; Wang, Yiming; Zhang, Naitong; Li, Bo
2016-01-01
Based on sparse representations, the problem of two-dimensional (2-D) direction of arrival (DOA) estimation is addressed in this paper. A novel sparse 2-D DOA estimation method, called Dimension Reduction Sparse Reconstruction (DRSR), is proposed with pairing by Spatial Spectrum Reconstruction of Sub-Dictionary (SSRSD). By utilizing the angle decoupling method, which transforms a 2-D estimation into two independent one-dimensional (1-D) estimations, the high computational complexity induced by a large 2-D redundant dictionary is greatly reduced. Furthermore, a new angle matching scheme, SSRSD, which is less sensitive to the sparse reconstruction error with higher pair-matching probability, is introduced. The proposed method can be applied to any type of orthogonal array without requirement of a large number of snapshots and a priori knowledge of the number of signals. The theoretical analyses and simulation results show that the DRSR-SSRSD method performs well for coherent signals, which performance approaches Cramer-Rao bound (CRB), even under a single snapshot and low signal-to-noise ratio (SNR) condition. PMID:27649191
Maximum entropy image reconstruction from projections
NASA Astrophysics Data System (ADS)
Bara, N.; Murata, K.
1981-07-01
The maximum entropy method is applied to image reconstruction from projections, of which angular view is restricted. The relaxation parameters are introduced to the maximum entropy reconstruction and after iteration the median filtering is implemented. These procedures improve the quality of the reconstructed image from noisy projections
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
Chen, Mingqing; Cao, Kunlin; Zheng, Yefeng; Siochi, R Alfredo C
2013-08-01
This paper presents a novel method for respiratory motion compensated reconstruction for cone beam computed tomography (CBCT). The reconstruction is based on a time sequence of motion vector fields, which is generated by a dynamic geometrical object shape model. The dynamic model is extracted from the 2D projection images of the CBCT. The process of the motion extraction is converted into an optimal 3D multiple interrelated surface detection problem, which can be solved by computing a maximum flow in a 4D directed graph. The method was tested on 12 mega-voltage (MV) CBCT scans from three patients. Two sets of motion-artifact-free 3D volumes, full exhale (FE) and full inhale (FI) phases, were reconstructed for each daily scan. The reconstruction was compared with three other motion-compensated approaches based on quantification accuracy of motion and size. Contrast-to-noise ratio (CNR) was also quantified for image quality. The proposed approach has the best overall performance, with a relative tumor volume quantification error of 3.39 ± 3.64% and 8.57 ± 8.31% for FE and FI phases, respectively. The CNR near the tumor area is 3.85 ± 0.42 (FE) and 3.58 ± 3.33 (FI). These results show the clinical feasibility to use the proposed method to reconstruct motion-artifact-free MVCBCT volumes. PMID:23247845
NASA Astrophysics Data System (ADS)
Demirci, Stefanie; Kutter, Oliver; Manstad-Hulaas, Frode; Bauernschmitt, Robert; Navab, Nassir
2008-03-01
In the current clinical workflow of minimally invasive aortic procedures navigation tasks are performed under 2D or 3D angiographic imaging. Many solutions for navigation enhancement suggest an integration of the preoperatively acquired computed tomography angiography (CTA) in order to provide the physician with more image information and reduce contrast injection and radiation exposure. This requires exact registration algorithms that align the CTA volume to the intraoperative 2D or 3D images. Additional to the real-time constraint, the registration accuracy should be independent of image dissimilarities due to varying presence of medical instruments and contrast agent. In this paper, we propose efficient solutions for image-based 2D-3D and 3D-3D registration that reduce the dissimilarities by image preprocessing, e.g. implicit detection and segmentation, and adaptive weights introduced into the registration procedure. Experiments and evaluations are conducted on real patient data.
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.
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. PMID:27335531
Automatic masking for robust 3D-2D image registration in image-guided spine surgery
NASA Astrophysics Data System (ADS)
Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.
2016-03-01
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.
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
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.
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
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.
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.
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.
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.
Reconstructing HST Images of Asteroids
NASA Astrophysics Data System (ADS)
Storrs, A. D.; Bank, S.; Gerhardt, H.; Makhoul, K.
2003-12-01
We present reconstructions of images of 22 large main belt asteroids that were observed by Hubble Space Telescope with the Wide-Field/Planetary cameras. All images were restored with the MISTRAL program (Mugnier, Fusco, and Conan 2003) at enhanced spatial resolution. This is possible thanks to the well-studied and stable point spread function (PSF) on HST. We present some modeling of this process and determine that the Strehl ratio for WF/PC (aberrated) images can be improved to 130 ratio of 80 We will report sizes, shapes, and albedos for these objects, as well as any surface features. Images taken with the WFPC-2 instrument were made in a variety of filters so that it should be possible to investigate changes in mineralogy across the surface of the larger asteroids in a manner similar to that done on 4 Vesta by Binzel et al. (1997). Of particular interest are a possible water of hydration feature on 1 Ceres, and the non-observation of a constriction or gap between the components of 216 Kleopatra. Reduction of this data was aided by grant HST-GO-08583.08A from the Space Telescope Science Institute. References: Mugnier, L.M., T. Fusco, and J.-M. Conan, 2003. JOSA A (submitted) Binzel, R.P., Gaffey, M.J., Thomas, P.C., Zellner, B.H., Storrs, A.D., and Wells, E.N. 1997. Icarus 128 pp. 95-103
A new iterative reconstruction algorithm for 2D exterior fan-beam CT.
Zeng, Li; Liu, Baodong; Liu, Linghui; Xiang, Caibing
2010-01-01
The exterior computed tomography (CT) problem is one kind of truncation problem. It is very ill-posed, so that accurate reconstruction of the attenuation function is hardly possible from real data. Based on projection onto convex sets (POCS) algorithm, total variation minimization (TVM) methods, and C-V model, we develop and investigate a new iterative reconstruction algorithm, which is referred to as subregion-averaged-TVM-POCS (SA-TVM-POCS). Numerical simulations are presented to illustrate the efficiency of the algorithm. The results of this paper can be easily applied to other x-ray CT reconstruction problems.
Image reconstruction via truncated lambda tomography
NASA Astrophysics Data System (ADS)
Yu, Hengyong; Ye, Yangbo; Wang, Ge
2006-08-01
This paper investigates the feasibility of reconstructing a Computed Tomography (CT) image from truncated Lambda Tomography (LT), a gradient-like image of it's original. An LT image can be regarded as a convolution of the object image and the point spread function (PSF) of the Calderon operator. The PSF's infinite support provides the LT image infinite support; even the original CT image is of compact support. When the support of a truncated LT image fully covers the compact support of the corresponding CT image, we develop an extrapolation method to recover the CT image more precisely. When the support of the CT image fully covers the support of the truncated LT image, we design a template-based scheme to compensate the cupping effects and reconstruct a satisfactory image. Our algorithms are evaluated in numerical simulations and the results demonstrate the feasibilities of our methods. Our approaches provide a new way to reconstruct high-quality CT images.
Heuristic reconstructions of neutron penumbral images
Nozaki, Shinya; Chen Yenwei
2004-10-01
Penumbral imaging is a technique of coded aperture imaging proposed for imaging of highly penetrating radiations. To date, the penumbral imaging technique has been successfully applied to neutron imaging in laser fusion experiments. Since the reconstruction of penumbral images is based on linear deconvolution methods, such as inverse filter and Wiener filer, the point spread function of apertures should be space invariant; it is also sensitive to the noise contained in penumbral images. In this article, we propose a new heuristic reconstruction method for neutron penumbral imaging, which can be used for a space-variant imaging system and is also very tolerant to the noise.
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 electron cyclotron emission imaging at ASDEX Upgrade (invited)a)
NASA Astrophysics Data System (ADS)
Classen, I. G. J.; Boom, J. E.; Suttrop, W.; Schmid, E.; Tobias, B.; Domier, C. W.; Luhmann, N. C.; Donné, A. J. H.; Jaspers, R. J. E.; de Vries, P. C.; Park, H. K.; Munsat, T.; García-Muñoz, M.; Schneider, P. A.
2010-10-01
The newly installed electron cyclotron emission imaging diagnostic on ASDEX Upgrade provides measurements of the 2D electron temperature dynamics with high spatial and temporal resolution. An overview of the technical and experimental properties of the system is presented. These properties are illustrated by the measurements of the edge localized mode and the reversed shear Alfvén eigenmode, showing both the advantage of having a two-dimensional (2D) measurement, as well as some of the limitations of electron cyclotron emission measurements. Furthermore, the application of singular value decomposition as a powerful tool for analyzing and filtering 2D data is presented.
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.
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.
Pothuaud, Laurent; Carceller, Pascal; Hans, Didier
2008-04-01
X-ray imaging remains a very cost-effective technique, with many applications in both medical and material science. However, the physical process of X-ray imaging transforms (e.g. projects) the 3-dimensional (3D) microarchitecture of the object or tissue being studied into a complex 2D grey-level texture. The 3D/2D projection process continues to be a difficult mathematical problem, and neither demonstrations nor well-established correlations have positioned 2D texture analysis-based measurement as a valid indirect evaluation of 3D microarchitecture. The trabecular bone score (TBS) is a new grey-level texture measurement which utilizes experimental variograms of 2D projection images. The aim of the present study was to determine the level of correlation between the 3D characteristics of trabecular bone microarchitecture, as evaluated using muCT reconstruction, and TBS, as evaluated using 2D projection images derived directly from 3D muCT reconstruction. Analyses were performed using sets of human cadaver bone samples from different anatomical sites (lumbar spine, femoral neck, and distal radius). Significant correlations were established via standard multiple regression analysis, and via the use of a generic mathematical 3D/2D relationship. In both instances, the correlations established a significant relationship between TBS and two 3D characteristics of bone microarchitecture: bone volume fraction and mean bone thickness. In particular, it appears that TBS permits to accurately differentiate between two 3D microarchitectures that exhibit the same amount of bone, but different trabecular characteristics. These results demonstrate the existence of a robust and generic relationship, taking into consideration a simplified model of a 2D projection image. Ultimately, this may lead to using TBS measurements directly on DXA images obtained in routine clinical practice.
Geometric uncertainty of 2D projection imaging in monitoring 3D tumor motion
NASA Astrophysics Data System (ADS)
Suh, Yelin; Dieterich, Sonja; Keall, Paul J.
2007-07-01
The purpose of this study was to investigate the accuracy of two-dimensional (2D) projection imaging methods in three-dimensional (3D) tumor motion monitoring. Many commercial linear accelerator types have projection imaging capabilities, and tumor motion monitoring is useful for motion inclusive, respiratory gated or tumor tracking strategies. Since 2D projection imaging is limited in its ability to resolve the motion along the imaging beam axis, there is unresolved motion when monitoring 3D tumor motion. From the 3D tumor motion data of 160 treatment fractions for 46 thoracic and abdominal cancer patients, the unresolved motion due to the geometric limitation of 2D projection imaging was calculated as displacement in the imaging beam axis for different beam angles and time intervals. The geometric uncertainty to monitor 3D motion caused by the unresolved motion of 2D imaging was quantified using the root-mean-square (rms) metric. Geometric uncertainty showed interfractional and intrafractional variation. Patient-to-patient variation was much more significant than variation for different time intervals. For the patient cohort studied, as the time intervals increase, the rms, minimum and maximum values of the rms uncertainty show decreasing tendencies for the lung patients but increasing for the liver and retroperitoneal patients, which could be attributed to patient relaxation. Geometric uncertainty was smaller for coplanar treatments than non-coplanar treatments, as superior-inferior (SI) tumor motion, the predominant motion from patient respiration, could be always resolved for coplanar treatments. Overall rms of the rms uncertainty was 0.13 cm for all treatment fractions and 0.18 cm for the treatment fractions whose average breathing peak-trough ranges were more than 0.5 cm. The geometric uncertainty for 2D imaging varies depending on the tumor site, tumor motion range, time interval and beam angle as well as between patients, between fractions and within a
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.
Nanohole-array-based device for 2D snapshot multispectral imaging
Najiminaini, Mohamadreza; Vasefi, Fartash; Kaminska, Bozena; Carson, Jeffrey J. L.
2013-01-01
We present a two-dimensional (2D) snapshot multispectral imager that utilizes the optical transmission characteristics of nanohole arrays (NHAs) in a gold film to resolve a mixture of input colors into multiple spectral bands. The multispectral device consists of blocks of NHAs, wherein each NHA has a unique periodicity that results in transmission resonances and minima in the visible and near-infrared regions. The multispectral device was illuminated over a wide spectral range, and the transmission was spectrally unmixed using a least-squares estimation algorithm. A NHA-based multispectral imaging system was built and tested in both reflection and transmission modes. The NHA-based multispectral imager was capable of extracting 2D multispectral images representative of four independent bands within the spectral range of 662 nm to 832 nm for a variety of targets. The multispectral device can potentially be integrated into a variety of imaging sensor systems. PMID:24005065
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
Optimal reconstruction of images from localized phase.
Urieli, S; Porat, M; Cohen, N
1998-01-01
The importance of localized phase in signal representation is investigated. The convergence rate of the POCS algorithm (projection onto convex sets) used for image reconstruction from spectral phase is defined and analyzed, and the characteristics of images optimally reconstructed from phase-only information are presented. It is concluded that images of geometric form are most efficiently reconstructed from their spectral phase, whereas images of symmetric form have the poorest convergence characteristics. The transition between the two extremes is shown to be continuous. The results provide a new approach and analysis of the previously reported advantages of the localized phase representation over the global approach, and suggest possible compression schemes.
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
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.
NASA Technical Reports Server (NTRS)
Newman, Timothy; Santhanam, Naveen; Zhang, Huijuan; Gallagher, Dennis
2003-01-01
A new method for reconstructing the global 3D distribution of plasma densities in the plasmasphere from a limited number of 2D views is presented. The method is aimed at using data from the Extreme Ultra Violet (EUV) sensor on NASA s Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite. Physical properties of the plasmasphere are exploited by the method to reduce the level of inaccuracy imposed by the limited number of views. The utility of the method is demonstrated on synthetic data.
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
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
Gil, Bomi; Hwang, Eo-Jin; Lee, Song; Jang, Jinhee; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-soo
2016-01-01
Introduction To compare the diagnostic accuracy of contrast-enhanced 3D(dimensional) T1-weighted sampling perfection with application-optimized contrasts by using different flip angle evolutions (T1-SPACE), 2D fluid attenuated inversion recovery (FLAIR) images and 2D contrast-enhanced T1-weighted image in detection of leptomeningeal metastasis except for invasive procedures such as a CSF tapping. Materials and Methods Three groups of patients were included retrospectively for 9 months (from 2013-04-01 to 2013-12-31). Group 1 patients with positive malignant cells in CSF cytology (n = 22); group 2, stroke patients with steno-occlusion in ICA or MCA (n = 16); and group 3, patients with negative results on MRI, whose symptom were dizziness or headache (n = 25). A total of 63 sets of MR images are separately collected and randomly arranged: (1) CE 3D T1-SPACE; (2) 2D FLAIR; and (3) CE T1-GRE using a 3-Tesla MR system. A faculty neuroradiologist with 8-year-experience and another 2nd grade trainee in radiology reviewed each MR image- blinded by the results of CSF cytology and coded their observations as positives or negatives of leptomeningeal metastasis. The CSF cytology result was considered as a gold standard. Sensitivity and specificity of each MR images were calculated. Diagnostic accuracy was compared using a McNemar’s test. A Cohen's kappa analysis was performed to assess inter-observer agreements. Results Diagnostic accuracy was not different between 3D T1-SPACE and CSF cytology by both raters. However, the accuracy test of 2D FLAIR and 2D contrast-enhanced T1-weighted GRE was inconsistent by the two raters. The Kappa statistic results were 0.657 (3D T1-SPACE), 0.420 (2D FLAIR), and 0.160 (2D contrast-enhanced T1-weighted GRE). The 3D T1-SPACE images showed the highest inter-observer agreements between the raters. Conclusions Compared to 2D FLAIR and 2D contrast-enhanced T1-weighted GRE, contrast-enhanced 3D T1 SPACE showed a better detection rate of
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.
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.
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.
Robust 2D phase correction for echo planar imaging under a tight field-of-view.
Xu, Dan; King, Kevin F; Zur, Yuval; Hinks, R Scott
2010-12-01
Nyquist ghost artifacts are a serious issue in echo planar imaging. These artifacts primarily originate from phase difference between even and odd echo images and can be removed or reduced using phase correction methods. The commonly used 1D phase correction can only correct phase difference along readout axis. 2D correction is, therefore, necessary when phase difference presents along both readout and phase encoding axes. However, existing 2D methods have several unaddressed issues that affect their practicality. These issues include uncharacterized noise behavior, image artifact due to unoptimized phase estimation, Gibbs ringing artifact when directly applying to partial k(y) data, and most seriously a new image artifact under tight field-of-view (i.e., field-of-view slightly smaller than object size). All these issues are addressed in this article. Specifically, theoretical analysis of noise amplification and effect of phase estimation error is provided, and tradeoff between noise and ghost is studied. A new 2D phase correction method with improved polynomial fitting, joint homodyne processing and phase correction, compatibility with tight field-of-view is then proposed. Various results show that the proposed method can robustly generate images free of Nyquist ghosts and other image artifacts even in oblique scans or when cross-term eddy current terms are significant. PMID:20806354
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
NASA Astrophysics Data System (ADS)
Klein, Jonathan; Peters, Christoph; Martín, Jaime; Laurenzis, Martin; Hullin, Matthias B.
2016-08-01
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.
Tracking objects outside the line of sight using 2D intensity images.
Klein, Jonathan; Peters, Christoph; Martín, Jaime; Laurenzis, Martin; Hullin, Matthias B
2016-08-31
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.
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
Research on 2D representation method of wireless Micro-Ball endoscopic images.
Wang, Dan; Xie, Xiang; Li, Guolin; Gu, Yingke; Yin, Zheng; Wang, Zhihua
2012-01-01
Nowadays the interpretation of the images acquired by wireless endoscopy system is a tedious job for doctors. A viable solution is to construct a map, which is the 2D representation of gastrointestinal (GI) tract to reduce the redundancy of images and improve the understandability of them. The work reported in this paper addresses the problem of the 2D representation of GI tract based on a new wireless Micro-Ball endoscopy system with multiple image sensors. This paper firstly models the problem of constructing the map, and then discusses mainly on the issues of perspective distortion correction, image preprocessing and image registration, which lie in the whole problem. The perspective distortion correction algorithm is realized based on attitude angles, while the image registration is based on phase correlation method (PCM) and scale invariant feature transform (SIFT) combined with particular image preprocessing methods. Based on R channels of images, the algorithm can deal with 26.3% to 100% of image registration when the ratio of overlap varies from 25% to 80%. The performance and effectiveness of the algorithms are verified by experiments.
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.
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.
A quantitative damage imaging technique based on enhanced CCRTM for composite plates using 2D scan
NASA Astrophysics Data System (ADS)
He, Jiaze; Yuan, Fuh-Gwo
2016-10-01
A two-dimensional (2D) 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 wafer mounted on the composite plate and a laser Doppler vibrometer (LDV) for scanning a region in the vicinity of the PZT to capture the scattered wavefield. 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, a reflectivity coefficients of the delamination is calculated and potentially related to damage severity. Comparisons are made in terms of damage imaging quality between 2D areal scans and 1D line scans as well as between the proposed and existing imaging conditions. The experimental results show that the 2D 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.
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.
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.
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
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.
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.
Occluded target viewing and identification high-resolution 2D imaging laser radar
NASA Astrophysics Data System (ADS)
Grasso, Robert J.; Dippel, George F.; Cecchetti, Kristen D.; Wikman, John C.; Drouin, David P.; Egbert, Paul I.
2007-09-01
BAE SYSTEMS has developed a high-resolution 2D imaging laser radar (LADAR) system that has proven its ability to detect and identify hard targets in occluded environments, through battlefield obscurants, and through naturally occurring image-degrading atmospheres. Limitations of passive infrared imaging for target identification using medium wavelength infrared (MWIR) and long wavelength infrared (LWIR) atmospheric windows are well known. Of particular concern is that as wavelength is increased the aperture must be increased to maintain resolution, hence, driving apertures to be very larger for long-range identification; impractical because of size, weight, and optics cost. Conversely, at smaller apertures and with large f-numbers images may become photon starved with long integration times. Here, images are most susceptible to distortion from atmospheric turbulence, platform vibration, or both. Additionally, long-range identification using passive thermal imaging is clutter limited arising from objects in close proximity to the target object.
Reconfigurable 2D cMUT-ASIC arrays for 3D ultrasound image
NASA Astrophysics Data System (ADS)
Song, Jongkeun; Jung, Sungjin; Kim, Youngil; Cho, Kyungil; Kim, Baehyung; Lee, Seunghun; Na, Junseok; Yang, Ikseok; Kwon, Oh-kyong; Kim, Dongwook
2012-03-01
This paper describes the design and implementations of the complete 2D capacitive micromachined ultrasound transducer electronics and its analog front-end module for transmitting high voltage ultrasound pulses and receiving its echo signals to realize 3D ultrasound image. In order to minimize parasitic capacitances and ultimately improve signal-to- noise ratio (SNR), cMUT has to be integrate with Tx/Rx electronics. Additionally, in order to integrate 2D cMUT array module, significant optimized high voltage pulser circuitry, low voltage analog/digital circuit design and packaging challenges are required due to high density of elements and small pitch of each element. We designed 256(16x16)- element cMUT and reconfigurable driving ASIC composed of 120V high voltage pulser, T/R switch, low noise preamplifier and digital control block to set Tx frequency of ultrasound and pulse train in each element. Designed high voltage analog ASIC was successfully bonded with 2D cMUT array by flip-chip bonding process and it connected with analog front-end board to transmit pulse-echo signals. This implementation of reconfigurable cMUT-ASIC-AFE board enables us to produce large aperture 2D transducer array and acquire high quality of 3D ultrasound image.
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.
Bayesian image reconstruction - The pixon and optimal image modeling
NASA Technical Reports Server (NTRS)
Pina, R. K.; Puetter, R. C.
1993-01-01
In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.
The start-to-end chemometric image processing of 2D thin-layer videoscans.
Komsta, Łukasz; Cieśla, Łukasz; Bogucka-Kocka, Anna; Józefczyk, Aleksandra; Kryszeń, Jakub; Waksmundzka-Hajnos, Monika
2011-05-13
The purpose of the research was to recommend a unified procedure of image preprocessing of 2D thin layer videoscans for further supervised or unsupervised chemometric analysis. All work was done with open source software. The videoscans saved as JPG files underwent the following procedures: denoising using a median filter, baseline removal with the rollerball algorithm and nonlinear warping using spline functions. The application of the proposed procedure enabled filtration of random difference between images (background intensity changes and spatial differences of the spots location). After the preprocessing only spot intensities have an influence on the performed PCA or other techniques. The proposed technique was successfully applied to recognize the differences between three Carex species from the 2D videoscans of the extracts. The proposed solution may be of value for the any chemometric task--both unsupervised and supervised.
On 2-D recursive LMS algorithms using ARMA prediction for ADPCM encoding of images.
Chung, Y S; Kanefsky, M
1992-01-01
A two-dimensional (2D) linear predictor which has an autoregressive moving average (ARMA) representation well as a bias term is adapted for adaptive differential pulse code modulation (ADPCM) encoding of nonnegative images. The predictor coefficients are updated by using a 2D recursive LMS (TRLMS) algorithm. A constraint on optimum values for the convergence factors and an updating algorithm based on the constraint are developed. The coefficient updating algorithm can be modified with a stability control factor. This realization can operate in real time and in the spatial domain. A comparison of three different types of predictors is made for real images. ARMA predictors show improved performance relative to an AR algorithm. PMID:18296174
Image Pretreatment Tools II: Normalization Techniques for 2-DE and 2-D DIGE.
Robotti, Elisa; Marengo, Emilio; Quasso, Fabio
2016-01-01
Gel electrophoresis is usually applied to identify different protein expression profiles in biological samples (e.g., control vs. pathological, control vs. treated). Information about the effect to be investigated (a pathology, a drug, a ripening effect, etc.) is however generally confounded with experimental variability that is quite large in 2-DE and may arise from small variations in the sample preparation, reagents, sample loading, electrophoretic conditions, staining and image acquisition. Obtaining valid quantitative estimates of protein abundances in each map, before the differential analysis, is therefore fundamental to provide robust candidate biomarkers. Normalization procedures are applied to reduce experimental noise and make the images comparable, improving the accuracy of differential analysis. Certainly, they may deeply influence the final results, and to this respect they have to be applied with care. Here, the most widespread normalization procedures are described both for what regards the applications to 2-DE and 2D Difference Gel-electrophoresis (2-D DIGE) maps.
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.
Evolutionary approach to image reconstruction from projections
NASA Astrophysics Data System (ADS)
Nakao, Zensho; Ali, Fathelalem F.; Takashibu, Midori; Chen, Yen-Wei
1997-10-01
We present an evolutionary approach for reconstructing CT images; the algorithm reconstructs two-dimensional unknown images from four one-dimensional projections. A genetic algorithm works on a randomly generated population of strings each of which contains encodings of an image. The traditional, as well as new, genetic operators are applied on each generation. The mean square error between the projection data of the image encoded into a string and original projection data is used to estimate the string fitness. A Laplacian constraint term is included in the fitness function of the genetic algorithm for handling smooth images. Two new modified versions of the original genetic algorithm are presented. Results obtained by the original algorithm and the modified versions are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the evolutionary method is more effective than ART in the particular case of limiting projection directions to four.
Multiresolution reconstruction method to optoacoustic imaging
NASA Astrophysics Data System (ADS)
Patrickeyev, Igor; Oraevsky, Alexander A.
2003-06-01
A new method for reconstruction of optoacoustic images is proposed. The method of image reconstruction incorporates multiresolution wavelet filtering into spherical back-projection algorithm. According to our method, each optoacoustic signal detected with an array of ultrawide-band transducers is decomposed into a set of self-similar wavelets with different resolution (characteristic frequency) and then back-projected along the spherical traces for each resolution scale separately. The advantage of this approach is that one can reconstruct objects of a preferred size or a range of sizes. The sum of all images reconstructed with different resolutions yields an image that visualizes small and large objects at once. An approximate speed of the proposed algorithm is of the same order as algorithm, based on the Fast Fourier Transform (FFT). The accuracy of the proposed method is illustrated by images, which are reconstructed from simulated optoacoustic signals as well as signals measured with the Laser Optoacoustic Imaging System (LOIS) from a loop of blood vessel embedded in a gel phantom. The method can be used for contrast-enhanced optoacoustic imaging in the depth of tissue, i.e. for medical applications such as breast cancer or prostate cancer detection.
Image quality of up-converted 2D video from frame-compatible 3D video
NASA Astrophysics Data System (ADS)
Speranza, Filippo; Tam, Wa James; Vázquez, Carlos; Renaud, Ronald; Blanchfield, Phil
2011-03-01
In the stereoscopic frame-compatible format, the separate high-definition left and high-definition right views are reduced in resolution and packed to fit within the same video frame as a conventional two-dimensional high-definition signal. This format has been suggested for 3DTV since it does not require additional transmission bandwidth and entails only small changes to the existing broadcasting infrastructure. In some instances, the frame-compatible format might be used to deliver both 2D and 3D services, e.g., for over-the-air television services. In those cases, the video quality of the 2D service is bound to decrease since the 2D signal will have to be generated by up-converting one of the two views. In this study, we investigated such loss by measuring the perceptual image quality of 1080i and 720p up-converted video as compared to that of full resolution original 2D video. The video was encoded with either a MPEG-2 or a H.264/AVC codec at different bit rates and presented for viewing with either no polarized glasses (2D viewing mode) or with polarized glasses (3D viewing mode). The results confirmed a loss of video quality of the 2D video up-converted material. The loss due to the sampling processes inherent to the frame-compatible format was rather small for both 1080i and 720p video formats; the loss became more substantial with encoding, particularly for MPEG-2 encoding. The 3D viewing mode provided higher quality ratings, possibly because the visibility of the degradations was reduced.
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.
Extraction of Individual Filaments from 2D Confocal Microscopy Images of Flat Cells.
Basu, Saurav; Chi Liu; Rohde, Gustavo Kunde
2015-01-01
A crucial step in understanding the architecture of cells and tissues from microscopy images, and consequently explain important biological events such as wound healing and cancer metastases, is the complete extraction and enumeration of individual filaments from the cellular cytoskeletal network. Current efforts at quantitative estimation of filament length distribution, architecture and orientation from microscopy images are predominantly limited to visual estimation and indirect experimental inference. Here we demonstrate the application of a new algorithm to reliably estimate centerlines of biological filament bundles and extract individual filaments from the centerlines by systematically disambiguating filament intersections. We utilize a filament enhancement step followed by reverse diffusion based filament localization and an integer programming based set combination to systematically extract accurate filaments automatically from microscopy images. Experiments on simulated and real confocal microscope images of flat cells (2D images) show efficacy of the new method.
Night vision image fusion for target detection with improved 2D maximum entropy segmentation
NASA Astrophysics Data System (ADS)
Bai, Lian-fa; Liu, Ying-bin; Yue, Jiang; Zhang, Yi
2013-08-01
Infrared and LLL image are used for night vision target detection. In allusion to the characteristics of night vision imaging and lack of traditional detection algorithm for segmentation and extraction of targets, we propose a method of infrared and LLL image fusion for target detection with improved 2D maximum entropy segmentation. Firstly, two-dimensional histogram was improved by gray level and maximum gray level in weighted area, weights were selected to calculate the maximum entropy for infrared and LLL image segmentation by using the histogram. Compared with the traditional maximum entropy segmentation, the algorithm had significant effect in target detection, and the functions of background suppression and target extraction. And then, the validity of multi-dimensional characteristics AND operation on the infrared and LLL image feature level fusion for target detection is verified. Experimental results show that detection algorithm has a relatively good effect and application in target detection and multiple targets detection in complex background.
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)
Antoine, Jean-Pierre; Vandergheynst, Pierre; Bouyoucef, Karim; Murenzi, Romain
1995-06-01
Both in 1D (signal analysis) and 2D (image processing), the wavelet transform (WT) has become by now a standard tool. Although the discrete version, based on multiresolution analysis, is probably better known, the continous WT (CWT) plays a crucial role for the detection and analysis of particular features in a signal, and we will focus here on the latter. In 2D however, one faces a practical problem. Indeed, the full parameter space of the wavelet transform of an image is 4D. It yields a representation of the image in position parameters (range and perception angle), as well as scale and anisotropy angle. The real challenge is to compute and visualize the full continuous wavelet transform in all four variables--obviously a demanding task. Thus, in order to obtain a manageable tool, some of the variables must be frozen. In other words, one must limit oneself to sections of the parameter space, usually 2D or 3D. For 2D sections, two variables are fixed and the transform is viewed as a function of the two remaing ones, and similarly for 3D sections. Among the six possible 2D sections, two play a privileged role. They yield respectively the position representation, which is the standard one, and the scale-angle representation, which has been proposed and studied systematically by two of us in a number of works. In this paper we will review these results and investigate the four remaining 2D representations. We will also make some comments on possible applications of 3D sections. The most spectacular property of the CWT is its ability at detecting discontinuities in a signal. In an image, this means in particular the sharp boundary between two regions of different luminosity, that is, a contour or an edge. Even more prominent in the transform are the corners of a given contour, for instance the contour of a letter. In a second part, we will exploit this property of the CWT and describe how one may design an algorithm for automatic character recognition (here we
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
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.
Computational acceleration for MR image reconstruction in partially parallel imaging.
Ye, Xiaojing; Chen, Yunmei; Huang, Feng
2011-05-01
In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images. PMID:20833599
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.
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
Dynamic 2D ultrasound and 3D CT image registration of the beating heart.
Huang, Xishi; Moore, John; Guiraudon, Gerard; Jones, Douglas L; Bainbridge, Daniel; Ren, Jing; Peters, Terry M
2009-08-01
Two-dimensional ultrasound (US) is widely used in minimally invasive cardiac procedures due to its convenience of use and noninvasive nature. However, the low quality of US images often limits their utility as a means for guiding procedures, since it is often difficult to relate the images to their anatomical context. To improve the interpretability of the US images while maintaining US as a flexible anatomical and functional real-time imaging modality, we describe a multimodality image navigation system that integrates 2D US images with their 3D context by registering them to high quality preoperative models based on magnetic resonance imaging (MRI) or computed tomography (CT) images. The mapping from such a model to the patient is completed using spatial and temporal registrations. Spatial registration is performed by a two-step rapid registration method that first approximately aligns the two images as a starting point to an automatic registration procedure. Temporal alignment is performed with the aid of electrocardiograph (ECG) signals and a latency compensation method. Registration accuracy is measured by calculating the TRE. Results show that the error between the US and preoperative images of a beating heart phantom is 1.7 +/-0.4 mm, with a similar performance being observed in in vivo animal experiments.
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
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.
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.
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.
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
Imaging Meso-Scale Structures in TEXTOR with 2D-ECE
NASA Astrophysics Data System (ADS)
Classen, I. G. J.; Jaspers, R. J. E.; Park, H. K.; Spakman, G. W.; van der Pol, M. J.; Domier, C. W.; Donne, A. J. H.; Luhmann, N. C., Jr.; Westerhof, E.; Jakubowski, M. W.; TEXTOR Team
The detection and control of instabilities in a tokamak is one of the exciting challenges in fusion research on the way to a reactor. Thanks to a combination of an innovative 2D temperature imaging technique (ECEI), a versatile ECRH/ECCD system and a unique possibility to externally induce tearing modes in the plasma, TEXTOR is able to make pioneering contributions in this field. This paper focuses on two meso-scale phenomena in tokamaks: m = 2 tearing modes and magnetic structures in the stochastic boundary. In these cases the 2D-ECEI diagnostic can resolve features not attainable before. In addition the possibility to use the diagnostic for fluctuation measurements is addressed.
Augmented depth perception visualization in 2D/3D image fusion.
Wang, Jian; Kreiser, Matthias; Wang, Lejing; Navab, Nassir; Fallavollita, Pascal
2014-12-01
2D/3D image fusion applications are widely used in endovascular interventions. Complaints from interventionists about existing state-of-art visualization software are usually related to the strong compromise between 2D and 3D visibility or the lack of depth perception. In this paper, we investigate several concepts enabling improvement of current image fusion visualization found in the operating room. First, a contour enhanced visualization is used to circumvent hidden information in the X-ray image. Second, an occlusion and depth color-coding scheme is considered to improve depth perception. To validate our visualization technique both phantom and clinical data are considered. An evaluation is performed in the form of a questionnaire which included 24 participants: ten clinicians and fourteen non-clinicians. Results indicate that the occlusion correction method provides 100% correctness when determining the true position of an aneurysm in X-ray. Further, when integrating an RGB or RB color-depth encoding in the image fusion both perception and intuitiveness are improved.
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.
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.
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.
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
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.
Estimating elastic properties of tissues from standard 2D ultrasound images
NASA Astrophysics Data System (ADS)
Kybic, Jan; Smutek, Daniel
2005-04-01
We propose a way of measuring elastic properties of tissues in-vivo, using standard medical image ultrasound machine without any special hardware. Images are acquired while the tissue is being deformed by a varying pressure applied by the operator on the hand-held ultrasound probe. The local elastic shear modulus is either estimated from a local displacement field reconstructed by an elastic registration algorithm, or both the modulus and the displacement are estimated simultaneously. The relation between modulus and displacement is calculated using a finite element method (FEM). The estimation algorithms were tested on both synthetic, phantom and real subject data.
Database-guided breast tumor detection and segmentation in 2D ultrasound images
NASA Astrophysics Data System (ADS)
Zhang, Jingdan; Zhou, Shaohua K.; Brunke, Shelby; Lowery, Carol; Comaniciu, Dorin
2010-03-01
Ultrasonography is a valuable technique for diagnosing breast cancer. Computer-aided tumor detection and segmentation in ultrasound images can reduce labor cost and streamline clinic workflows. In this paper, we propose a fully automatic system to detect and segment breast tumors in 2D ultrasound images. Our system, based on database-guided techniques, learns the knowledge of breast tumor appearance exemplified by expert annotations. For tumor detection, we train a classifier to discriminate between tumors and their background. For tumor segmentation, we propose a discriminative graph cut approach, where both the data fidelity and compatibility functions are learned discriminatively. The performance of the proposed algorithms is demonstrated on a large set of 347 images, achieving a mean contour-to-contour error of 3.75 pixels with about 4.33 seconds.
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.
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%.
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.
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
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
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
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…
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.
NASA Astrophysics Data System (ADS)
Sertoli, M.; Horváth, L.; Pokol, G. I.; Igochine, V.; Barrera, L.
2013-05-01
A new method for the reconstruction of two-dimensional (2D) electron temperature profiles in the presence of saturated magneto-hydro-dynamic (MHD) modes from the one-dimensional (1D) electron cyclotron emission (ECE) diagnostic is presented. The analysis relies on harmonic decomposition of the electron temperature oscillations through short time Fourier transforms and requires rigid poloidal mode rotation as the only assumption. The method is applicable to any magnetic perturbation as long as the poloidal and toroidal mode numbers m and n are known. Its application to the case of a (m, n) = (1, 1) internal kink mode on ASDEX Upgrade is presented and a new way to estimate the mode displacement is explained. For such modes, it is shown that the higher order harmonics usually visible in the ECE spectrogram arise also for the pure m = n = 1 mode and that they cannot be directly associated with m = n > 1 magnetic perturbations. This method opens up new possibilities for electron heat transport studies in the presence of saturated MHD modes and a way to disentangle the impurity density contributions from electron temperature effects in the analysis of the soft x-ray data.
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.
Iterative image reconstruction in spectral CT
NASA Astrophysics Data System (ADS)
Hernandez, Daniel; Michel, Eric; Kim, Hye S.; Kim, Jae G.; Han, Byung H.; Cho, Min H.; Lee, Soo Y.
2012-03-01
Scan time of spectral-CTs is much longer than conventional CTs due to limited number of x-ray photons detectable by photon-counting detectors. However, the spectral pixel information in spectral-CT has much richer information on physiological and pathological status of the tissues than the CT-number in conventional CT, which makes the spectral- CT one of the promising future imaging modalities. One simple way to reduce the scan time in spectral-CT imaging is to reduce the number of views in the acquisition of projection data. But, this may result in poorer SNR and strong streak artifacts which can severely compromise the image quality. In this work, spectral-CT projection data were obtained from a lab-built spectral-CT consisting of a single CdTe photon counting detector, a micro-focus x-ray tube and scan mechanics. For the image reconstruction, we used two iterative image reconstruction methods, the simultaneous iterative reconstruction technique (SIRT) and the total variation minimization based on conjugate gradient method (CG-TV), along with the filtered back-projection (FBP) to compare the image quality. From the imaging of the iodine containing phantoms, we have observed that SIRT and CG-TV are superior to the FBP method in terms of SNR and streak artifacts.
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.
Design of the 2D electron cyclotron emission imaging instrument for the J-TEXT tokamak
NASA Astrophysics Data System (ADS)
Pan, X. M.; Yang, Z. J.; Ma, X. D.; Zhu, Y. L.; Luhmann, N. C.; Domier, C. W.; Ruan, B. W.; Zhuang, G.
2016-11-01
A new 2D Electron Cyclotron Emission Imaging (ECEI) diagnostic is being developed for the J-TEXT tokamak. It will provide the 2D electron temperature information with high spatial, temporal, and temperature resolution. The new ECEI instrument is being designed to support fundamental physics investigations on J-TEXT including MHD, disruption prediction, and energy transport. The diagnostic contains two dual dipole antenna arrays corresponding to F band (90-140 GHz) and W band (75-110 GHz), respectively, and comprises a total of 256 channels. The system can observe the same magnetic surface at both the high field side and low field side simultaneously. An advanced optical system has been designed which permits the two arrays to focus on a wide continuous region or two radially separate regions with high imaging spatial resolution. It also incorporates excellent field curvature correction with field curvature adjustment lenses. An overview of the diagnostic and the technical progress including the new remote control technique are presented.
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
2D label-free imaging of resonant grating biochips in ultraviolet.
Bougot-Robin, K; Reverchon, J-L; Fromant, M; Mugherli, L; Plateau, P; Benisty, H
2010-05-24
2D images of label-free biochips exploiting resonant waveguide grating (RWG) are presented. They indicate sensitivities on the order of 1 pg/mm2 for proteins in air, and hence 10 pg/mm2 in water can be safely expected. A 320x256 pixels Aluminum-Gallium-Nitride-based sensor array is used, with an intrinsic narrow spectral window centered at 280 nm. The additional role of characteristic biological layer absorption at this wavelength is calculated, and regimes revealing its impact are discussed. Experimentally, the resonance of a chip coated with protein is revealed and the sensitivity evaluated through angular spectroscopy and imaging. In addition to a sensitivity similar to surface plasmon resonance (SPR), the RWGs resonance can be flexibly tailored to gain spatial, biochemical, or spectral sensitivity.
High contrast 2D visualization of edge plasma instabilities by ECE imaging
NASA Astrophysics Data System (ADS)
Yun, G. S.; Choi, M. J.; Lee, W.; Park, H. K.; Domier, C. W.; Luhmann, N. C., Jr.
2012-01-01
High contrast high resolution 2D images of edge MHD instabilities have been obtained for the KSTAR H-mode plasmas in 2010 using an electron cyclotron emission (ECE) imaging system. A fast structural evolution of the edge instabilities has been identified where the validity of the observed structures, i.e., the local measurement is ensured by the high contrast. On the other hand, the exact interpretation of the ECE intensity (Trad) is not straightforward due to the marginal optical depth ( ~ 1) in the plasma edge region. The effect of the electron temperature (Te) and density (ne) profiles in the edge region on the ECE localization and intensity have been evaluated for typical KSTAR H-mode discharges.
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.
Integrated Image Reconstruction and Gradient Nonlinearity Correction
Tao, Shengzhen; Trzasko, Joshua D.; Shu, Yunhong; Huston, John; Bernstein, Matt A.
2014-01-01
Purpose To describe a model-based reconstruction strategy for routine magnetic resonance imaging (MRI) that accounts for gradient nonlinearity (GNL) during rather than after transformation to the image domain, and demonstrate that this approach reduces the spatial resolution loss that occurs during strictly image-domain GNL-correction. Methods After reviewing conventional GNL-correction methods, we propose a generic signal model for GNL-affected MRI acquisitions, discuss how it incorporates into contemporary image reconstruction platforms, and describe efficient non-uniform fast Fourier transform (NUFFT)-based computational routines for these. The impact of GNL-correction on spatial resolution by the conventional and proposed approaches is investigated on phantom data acquired at varying offsets from gradient isocenter, as well as on fully-sampled and (retrospectively) undersampled in vivo acquisitions. Results Phantom results demonstrate that resolution loss that occurs during GNL-correction is significantly less for the proposed strategy than for the standard approach at distances >10 cm from isocenter with a 35 cm FOV gradient coil. The in vivo results suggest that the proposed strategy better preserves fine anatomical detail than retrospective GNL-correction while offering comparable geometric correction. Conclusion Accounting for GNL during image reconstruction allows geometric distortion to be corrected with less spatial resolution loss than is typically observed with the conventional image domain correction strategy. PMID:25298258
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.
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.
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.
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
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
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.
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)
Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu
2016-03-01
The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).
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
Mirror Surface Reconstruction from a Single Image.
Liu, Miaomiao; Hartley, Richard; Salzmann, Mathieu
2015-04-01
This paper tackles the problem of reconstructing the shape of a smooth mirror surface from a single image. In particular, we consider the case where the camera is observing the reflection of a static reference target in the unknown mirror. We first study the reconstruction problem given dense correspondences between 3D points on the reference target and image locations. In such conditions, our differential geometry analysis provides a theoretical proof that the shape of the mirror surface can be recovered if the pose of the reference target is known. We then relax our assumptions by considering the case where only sparse correspondences are available. In this scenario, we formulate reconstruction as an optimization problem, which can be solved using a nonlinear least-squares method. We demonstrate the effectiveness of our method on both synthetic and real images. We then provide a theoretical analysis of the potential degenerate cases with and without prior knowledge of the pose of the reference target. Finally we show that our theory can be similarly applied to the reconstruction of the surface of transparent object.
Sparse image reconstruction for molecular imaging.
Ting, Michael; Raich, Raviv; Hero, Alfred O
2009-06-01
The application that motivates this paper is molecular imaging at the atomic level. When discretized at subatomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. This paper, therefore, does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing the joint p.d.f. of the observation and image conditioned on the hyperparameters. A thresholding rule that generalizes the hard and soft thresholding rule appears in the course of the derivation. This so-called hybrid thresholding rule, when used in the iterative thresholding framework, gives rise to the hybrid estimator, a generalization of the lasso. Estimates of the hyperparameters for the lasso and hybrid estimator are obtained via Stein's unbiased risk estimate (SURE). A numerical study with a Gaussian psf and two sparse images shows that the hybrid estimator outperforms the lasso.
Speckle image reconstruction of the adaptive optics solar images.
Zhong, Libo; Tian, Yu; Rao, Changhui
2014-11-17
Speckle image reconstruction, in which the speckle transfer function (STF) is modeled as annular distribution according to the angular dependence of adaptive optics (AO) compensation and the individual STF in each annulus is obtained by the corresponding Fried parameter calculated from the traditional spectral ratio method, is used to restore the solar images corrected by AO system in this paper. The reconstructions of the solar images acquired by a 37-element AO system validate this method and the image quality is improved evidently. Moreover, we found the photometric accuracy of the reconstruction is field dependent due to the influence of AO correction. With the increase of angular separation of the object from the AO lockpoint, the relative improvement becomes approximately more and more effective and tends to identical in the regions far away the central field of view. The simulation results show this phenomenon is mainly due to the disparity of the calculated STF from the real AO STF with the angular dependence.
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.
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
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.
Quantizing calcification in the lumbar aorta on 2-D lateral x-ray images
NASA Astrophysics Data System (ADS)
Conrad-Hansen, Lars A.; Lauze, Francois; Tanko, Laszlo B.; Nielsen, Mads
2005-04-01
In this paper we seek to improve upon the standard method of assessing the degree of calcification in the lumbar aorta, which is commonly used on lateral 2-D x-rays. The necessity for improvement arises from the fact that the existing method can not measure subtle progressions in the plaque development; neither is it possible to express the density of individual plaques. Both of these qualities would be desireable to assess, since they are the key for making progression studies as well as for testing the effect of drugs in longitudinal studies. Our approach is based on inpainting, a technique used in image restoration as well as postprocessing of film. In this study we discuss the potential implications of total variation inpainting for characterizing aortic calcification.
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.
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
Directional adaptive deformable models for segmentation with application to 2D and 3D medical images
NASA Astrophysics Data System (ADS)
Rougon, Nicolas F.; Preteux, Francoise J.
1993-09-01
In this paper, we address the problem of adapting the functions controlling the material properties of 2D snakes, and show how introducing oriented smoothness constraints results in a novel class of active contour models for segmentation which extends standard isotropic inhomogeneous membrane/thin-plate stabilizers. These constraints, expressed as adaptive L2 matrix norms, are defined by two 2nd-order symmetric and positive definite tensors which are invariant with respect to rigid motions in the image plane. These tensors, equivalent to directional adaptive stretching and bending densities, are quadratic with respect to 1st- and 2nd-order derivatives of the image intensity, respectively. A representation theorem specifying their canonical form is established and a geometrical interpretation of their effects if developed. Within this framework, it is shown that, by achieving a directional control of regularization, such non-isotropic constraints consistently relate the differential properties (metric and curvature) of the deformable model with those of the underlying intensity surface, yielding a satisfying preservation of image contour characteristics.
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
Spatial anatomic knowledge for 2-D interactive medical image segmentation and matching.
Brinkley, J F
1991-01-01
A representation is described for two-dimensional anatomic shapes which can be described by single-valued distortions of a circle. The representation, called a radial contour model, is both generic, in that it captures the expected shape as well as the range of variation for an anatomic shape class, and flexible, in that the model can deform to fit an individual instance of the shape class. The model is implemented in a program called SCANNER (version 0.61) for 2-D interactive image segmentation and matching. An initial evaluation was performed using 7 shape models learned from a training set of 93 contours, and a control model containing no shape knowledge. Evaluation using 60 additional contours showed that in general the shape knowledge should reduce interactive segmentation time by a factor of two over the control, and that for specific shapes such as the eye, the improvement is much greater. A matching function was also devised which showed that the radial contour model should allow diagnosis of subtle shape changes. These results suggest that the use of spatial anatomic knowledge, when combined with good interactive tools, can help to alleviate the segmentation bottleneck in medical imaging. The models, when extended to more complex shapes, will form the spatial component of a knowledge base of anatomy that could have many uses in addition to image segmentation.
Three-dimensional volumetric object reconstruction using computational integral imaging.
Hong, Seung-Hyun; Jang, Ju-Seog; Javidi, Bahram
2004-02-01
We propose a three-dimensional (3D) imaging technique that can sense a 3D scene and computationally reconstruct it as a 3D volumetric image. Sensing of the 3D scene is carried out by obtaining elemental images optically using a pickup microlens array and a detector array. Reconstruction of volume pixels of the scene is accomplished by computationally simulating optical reconstruction according to ray optics. The entire pixels of the recorded elemental images contribute to volumetric reconstruction of the 3D scene. Image display planes at arbitrary distances from the display microlens array are computed and reconstructed by back propagating the elemental images through a computer synthesized pinhole array based on ray optics. We present experimental results of 3D image sensing and volume pixel reconstruction to test and verify the performance of the algorithm and the imaging system. The volume pixel values can be used for 3D image surface reconstruction.
Near Real-Time Solar Image Reconstruction
NASA Astrophysics Data System (ADS)
Yang, G.; Denker, C.; Wang, H.
2001-05-01
We use a Linux Beowulf cluster to build a system for near real-time solar image reconstruction with the goal to obtain diffraction limited solar images at a cadence of one minute. This gives us immediate access to high-level data products and enables direct visualization of dynamic processes on the Sun. Space weather warnings and flare forecasting will benefit from this project. The image processing algorithms are based on the speckle masking method combined with frame selection. The parallel programs use explicit message passing via Parallel Virtual Machine (PVM). The preliminary results are very promising. Now, we can construct a 256 by 256 pixel image out of 50 short-exposure images within one minute on a Beowulf cluster with four 500~MHz CPUs. In addition, we want to explore the possibility of applying parallel computing on Beowulf clusters to other complex data reduction and analysis problems that we encounter, e.g., in multi-dimensional spectro-polarimetry.
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.
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
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
Xu, Qiaofeng; Sidky, Emil Y; Pan, Xiaochuan; Stampanoni, Marco; Modregger, Peter; Anastasio, Mark A
2012-05-01
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.
Skerl, Darko . E-mail: franjo.pernus@fe.uni-lj.si; Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo
2006-07-01
Purpose: A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs) suitable for registration of CT or MR images to low-quality CBCTs. Methods and Materials: Using the recently proposed evaluation protocol, we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns. Results: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric multi-feature mutual information (AMMI). Conclusions: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the AMMI similarity measure is used.
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
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.
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
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.
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.
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.
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
Wan, Yong; Otsuna, Hideo; Chien, Chi-Bin; Hansen, Charles
2012-01-01
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.
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
2-D arterial wall motion imaging using ultrafast ultrasound and transverse oscillations.
Salles, Sebastien; Chee, Adrian J Y; Garcia, Damien; Yu, Alfred C H; Vray, Didier; Liebgott, Herve
2015-06-01
Ultrafast ultrasound is a promising imaging modality that enabled, inter alia, the development of pulse wave imaging and the local velocity estimation of the so-called pulse wave for a quantitative evaluation of arterial stiffness. However, this technique only focuses on the propagation of the axial displacement of the artery wall, and most techniques are not specific to the intima-media complex and do not take into account the longitudinal motion of this complex. Within this perspective, this paper presents a study of two-dimensional tissue motion estimation in ultrafast imaging combining transverse oscillations, which can improve motion estimation in the transverse direction, i.e., perpendicular to the beam axis, and a phase-based motion estimation. First, the method was validated in simulation. Two-dimensional motion, inspired from a real data set acquired on a human carotid artery, was applied to a numerical phantom to produce a simulation data set. The estimated motion showed axial and lateral mean errors of 4.2 ± 3.4 μm and 9.9 ± 7.9 μm, respectively. Afterward, experimental results were obtained on three artery phantoms with different wall stiffnesses. In this study, the vessel phantoms did not contain a pure longitudinal displacement. The longitudinal displacements were induced by the axial force produced by the wall's axial dilatation. This paper shows that the approach presented is able to perform 2-D tissue motion estimation very accurately even if the displacement values are very small and even in the lateral direction, making it possible to estimate the pulse wave velocity in both the axial and longitudinal directions. This demonstrates the method's potential to estimate the velocity of purely longitudinal waves propagating in the longitudinal direction. Finally, the stiffnesses of the three vessel phantom walls investigated were estimated with an average relative error of 2.2%. PMID:26067039
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.
2-D arterial wall motion imaging using ultrafast ultrasound and transverse oscillations.
Salles, Sebastien; Chee, Adrian J Y; Garcia, Damien; Yu, Alfred C H; Vray, Didier; Liebgott, Herve
2015-06-01
Ultrafast ultrasound is a promising imaging modality that enabled, inter alia, the development of pulse wave imaging and the local velocity estimation of the so-called pulse wave for a quantitative evaluation of arterial stiffness. However, this technique only focuses on the propagation of the axial displacement of the artery wall, and most techniques are not specific to the intima-media complex and do not take into account the longitudinal motion of this complex. Within this perspective, this paper presents a study of two-dimensional tissue motion estimation in ultrafast imaging combining transverse oscillations, which can improve motion estimation in the transverse direction, i.e., perpendicular to the beam axis, and a phase-based motion estimation. First, the method was validated in simulation. Two-dimensional motion, inspired from a real data set acquired on a human carotid artery, was applied to a numerical phantom to produce a simulation data set. The estimated motion showed axial and lateral mean errors of 4.2 ± 3.4 μm and 9.9 ± 7.9 μm, respectively. Afterward, experimental results were obtained on three artery phantoms with different wall stiffnesses. In this study, the vessel phantoms did not contain a pure longitudinal displacement. The longitudinal displacements were induced by the axial force produced by the wall's axial dilatation. This paper shows that the approach presented is able to perform 2-D tissue motion estimation very accurately even if the displacement values are very small and even in the lateral direction, making it possible to estimate the pulse wave velocity in both the axial and longitudinal directions. This demonstrates the method's potential to estimate the velocity of purely longitudinal waves propagating in the longitudinal direction. Finally, the stiffnesses of the three vessel phantom walls investigated were estimated with an average relative error of 2.2%.
Dynamic tracking of a deformable tissue based on 3D-2D MR-US image registration
NASA Astrophysics Data System (ADS)
Marami, Bahram; Sirouspour, Shahin; Fenster, Aaron; Capson, David W.
2014-03-01
Real-time registration of pre-operative magnetic resonance (MR) or computed tomography (CT) images with intra-operative Ultrasound (US) images can be a valuable tool in image-guided therapies and interventions. This paper presents an automatic method for dynamically tracking the deformation of a soft tissue based on registering pre-operative three-dimensional (3D) MR images to intra-operative two-dimensional (2D) US images. The registration algorithm is based on concepts in state estimation where a dynamic finite element (FE)- based linear elastic deformation model correlates the imaging data in the spatial and temporal domains. A Kalman-like filtering process estimates the unknown deformation states of the soft tissue using the deformation model and a measure of error between the predicted and the observed intra-operative imaging data. The error is computed based on an intensity-based distance metric, namely, modality independent neighborhood descriptor (MIND), and no segmentation or feature extraction from images is required. The performance of the proposed method is evaluated by dynamically deforming 3D pre-operative MR images of a breast phantom tissue based on real-time 2D images obtained from an US probe. Experimental results on different registration scenarios showed that deformation tracking converges in a few iterations. The average target registration error on the plane of 2D US images for manually selected fiducial points was between 0.3 and 1.5 mm depending on the size of deformation.
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.
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
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.
Birkfellner, Wolfgang; Stock, Markus; Figl, Michael; Gendrin, Christelle; Hummel, Johann; Dong, Shuo; Kettenbach, Joachim; Georg, Dietmar; Bergmann, Helmar
2010-01-01
In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman’s rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general. PMID:19746775
Helfer, Talita Micheletti; Peixoto, Alberto Borges; Tonni, Gabriele; Araujo Júnior, Edward
2016-09-01
Craniosynostosis is defined as the process of premature fusion of one or more of the cranial sutures. It is a common condition that occurs in about 1 to 2,000 live births. Craniosynostosis may be classified in primary or secondary. It is also classified as nonsyndromic or syndromic. According to suture commitment, craniosynostosis may affect a single suture or multiple sutures. There is a wide range of syndromes involving craniosynostosis and the most common are Apert, Pffeifer, Crouzon, Shaethre-Chotzen and Muenke syndromes. The underlying etiology of nonsyndromic craniosynostosis is unknown. Mutations in the fibroblast growth factor (FGF) signalling pathway play a crucial role in the etiology of craniosynostosis syndromes. Prenatal ultrasound`s detection rate of craniosynostosis is low. Nowadays, different methods can be applied for prenatal diagnosis of craniosynostosis, such as two-dimensional (2D) and three-dimensional (3D) ultrasound, magnetic resonance imaging (MRI), computed tomography (CT) scan and, finally, molecular diagnosis. The presence of craniosynostosis may affect the birthing process. Fetuses with craniosynostosis also have higher rates of perinatal complications. In order to avoid the risks of untreated craniosynostosis, children are usually treated surgically soon after postnatal diagnosis. PMID:27622416
Large resistive 2D Micromegas with genetic multiplexing and some imaging applications
NASA Astrophysics Data System (ADS)
Bouteille, S.; Attié, D.; Baron, P.; Calvet, D.; Magnier, P.; Mandjavidze, I.; Procureur, S.; Riallot, M.
2016-10-01
The performance of the first large resistive Micromegas detectors with 2D readout and genetic multiplexing is presented. These detectors have a 50 × 50cm2 active area and are equipped with 1024 strips both in X- and Y-directions. The same genetic multiplexing pattern is applied on both coordinates, resulting in the compression of signals on 2 × 61 readout channels. Four such detectors have been built at CERN, and extensively tested with cosmics. The resistive strip film allows for very high gain operation, compensating for the charge spread on the 2 dimensions as well as the S / N loss due to the huge, 1 nF input capacitance. This film also creates a significantly different signal shape in the X- and Y-coordinates due to the charge evacuation along the resistive strips. All in all a detection efficiency above 95% is achieved with a 1 cm drift gap. Though not yet optimal, the measured 300 μm spatial resolution allows for very precise imaging in the field of muon tomography, and some applications of these detectors are presented.
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
Patterson, S D; Latter, G I
1993-12-01
The advent of storage phosphor technology has been of considerable benefit to the imaging of gel-separated radiolabeled proteins due to the rapid and quantitative nature of the data acquisition process. Previously, times over one month were required to obtain fluorographs of the same gel to yield data of sufficient dynamic range for quantitative analysis of high-resolution two-dimensional (2-D) gels. As we are in the process of building a human 2-D gel protein database, and therefore have a high throughput of 2-D gels both to image and quantitate using the Quest II software, we undertook an evaluation of a storage phosphor imager, including an evaluation of signal fade. The results of this evaluation demonstrate the feasibility of using such a system, and we describe the procedures that allow us to use this technique for quantitative analysis of many complex 2-D gel patterns. These procedures include a useful batch printing program that allows printing of many images in a non-interactive mode. Examples will be presented of how autoradiography, using storage phosphor plates and the Quest II system, have enabled us to begin building a human 2-D gel protein database including posttranslational modification information, without the previous time constraints associated with such a project.
Detection of Cracks Using 2d Electrical Resistivity Imaging In A Cultivated Soil
NASA Astrophysics Data System (ADS)
Samouëlian, A.; Cousin, I.; Richard, G.; Bruand, A.
Variations of soil structure is significant for the understanding of water and gas trans- fer in soil profiles. In the context of arable land, soil structure can be compacted due to either agriculture operation (wheel tracks), or hardsetting and crusting processes. As a consequence, soil porosity is reduced which may lead to decrease water infiltra- tion and to anoxic conditions. Porosity can be increased by cracks formation due to swelling and shrinking phenomenon. We present here a laboratory experiment based on soil electrical characteristics. Electrical resistivity allows a non destructive three di- mensional and dynamical analysis of the soil structure. Our main objective is to detect cracks in the soil. Cracks form an electrical resistant object and the contrast of resis- tivity between air and soil is large enough to be detected. Our sample is an undisturbed soil block 240mm*170mm*160mm with an initial structure compacted by wheel traf- fic. Successive artificial cracks are generated. Electrodes built with 2 mm ceramic cups permit a good electrical contact at the soil surface whatever its water content. They are installed 15 mm apart and the electrical resistivity is monitored using a dipole-dipole and wenner multi-electrodes 2D imaging method which gives a picture of the subsur- face resistivity. The interpreted resistivity sections show the major soil structure. The electrical response changes with the cracks formation. The structure information ex- tracted from the electrical map are in good agreement with the artificially man-made cracks. These first results demonstrate the relevance of high resolution electrical imag- ing of the soil profile. Further experiments need to be carried out in order to monitor natural soil structure evolution during wetting-drying cycles.
Fast 2-D soft X-ray imaging device based on micro pattern gas detector
NASA Astrophysics Data System (ADS)
Pacella, D.; Bellazzini, R.; Brez, A.; Pizzicaroli, G.
2003-09-01
An innovative fast system for X-ray imaging has been developed at ENEA Frascati (Italy) to be used as diagnostic of magnetic plasmas for thermonuclear fusion. It is based on a pinhole camera coupled to a Micro Pattern Gas Detector (MPGD) having a Gas Electron Multiplier (GEM) as amplifying stage. This detector (2.5 cm × 2.5 cm active area) is equipped with a 2-D read-out printed circuit board with 144 pixels (12 × 12), with an electronic channel for each pixel (charge conversion, shaping, discrimination and counting). Working in photon counting mode, in proportional regime, it is able to get X-ray images of the plasma in a selectable X-ray energy range, at very high photon fluxes (106 ph s-̊1mm-2 all over the detector) and high framing rate (up to 100 kHz). It has very high dynamic range, high signal to noise ratio (statistical) and large flexibility in the optical configurations (magnification and views on the plasma). The system has been tested successfully on the Frascati Tokamak Upgrade (FTU), having central electron temperature of a few keV and density of 1020 m-3, during the summer 2001, with a one-dimensional perpendicular view of the plasma. In collaboration with ENEA, the Johns Hopkins University (JHU) and Princeton Plasma Physics (PPPL), this system has been set up and calibrated in the X-ray energy range 2-8 keV and it has been installed, with a two-dimensional tangential view, on the spherical tokamak NSTX at Princeton. Time resolved X-ray images of the NSTX plasma core have been obtained. Fast acquisitions, performed up to 50 kHz of framing rate, allow the study of the plasma evolution and its magneto-hydrodynamic instabilities, while with a slower sampling (a few kHz) the curvature of the magnetic surfaces can be measured. All these results reveal the good imaging properties of this device at high time resolution, despite of the low number of pixels, and the effectiveness of the fine controlled energy discrimination.
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.
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
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.
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.
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
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
Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts
Qin, Xulei; Wang, Silun; Shen, Ming; Zhang, Xiaodong; Lerakis, Stamatios; Wagner, Mary B.; Fei, Baowei
2015-01-01
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. PMID:26855466
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.
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.
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
2-D Precise Radiation Mapping of Sedimentary Core Using Imaging Plate
NASA Astrophysics Data System (ADS)
Sugihara, M.; Tsuchiya, N.
2006-12-01
The imaging plate (IP) is a storage film coated with photostimulated phosphor (BaFBr: Eu2+), and the latent images produced by irradiation of the imaging plate are read by superficial scanning with stimulation light and are reconstructed as two-dimensional dot images on a computer display. It has an excellent performance for radiation detection, and its advantages include an ease of use, a high position resolution (up to 25ƒÊm), a large detection area (up to 35'43cm2), a high detection sensitivity with high signal-to- noise ratio, an extremely wide dynamic range of dose, a sensitivity to several kinds of radiation, and an erasing capability for reuse (Hareyama et al., 2000). In this study, in order to develop a nondestructive, precise and large area evaluation method of sedimentary structure, an application of autoradiography using IP is attempted to marine sediments. Imaging plate (BAS-MS2040 Fujifilm Co. Ltd., 20'~40 cm2) was cut into rectangular five pieces (4'~40 cm2). Whole round marine sedimentary cores were divided into two half for duplicate and they were covered with a plastic wrap. The rectangular IP were put along the center line of plane side of half round. The exposure in the low temperature was for 48 hours in a shield box. The latent images produced by irradiation of the IP were read out by using the BAS-2500 imaging analyzer (Fujifilm Co. Ltd.). Radiation dose of IP is output as PSL value, that is unique dose units and quantities of IP system. Position resolution was set to 50ƒÊm. Marine sedimentary cores including volcanic ash layer were measured using IP and Natural Gamma Logger (NGL), which is measuring instrument for marine sediments in practice use, to compare their measuring ability. As a result of experiment, it becomes clear that high dose distribution is found at volcanic ash layer with IP, meanwhile it can't be found with NGL. The content of radiation source in volcanic ash layer is supposed to be high compared with other layers
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%.
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.
Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET.
Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E; Nuyts, Johan
2016-02-21
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. PMID:26854817
Gerber, Thomas; Liu Yuzhu; Knopp, Gregor; Hemberger, Patrick; Bodi, Andras; Radi, Peter; Sych, Yaroslav
2013-03-15
Velocity map imaging (VMI) is used in mass spectrometry and in angle resolved photo-electron spectroscopy to determine the lateral momentum distributions of charged particles accelerated towards a detector. VM-images are composed of projected Newton spheres with a common centre. The 2D images are usually evaluated by a decomposition into base vectors each representing the 2D projection of a set of particles starting from a centre with a specific velocity distribution. We propose to evaluate 1D projections of VM-images in terms of 1D projections of spherical functions, instead. The proposed evaluation algorithm shows that all distribution information can be retrieved from an adequately chosen set of 1D projections, alleviating the numerical effort for the interpretation of VM-images considerably. The obtained results produce directly the coefficients of the involved spherical functions, making the reconstruction of sliced Newton spheres obsolete.
Gerber, Thomas; Liu, Yuzhu; Knopp, Gregor; Hemberger, Patrick; Bodi, Andras; Radi, Peter; Sych, Yaroslav
2013-03-01
Velocity map imaging (VMI) is used in mass spectrometry and in angle resolved photo-electron spectroscopy to determine the lateral momentum distributions of charged particles accelerated towards a detector. VM-images are composed of projected Newton spheres with a common centre. The 2D images are usually evaluated by a decomposition into base vectors each representing the 2D projection of a set of particles starting from a centre with a specific velocity distribution. We propose to evaluate 1D projections of VM-images in terms of 1D projections of spherical functions, instead. The proposed evaluation algorithm shows that all distribution information can be retrieved from an adequately chosen set of 1D projections, alleviating the numerical effort for the interpretation of VM-images considerably. The obtained results produce directly the coefficients of the involved spherical functions, making the reconstruction of sliced Newton spheres obsolete.
NASA Astrophysics Data System (ADS)
Gerber, Thomas; Liu, Yuzhu; Knopp, Gregor; Hemberger, Patrick; Bodi, Andras; Radi, Peter; Sych, Yaroslav
2013-03-01
Velocity map imaging (VMI) is used in mass spectrometry and in angle resolved photo-electron spectroscopy to determine the lateral momentum distributions of charged particles accelerated towards a detector. VM-images are composed of projected Newton spheres with a common centre. The 2D images are usually evaluated by a decomposition into base vectors each representing the 2D projection of a set of particles starting from a centre with a specific velocity distribution. We propose to evaluate 1D projections of VM-images in terms of 1D projections of spherical functions, instead. The proposed evaluation algorithm shows that all distribution information can be retrieved from an adequately chosen set of 1D projections, alleviating the numerical effort for the interpretation of VM-images considerably. The obtained results produce directly the coefficients of the involved spherical functions, making the reconstruction of sliced Newton spheres obsolete.
Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging
NASA Astrophysics Data System (ADS)
Ishihara, Yasutoshi; Kuwabara, Tsuyoshi; Honma, Takumi; Nakagawa, Yohei
Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function—defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction 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.
Principles of MR image formation and reconstruction.
Duerk, J L
1999-11-01
This article describes a number of concepts that provide insights into the process of MR imaging. The use of shaped, fixed-bandwidth RF pulses and magnetic field gradients is described to provide an understanding of the methods used for slice selection. Variations in the slice-excitation profile are shown as a function of the RF pulse shape used, the truncation method used, and the tip angle. It should be remembered that although the goal is to obtain uniform excitation across the slice, this goal is never achieved in practice, thus necessitating the use of slice gaps in some cases. Excitation, refocusing, and inversion pulses are described. Excitation pulses nutate the spins from the longitudinal axis into the transverse plane, where their magnetization can be detected. Refocusing pulses are used to flip the magnetization through 180 degrees once it is in the transverse plane, so that the influence of magnetic field inhomogeneities is eliminated. Inversion pulses are used to flip the magnetization from the +z to the -z direction in invesrsion-recovery sequences. Radiofrequency pulses can also be used to eliminate either fat or water protons from the images because of the small differences in resonant frequency between these two types of protons. Selective methods based on chemical shift and binomial methods are described. Once the desired magnetization has been tipped into the transverse plane by the slice-selection process, two imaging axes remain to be spatially encoded. One axis is easily encoded by the application of a second magnetic field gradient that establishes a one-to-one mapping between position and frequency during the time that the signal is converted from analog to digital sampling. This frequency-encoding gradient is used in combination with the Fourier transform to determine the location of the precessing magnetization. The second image axis is encoded by a process known as phase encoding. The collected data can be described as the 2D Fourier
Diagnostic value of 2D and 3D imaging in odontogenic maxillary sinusitis: a review of literature.
Shahbazian, M; Jacobs, R
2012-04-01
This review aims to explore whether 3D imaging offers an added value in diagnosis of odontogenic sinusitis. Odontogenic maxillary sinusitis accounts for approximately 10-12% of maxillary sinusitis cases. Proper diagnosis of odontogenic sinusitis is based on a thorough dental and medical examination and crucial to ensure therapeutic efficacy. To establish the odontogenic cause of maxillary sinusitis, 2D and 3D imaging modalities may be considered, each presenting distinct advantages and drawbacks. The available research indicates that 2D imaging modalities may often mask the origin of odontogenic maxillary sinusitis. This limitation is particularly evident in the maxillary molar region, stressing the need for 3D cross-sectional imaging. The advent of low-dose cone beam computed tomography in dentistry may be particularly useful when odontogenic maxillary sinusitis is not responsive to therapy. Yet, it seems that more research is needed to validate its use in odontogenic maxillary sinusitis.
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)
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.
Otazo, Ricardo; Tsai, Shang-Yueh; Lin, Fa-Hsuan; Posse, Stefan
2007-12-01
MR spectroscopic imaging (MRSI) with whole brain coverage in clinically feasible acquisition times still remains a major challenge. A combination of MRSI with parallel imaging has shown promise to reduce the long encoding times and 2D acceleration with a large array coil is expected to provide high acceleration capability. In this work a very high-speed method for 3D-MRSI based on the combination of proton echo planar spectroscopic imaging (PEPSI) with regularized 2D-SENSE reconstruction is developed. Regularization was performed by constraining the singular value decomposition of the encoding matrix to reduce the effect of low-value and overlapped coil sensitivities. The effects of spectral heterogeneity and discontinuities in coil sensitivity across the spectroscopic voxels were minimized by unaliasing the point spread function. As a result the contamination from extracranial lipids was reduced 1.6-fold on average compared to standard SENSE. We show that the acquisition of short-TE (15 ms) 3D-PEPSI at 3 T with a 32 x 32 x 8 spatial matrix using a 32-channel array coil can be accelerated 8-fold (R = 4 x 2) along y-z to achieve a minimum acquisition time of 1 min. Maps of the concentrations of N-acetyl-aspartate, creatine, choline, and glutamate were obtained with moderate reduction in spatial-spectral quality. The short acquisition time makes the method suitable for volumetric metabolite mapping in clinical studies.
Otazo, Ricardo; Tsai, Shang-Yueh; Lin, Fa-Hsuan; Posse, Stefan
2007-12-01
MR spectroscopic imaging (MRSI) with whole brain coverage in clinically feasible acquisition times still remains a major challenge. A combination of MRSI with parallel imaging has shown promise to reduce the long encoding times and 2D acceleration with a large array coil is expected to provide high acceleration capability. In this work a very high-speed method for 3D-MRSI based on the combination of proton echo planar spectroscopic imaging (PEPSI) with regularized 2D-SENSE reconstruction is developed. Regularization was performed by constraining the singular value decomposition of the encoding matrix to reduce the effect of low-value and overlapped coil sensitivities. The effects of spectral heterogeneity and discontinuities in coil sensitivity across the spectroscopic voxels were minimized by unaliasing the point spread function. As a result the contamination from extracranial lipids was reduced 1.6-fold on average compared to standard SENSE. We show that the acquisition of short-TE (15 ms) 3D-PEPSI at 3 T with a 32 x 32 x 8 spatial matrix using a 32-channel array coil can be accelerated 8-fold (R = 4 x 2) along y-z to achieve a minimum acquisition time of 1 min. Maps of the concentrations of N-acetyl-aspartate, creatine, choline, and glutamate were obtained with moderate reduction in spatial-spectral quality. The short acquisition time makes the method suitable for volumetric metabolite mapping in clinical studies. PMID:17968995
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
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
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.
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.
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
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.
MMSE Reconstruction for 3D Freehand Ultrasound Imaging
Huang, Wei; Zheng, Yibin
2008-01-01
The reconstruction of 3D ultrasound (US) images from mechanically registered, but otherwise irregularly positioned, B-scan slices is of great interest in image guided therapy procedures. Conventional 3D ultrasound algorithms have low computational complexity, but the reconstructed volume suffers from severe speckle contamination. Furthermore, the current method cannot reconstruct uniform high-resolution data from several low-resolution B-scans. In this paper, the minimum mean-squared error (MMSE) method is applied to 3D ultrasound reconstruction. Data redundancies due to overlapping samples as well as correlation of the target and speckle are naturally accounted for in the MMSE reconstruction algorithm. Thus, the reconstruction process unifies the interpolation and spatial compounding. Simulation results for synthetic US images are presented to demonstrate the excellent reconstruction. PMID:18382623
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.
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.
Atsuchi, Masaru; Tsuji, Akiko; Usumoto, Yosuke; Yoshino, Mineo; Ikeda, Noriaki
2013-09-01
The number of criminal cases requiring facial image identification of a suspect has been increasing because a surveillance camera is installed everywhere in the city and furthermore, the intercom with the recording function is installed in the home. In this study, we aimed to analyze the usefulness of a 2D/3D facial image superimposition system for image identification when facial aging, facial expression, and twins are under consideration. As a result, the mean values of the average distances calculated from the 16 anatomical landmarks between the 3D facial images of the 50s groups and the 2D facial images of the 20s, 30s, and 40s groups were 2.6, 2.3, and 2.2mm, respectively (facial aging). The mean values of the average distances calculated from 12 anatomical landmarks between the 3D normal facial images and four emotional expressions were 4.9 (laughter), 2.9 (anger), 2.9 (sadness), and 3.6mm (surprised), respectively (facial expressions). The average distance obtained from 11 anatomical landmarks between the same person in twins was 1.1mm, while the average distance between different person in twins was 2.0mm (twins). Facial image identification using the 2D/3D facial image superimposition system demonstrated adequate statistical power and identified an individual with high accuracy, suggesting its usefulness. However, computer technology concerning video image processing and superimpose progress, there is a need to keep familiar with the morphology and anatomy as its base. PMID:23886899
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)
Lu, Yao; Ye, Hongwei; Xu, Yuesheng; Hu, Xiaofei; Vogelsang, Levon; Shen, Lixin; Feiglin, David; Lipson, Edward; Krol, Andrzej
2008-03-01
To improve the speed and quality of ordered-subsets expectation-maximization (OSEM) SPECT reconstruction, we have implemented a content-adaptive, singularity-based, mesh-domain, image model (CASMIM) with an accurate algorithm for estimation of the mesh-domain system matrix. A preliminary image, used to initialize CASMIM reconstruction, was obtained using pixel-domain OSEM. The mesh-domain representation of the image was produced by a 2D wavelet transform followed by Delaunay triangulation to obtain joint estimation of nodal locations and their activity values. A system matrix with attenuation compensation was investigated. Digital chest phantom SPECT was simulated and reconstructed. The quality of images reconstructed with OSEM-CASMIM is comparable to that from pixel-domain OSEM, but images are obtained five times faster by the CASMIM method.
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.
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.
Integration of 3D and 2D imaging data for assured navigation in unknown environments: initial steps
NASA Astrophysics Data System (ADS)
Dill, Evan; Uijt de Haag, Maarten
2009-05-01
This paper discusses the initial steps of the development of a novel navigation method that integrates three-dimensional (3D) point cloud data, two-dimensional (2D) gray-level (intensity), and data from an Inertial Measurement Unit (IMU). A time-of-flight camera such as MESA's Swissranger will output both the 3D and 2D data. The target application is position and attitude determination of unmanned aerial vehicles (UAV) and autonomous ground vehicles (AGV) in urban or indoor environments. In urban and indoor environments a GPS position capability may not only be unavailable due to shadowing, significant signal attenuation or multipath, but also due to intentional denial or deception. The proposed algorithm extracts key features such as planar surfaces, lines and corner-points from both the 3D (point-cloud) and 2D (intensity) imagery. Consecutive observations of corresponding features in the 3D and 2D image frames are then used to compute estimates of position and orientation changes. Since the use of 3D image features for positioning suffers from limited feature observability resulting in deteriorated position accuracies, and the 2D imagery suffers from an unknown depth when estimating the pose from consecutive image frames, it is expected that the integration of both data sets will alleviate the problems with the individual methods resulting in an position and attitude determination method with a high level of assurance. An Inertial Measurement Unit (IMU) is used to set up the tracking gates necessary to perform data association of the features in consecutive frames. Finally, the position and orientation change estimates can be used to correct for the IMU drift errors.
NASA Astrophysics Data System (ADS)
Mikhaylova, E.; Kolstein, M.; De Lorenzo, G.; Chmeissani, M.
2014-07-01
A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics.
A regularization-free Young's modulus reconstruction algorithm for ultrasound elasticity imaging.
Pan, Xiaochang; Gao, Jing; Shao, Jinhua; Luo, Jianwen; Bai, Jing
2013-01-01
Ultrasound elasticity imaging aims to reconstruct the distribution of elastic modulus (e.g., Young's modulus) within biological tissues, since the value of elastic modulus is often related to pathological changes. Currently, most elasticity imaging algorithms face a challenge of choosing the value of the regularization constant. We propose a more applicable algorithm without the need of any regularization. This algorithm is not only simple to use, but has a relatively high accuracy. Our method comprises of a nonrigid registration technique and tissue incompressibility assumption to estimate the two-dimensional (2D) displacement field, and finite element method (FEM) to reconstruct the Young's modulus distribution. Simulation and phantom experiments are performed to evaluate the algorithm. Simulation and phantom results showed that the proposed algorithm can reconstruct the Young's modulus with an accuracy of 63∼85%.
Noise and resolution of Bayesian reconstruction for multiple image configurations
Chinn, G.; Huang, Sung Cheng
1993-12-01
Images reconstructed by Bayesian and maximum-likelihood (ML) using a Gibbs prior with prior weight {beta} were compared with images produced by filtered back projection (FBP) from sinogram data simulated with different counts and image configurations. Bayesian images were generated by the OSL algorithm accelerated by an over relaxation parameter. For relatively low {beta}, Bayesian images can yield an overall improvement to the images compared to ML reconstruction. However, for larger {beta}, Bayesian images degrade from the standpoint of noise and quantitation. Compared to FBP, the ML images were superior in a mean square error sense in regions of low activity level and for small structures. At a comparable noise level to FBP, Bayesian reconstruction can be used to effectively recover higher resolution images. The overall performance is dependent on the image structure and the weight of the Bayesian prior.
NASA Astrophysics Data System (ADS)
Ortuño, J. E.; Kontaxakis, G.; Rubio, J. L.; Guerra, P.; Santos, A.
2010-04-01
A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.
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.
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.
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.
Toward real-time charged-particle image reconstruction using polar onion-peeling
NASA Astrophysics Data System (ADS)
Roberts, G. M.; Nixon, J. L.; Lecointre, J.; Wrede, E.; Verlet, J. R. R.
2009-05-01
A method to reconstruct full three-dimensional photofragment distributions from their two-dimensional (2D) projection onto a detection plane is presented, for processes in which the expanding Newton sphere has cylindrical symmetry around an axis parallel to the projection plane. The method is based on: (1) onion-peeling in polar coordinates [Zhao et al., Rev. Sci. Instrum. 73, 3044 (2002)] in which the contribution to the 2D projection from events outside the plane bisecting the Newton sphere are subtracted in polar coordinates at incrementally decreasing radii; and (2) ideas borrowed from the basis set expansion (pBASEX) method in polar coordinates [Garcia et al., Rev. Sci. Instrum. 75, 4989 (2004)], which we use to generate 2D projections at each incremental radius for the subtraction. Our method is as good as the pBASEX method in terms of accuracy, is devoid of centerline noise common to reconstruction methods employing Cartesian coordinates; and it is computationally cheap allowing images to be reconstructed as they are being acquired in a typical imaging experiment.
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.
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.
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.
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
2014-11-07
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.
PAINTER: a spatiospectral image reconstruction algorithm for optical interferometry.
Schutz, Antony; Ferrari, André; Mary, David; Soulez, Ferréol; Thiébaut, Éric; Vannier, Martin
2014-11-01
Astronomical optical interferometers sample the Fourier transform of the intensity distribution of a source at the observation wavelength. Because of rapid perturbations caused by atmospheric turbulence, the phases of the complex Fourier samples (visibilities) cannot be directly exploited. Consequently, specific image reconstruction methods have been devised in the last few decades. Modern polychromatic optical interferometric instruments are now paving the way to multiwavelength imaging. This paper is devoted to the derivation of a spatiospectral (3D) image reconstruction algorithm, coined Polychromatic opticAl INTErferometric Reconstruction software (PAINTER). The algorithm relies on an iterative process, which alternates estimation of polychromatic images and complex visibilities. The complex visibilities are not only estimated from squared moduli and closure phases, but also differential phases, which helps to better constrain the polychromatic reconstruction. Simulations on synthetic data illustrate the efficiency of the algorithm and, in particular, the relevance of injecting a differential phases model in the reconstruction.
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.
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.
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
Min, Junhong; Holden, Seamus J; Carlini, Lina; Unser, Michael; Manley, Suliana; Ye, Jong Chul
2014-11-01
Localization microscopy achieves nanoscale spatial resolution by iterative localization of sparsely activated molecules, which generally leads to a long acquisition time. By implementing advanced algorithms to treat overlapping point spread functions (PSFs), imaging of densely activated molecules can improve the limited temporal resolution, as has been well demonstrated in two-dimensional imaging. However, three-dimensional (3D) localization of high-density data remains challenging since PSFs are far more similar along the axial dimension than the lateral dimensions. Here, we present a new, high-density 3D imaging system and algorithm. The hybrid system is implemented by combining astigmatic and biplane imaging. The proposed 3D reconstruction algorithm is extended from our state-of-the art 2D high-density localization algorithm. Using mutual coherence analysis of model PSFs, we validated that the hybrid system is more suitable than astigmatic or biplane imaging alone for 3D localization of high-density data. The efficacy of the proposed method was confirmed via simulation and real data of microtubules. Furthermore, we also successfully demonstrated fluorescent-protein-based live cell 3D localization microscopy with a temporal resolution of just 3 seconds, capturing fast dynamics of the endoplasmic recticulum.
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.
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.
A GUI visualization system for airborne lidar image data to reconstruct 3D city model
NASA Astrophysics Data System (ADS)
Kawata, Yoshiyuki; Koizumi, Kohei
2015-10-01
A visualization toolbox system with graphical user interfaces (GUIs) was developed for the analysis of LiDAR point cloud data, as a compound object oriented widget application in IDL (Interractive Data Language). The main features in our system include file input and output abilities, data conversion capability from ascii formatted LiDAR point cloud data to LiDAR image data whose pixel value corresponds the altitude measured by LiDAR, visualization of 2D/3D images in various processing steps and automatic reconstruction ability of 3D city model. The performance and advantages of our graphical user interface (GUI) visualization system for LiDAR data are demonstrated.
Characterization of controlled bone defects using 2D and 3D ultrasound imaging techniques.
Parmar, Biren J; Longsine, Whitney; Sabonghy, Eric P; Han, Arum; Tasciotti, Ennio; Weiner, Bradley K; Ferrari, Mauro; Righetti, Raffaella
2010-08-21
Ultrasound is emerging as an attractive alternative modality to standard x-ray and CT methods for bone assessment applications. As of today, however, there is a lack of systematic studies that investigate the performance of diagnostic ultrasound techniques in bone imaging applications. This study aims at understanding the performance limitations of new ultrasound techniques for imaging bones in controlled experiments in vitro. Experiments are performed on samples of mammalian and non-mammalian bones with controlled defects with size ranging from 400 microm to 5 mm. Ultrasound findings are statistically compared with those obtained from the same samples using standard x-ray imaging modalities and optical microscopy. The results of this study demonstrate that it is feasible to use diagnostic ultrasound imaging techniques to assess sub-millimeter bone defects in real time and with high accuracy and precision. These results also demonstrate that ultrasound imaging techniques perform comparably better than x-ray imaging and optical imaging methods, in the assessment of a wide range of controlled defects both in mammalian and non-mammalian bones. In the future, ultrasound imaging techniques might provide a cost-effective, real-time, safe and portable diagnostic tool for bone imaging applications.
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.
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
Robust image reconstruction enhancement based on Gaussian mixture model estimation
NASA Astrophysics Data System (ADS)
Zhao, Fan; Zhao, Jian; Han, Xizhen; Wang, He; Liu, Bochao
2016-03-01
The low quality of an image is often characterized by low contrast and blurred edge details. Gradients have a direct relationship with image edge details. More specifically, the larger the gradients, the clearer the image details become. Robust image reconstruction enhancement based on Gaussian mixture model estimation is proposed here. First, image is transformed to its gradient domain, obtaining the gradient histogram. Second, the gradient histogram is estimated and extended using a Gaussian mixture model, and the predetermined function is constructed. Then, using histogram specification technology, the gradient field is enhanced with the constraint of the predetermined function. Finally, a matrix sine transform-based method is applied to reconstruct the enhanced image from the enhanced gradient field. Experimental results show that the proposed algorithm can effectively enhance different types of images such as medical image, aerial image, and visible image, providing high-quality image information for high-level processing.
Basis Functions in Image Reconstruction From Projections: A Tutorial Introduction
NASA Astrophysics Data System (ADS)
Herman, Gabor T.
2015-11-01
The series expansion approaches to image reconstruction from projections assume that the object to be reconstructed can be represented as a linear combination of fixed basis functions and the task of the reconstruction algorithm is to estimate the coefficients in such a linear combination based on the measured projection data. It is demonstrated that using spherically symmetric basis functions (blobs), instead of ones based on the more traditional pixels, yields superior reconstructions of medically relevant objects. The demonstration uses simulated computerized tomography projection data of head cross-sections and the series expansion method ART for the reconstruction. In addition to showing the results of one anecdotal example, the relative efficacy of using pixel and blob basis functions in image reconstruction from projections is also evaluated using a statistical hypothesis testing based task oriented comparison methodology. The superiority of the efficacy of blob basis functions over that of pixel basis function is found to be statistically significant.
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
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
Artificial neural network Radon inversion for image reconstruction.
Rodriguez, A F; Blass, W E; Missimer, J H; Leenders, K L
2001-04-01
Image reconstruction techniques are essential to computer tomography. Algorithms such as filtered backprojection (FBP) or algebraic techniques are most frequently used. This paper presents an attempt to apply a feed-forward back-propagation supervised artificial neural network (BPN) to tomographic image reconstruction, specifically to positron emission tomography (PET). The main result is that the network trained with Gaussian test images proved to be successful at reconstructing images from projection sets derived from arbitrary objects. Additional results relate to the design of the network and the full width at half maximum (FWHM) of the Gaussians in the training sets. First, the optimal number of nodes in the middle layer is about an order of magnitude less than the number of input or output nodes. Second, the number of iterations required to achieve a required training set tolerance appeared to decrease exponentially with the number of nodes in the middle layer. Finally, for training sets containing Gaussians of a single width, the optimal accuracy of reconstructing the control set is obtained with a FWHM of three pixels. Intended to explore feasibility, the BPN presented in the following does not provide reconstruction accuracy adequate for immediate application to PET. However, the trained network does reconstruct general images independent of the data with which it was trained. Proposed in the concluding section are several possible refinements that should permit the development of a network capable of fast reconstruction of three-dimensional images from the discrete, noisy projection data characteristic of PET.
Improving object detection in 2D images using a 3D world model
NASA Astrophysics Data System (ADS)
Viggh, Herbert E. M.; Cho, Peter L.; Armstrong-Crews, Nicholas; Nam, Myra; Shah, Danelle C.; Brown, Geoffrey E.
2014-05-01
A mobile robot operating in a netcentric environment can utilize offboard resources on the network to improve its local perception. One such offboard resource is a world model built and maintained by other sensor systems. In this paper we present results from research into improving the performance of Deformable Parts Model object detection algorithms by using an offboard 3D world model. Experiments were run for detecting both people and cars in 2D photographs taken in an urban environment. After generating candidate object detections, a 3D world model built from airborne Light Detection and Ranging (LIDAR) and aerial photographs was used to filter out false alarm using several types of geometric reasoning. Comparison of the baseline detection performance to the performance after false alarm filtering showed a significant decrease in false alarms for a given probability of detection.
MREJ: MRE elasticity reconstruction on ImageJ.
Xiang, Kui; Zhu, Xia Li; Wang, Chang Xin; Li, Bing Nan
2013-08-01
Magnetic resonance elastography (MRE) is a promising method for health evaluation and disease diagnosis. It makes use of elastic waves as a virtual probe to quantify soft tissue elasticity. The wave actuator, imaging modality and elasticity interpreter are all essential components for an MRE system. Efforts have been made to develop more effective actuating mechanisms, imaging protocols and reconstructing algorithms. However, translating MRE wave images into soft tissue elasticity is a nontrivial issue for health professionals. This study contributes an open-source platform - MREJ - for MRE image processing and elasticity reconstruction. It is established on the widespread image-processing program ImageJ. Two algorithms for elasticity reconstruction were implemented with spatiotemporal directional filtering. The usability of the method is shown through virtual palpation on different phantoms and patients. Based on the results, we conclude that MREJ offers the MRE community a convenient and well-functioning program for image processing and elasticity interpretation.
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.
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.
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.
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
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
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.
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)
Zagorchev, Lyubomir; Manzke, Robert; Cury, Ricardo; Reddy, Vivek Y.; Chan, Raymond C.
2007-03-01
Interventional cardiac electrophysiology (EP) procedures are typically performed under X-ray fluoroscopy for visualizing catheters and EP devices relative to other highly-attenuating structures such as the thoracic spine and ribs. These projections do not however contain information about soft-tissue anatomy and there is a recognized need for fusion of conventional fluoroscopy with pre-operatively acquired cardiac multislice computed tomography (MSCT) volumes. Rapid 2D-3D integration in this application would allow for real-time visualization of all catheters present within the thorax in relation to the cardiovascular anatomy visible in MSCT. We present a method for rapid fusion of 2D X-ray fluoroscopy with 3DMSCT that can facilitate EP mapping and interventional procedures by reducing the need for intra-operative contrast injections to visualize heart chambers and specialized systems to track catheters within the cardiovascular anatomy. We use hardware-accelerated ray-casting to compute digitally reconstructed radiographs (DRRs) from the MSCT volume and iteratively optimize the rigid-body pose of the volumetric data to maximize the similarity between the MSCT-derived DRR and the intra-operative X-ray projection data.
Improved Diffusion Imaging through SNR-Enhancing Joint Reconstruction
Haldar, Justin P.; Wedeen, Van J.; Nezamzadeh, Marzieh; Dai, Guangping; Weiner, Michael W.; Schuff, Norbert; Liang, Zhi-Pei
2012-01-01
Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio (SNR) represent significant hurdles for many in vivo applications. This paper presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstruction method that takes advantage of the high level of structural correlation observed in typical datasets. Compared to existing denoising methods, the proposed method performs reconstruction directly from the measured complex k-space data, allowing for Gaussian noise modeling and theoretical characterizations of the resolution and SNR of the reconstructed images. In addition, the proposed method is compatible with many different models of the diffusion signal (e.g., diffusion tensor modeling, q-space modeling, etc.). The joint reconstruction method can provide significant improvements in SNR relative to conventional reconstruction techniques, with a relatively minor corresponding loss in image resolution. Results are shown in the context of diffusion spectrum imaging tractography and diffusion tensor imaging, illustrating the potential of this SNR-enhancing joint reconstruction approach for a range of different diffusion imaging experiments. PMID:22392528
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.
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.
Hamid Muhammed, Hamed; Azar, Jimmy C.
2014-01-01
A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system. PMID:24971088
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
Digital infrared thermal imaging following anterior cruciate ligament reconstruction.
Barker, Lauren E; Markowski, Alycia M; Henneman, Kimberly
2012-03-01
This case describes the selective use of digital infrared thermal imaging for a 48-year-old woman who was being treated by a physical therapist following left anterior cruciate ligament (ACL) reconstruction with a semitendinosus autograft. PMID:22383168
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
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.
Time-of-flight PET image reconstruction using origin ensembles.
Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven
2015-03-01
The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.
Advanced photoacoustic image reconstruction using the k-Wave toolbox
NASA Astrophysics Data System (ADS)
Treeby, B. E.; Jaros, J.; Cox, B. T.
2016-03-01
Reconstructing images from measured time domain signals is an essential step in tomography-mode photoacoustic imaging. However, in practice, there are many complicating factors that make it difficult to obtain high-resolution images. These include incomplete or undersampled data, filtering effects, acoustic and optical attenuation, and uncertainties in the material parameters. Here, the processing and image reconstruction steps routinely used by the Photoacoustic Imaging Group at University College London are discussed. These include correction for acoustic and optical attenuation, spatial resampling, material parameter selection, image reconstruction, and log compression. The effect of each of these steps is demonstrated using a representative in vivo dataset. All of the algorithms discussed form part of the open-source k-Wave toolbox (available from http://www.k-wave.org).
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.
One decade of imaging precipitation measurement by 2D-video-distrometer
NASA Astrophysics Data System (ADS)
Schönhuber, M.; Lammer, G.; Randeu, W. L.
2007-04-01
The 2D-Video-Distrometer (2DVD) is a ground-based point-monitoring precipitation gauge. From each particle reaching the measuring area front and side contours as well as fall velocity and precise time stamp are recorded. In 1991 the 2DVD development has been started to clarify discrepancies found when comparing weather radar data analyses with literature models. Then being manufactured in a small scale series the first 2DVD delivery took place in 1996, 10 years back from now. An overview on present 2DVD features is given, and it is presented how the instrument was continuously improved in the past ten years. Scientific merits of 2DVD measurements are explained, including drop size readings without upper limit, drop shape and orientation angle information, contours of solid and melting particles, and an independent measurement of particles' fall velocity also in mixed phase events. Plans for a next generation instrument are described, by enhanced user-friendliness the unique data type shall be opened to a wider user community.
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.
Application of mathematical modelling methods for acoustic images reconstruction
NASA Astrophysics Data System (ADS)
Bolotina, I.; Kazazaeva, A.; Kvasnikov, K.; Kazazaev, A.
2016-04-01
The article considers the reconstruction of images by Synthetic Aperture Focusing Technique (SAFT). The work compares additive and multiplicative methods for processing signals received from antenna array. We have proven that the multiplicative method gives a better resolution. The study includes the estimation of beam trajectories for antenna arrays using analytical and numerical methods. We have shown that the analytical estimation method allows decreasing the image reconstruction time in case of linear antenna array implementation.
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.
NASA Astrophysics Data System (ADS)
Křemen, Tomáš; Koska, Bronislav
2013-04-01
Total reconstruction of a historical object is a complicated process consisting of several partial steps. One of these steps is acquiring high-quality data for preparation of the project documentation. If these data are not available from the previous periods, it is necessary to proceed to a detailed measurement of the object and to create a required drawing documentation. New measurement of the object brings besides its costs also several advantages as complex content and form of drawings exactly according to the requirements together with their high accuracy. The paper describes measurement of the Baroque church by the laser scanning method extended by the terrestrial and air photogrammetry. It deals with processing the measured data and creating the final outputs, which is a 2D drawing documentation, orthophotos and a 3D model. Attention is focused on their problematic parts like interconnection of the measurement data acquired by various technologies, creation of orthophotos and creation of the detailed combined 3D model of the church exterior. Results of this work were used for preparation of the planned reconstruction of the object.
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
3D/2D model-to-image registration applied to TIPS surgery.
Jomier, Julien; Bullitt, Elizabeth; Van Horn, Mark; Pathak, Chetna; Aylward, Stephen R
2006-01-01
We have developed a novel model-to-image registration technique which aligns a 3-dimensional model of vasculature with two semiorthogonal fluoroscopic projections. Our vascular registration method is used to intra-operatively initialize the alignment of a catheter and a preoperative vascular model in the context of image-guided TIPS (Transjugular, Intrahepatic, Portosystemic Shunt formation) surgery. Registration optimization is driven by the intensity information from the projection pairs at sample points along the centerlines of the model. Our algorithm shows speed, accuracy and consistency given clinical data.
Fast Ion Induced Shearing of 2D Alfven Eigenmodes Measured by Electron Cyclotron Emission Imaging
Tobias, Ben; Classen, I.G.J.; Domier, C. W.; Heidbrink, W.; Luhmann, N.C.; Nazikian, Raffi; Park, H.K.; Spong, Donald A; Van Zeeland, Michael
2011-01-01
Two-dimensional images of electron temperature perturbations are obtained with electron cyclotron emission imaging (ECEI) on the DIII-D tokamak and compared to Alfven eigenmode structures obtained by numerical modeling using both ideal MHD and hybrid MHD-gyrofluid codes. While many features of the observations are found to be in excellent agreement with simulations using an ideal MHD code (NOVA), other characteristics distinctly reveal the influence of fast ions on the mode structures. These features are found to be well described by the nonperturbative hybrid MHD-gyrofluid model TAEFL.
Super-Resolution Image Reconstruction Applied to Medical Ultrasound
NASA Astrophysics Data System (ADS)
Ellis, Michael
Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in
Reconstruction of images from radiofrequency electron paramagnetic resonance spectra.
Smith, C M; Stevens, A D
1994-12-01
This paper discusses methods for obtaining image reconstructions from electron paramagnetic resonance (EPR) spectra which constitute object projections. An automatic baselining technique is described which treats each spectrum consistently; rotating the non-horizontal baselines which are caused by stray magnetic effects onto the horizontal axis. The convolved backprojection method is described for both two- and three-dimensional reconstruction and the effect of cut-off frequency on the reconstruction is illustrated. A slower, indirect, iterative method, which does a non-linear fit to the projection data, is shown to give a far smoother reconstructed image when the method of maximum entropy is used to determine the value of the final residual sum of squares. Although this requires more computing time than the convolved backprojection method, it is more flexible and overcomes the problem of numerical instability encountered in deconvolution. Images from phantom samples in vitro are discussed. The spectral data for these have been accumulated quickly and have a low signal-to-noise ratio. The results show that as few as 16 spectra can still be processed to give an image. Artifacts in the image due to a small number of projections using the convolved backprojection reconstruction method can be removed by applying a threshold, i.e. only plotting contours higher than a given value. These artifacts are not present in an image which has been reconstructed by the maximum entropy technique. At present these techniques are being applied directly to in vivo studies.
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.
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
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.
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.
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.
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.
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.
Recent Advances In 2D-Band Structure Imaging By k-PEEM and Prospects For Technological Materials
NASA Astrophysics Data System (ADS)
Mathieu, C.; Renault, O.; Rotella, H.; Barrett, N.; Chabli, A.
2011-11-01
The imaging of surfaces using the PhotoElectron Emission Microscopy (PEEM) technique has recently received considerable interest, mainly thanks to the use of high brilliance synchrotron radiation which facilitates the study of surface properties and chemical selectivity. By inserting a transfer lens in the optical column of a high transmission and full energy-filtering PEEM, it is possible to image the back focal plane, named k-PEEM imaging mode. Hence, the corresponding image shows the angular distribution of the emitted photoelectrons for a given kinetic energy. By varying the kinetic energy, the complete energy filtering provides full 2D cuts of the band structure in reciprocal space. In this paper, we present the principles and the capabilities of this new imaging mode, and compare it to the standard ARPES technique. Then, we present results obtained on a model sample: Ag(100), and on a technological sample, epitaxial graphene on SiC(0001), highlighting the potential of this new imaging mode for the spatially resolved characterization of the electronic structure of monocrystalline materials in devices.
Application of image processing technology to 2-D signal processing (Abstract Only)
NASA Astrophysics Data System (ADS)
Meckley, John R.
1991-04-01
The analytical and processing developments in the field of Image Understanding over the last 15 years have led to the creation of a set of processing tools for the detection, characterization (feature extraction), and classification of 2 dimensional signals. This set of tools is applicable to 2 dimensional signals other than the traditional "image" type signals. In particular, for passive sonar detection processing several 2 dimensional signal transforms are generated from the 1 dimensional sensor time series data. These transforms are selected in order to concentrate signal energy locally within the 2 dimensional transform. A classic example is the Lofargram which is a grequency versus time transform of the time series data. If the acoutic source is emitting tones (for example from machinery) then the Lofargram will contain line like structures.
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.
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.
Image oscillation reduction and convergence acceleration for OSEM reconstruction
Huang, S.C.
1999-06-01
The authors have investigated the use of two approaches to reduce the image oscillation of OSEM reconstruction that is due to the inconsistencies among different partial subsets of the projection measurements (sinogram) when considering as a group. One approach pre-processes the sinogram to make it satisfy a sinogram consistency condition. The second approach takes the average of the intermediary images (i.e., smoothes image values over sub-iterations). Both approaches were found to be capable of reducing the image oscillation, and combination of both was most effective. With these approaches, the convergence of OSEM reconstruction is further improved. For computer simulated data and real PET data, a single iteration of these new OSEM reconstruction was shown to yield images comparable to those with 80 EM iterations.
NASA Astrophysics Data System (ADS)
Ambrico, Paolo F.; Ambrico, Marianna; Schiavulli, Luigi; De Benedictis, Santolo
2014-07-01
The charge trapping effect due to the exposure of alumina surfaces to plasma has been studied in a volume dielectric barrier discharge (DBD) in Ar and He noble gases. The long lasting charge trapping of alumina dielectric plates, used as barriers in DBDs, is evidenced by an ex situ thermoluminescence (TL) experiment performed with a standard and a custom two-dimensional (2D)-TL apparatus. The spatial density of trapped surface charges is found to be strongly correlated to the plasma morphology, and the surface spatial memory lasted for several minutes to hours after plasma exposure. In the case of Ar, the plasma channel impact signature on the surface shows a higher equivalent radiation dose with respect to the surface plasma wave and the post-discharge species signature. As a consequence, for the development of discharges, inside the dielectric surface the availability of lower energy trapped electrons is larger in the first region of plasma impact. The reported spatial memory increases the likelihood of the occurrence of plasma filaments in the same position in different runs. In He plasmas, the dielectric barrier shows an almost uniform distribution of trapped charges, meaning that there is no preferred region for the development of the discharge. In all cases a slight asymmetry was shown in the direction of the gas flow. This can be interpreted as being due to the long-living species moving in the direction of the gas flow, corresponding with the TL side experiment on the sample exposed to the plasma afterglow. The maximum values and the integral of the 2D-TL images showed a linear relation with the total charge per ac cycle, corresponding with findings for the TL glow curve. In conclusion, 2D-TL images allow the retrieval of information regarding the plasma surface interaction such as the plasma morphology, trap sites and their activation temperature.
2D and 3D GPR imaging of structural ceilings in historic and existing constructions
NASA Astrophysics Data System (ADS)
Colla, Camilla
2014-05-01
GPR applications in civil engineering are to date quite diversified. With respect to civil constructions and monumental buildings, detection of voids, cavities, layering in structural elements, variation of geometry, of moisture content, of materials, areas of decay, defects, cracks have been reported in timber, concrete and masonry elements. Nonetheless, many more fields of investigation remain unexplored. This contribution gives an account of a variety of examples of structural ceilings investigation by GPR radar in reflection mode, either as 2D or 3D data acquisition and visualisation. Ceilings have a pre-eminent role in buildings as they contribute to a good structural behaviour of the construction. Primarily, the following functions can be listed for ceilings: a) they carry vertical dead and live loads on floors and distribute such loads to the vertical walls; b) they oppose to external horizontal forces such as wind loads and earthquakes helping to transfer such forces from the loaded element to the other walls; c) they contribute to create the box skeleton and behaviour of a building, connecting the different load bearing walls and reducing the slenderness and flexural instability of such walls. Therefore, knowing how ceilings are made in specific buildings is of paramount importance for architects and structural engineers. According to the type of building and age of construction, ceilings may present very different solutions and materials. Moreover, in existing constructions, ceilings may have been substituted, modified or strengthened due to material decay or to change of use of the building. These alterations may often go unrecorded in technical documentation or technical drawings may be unavailable. In many cases, the position, orientation and number of the load carrying elements in ceilings may be hidden or not be in sight, due for example to the presence of false ceilings or to technical plants. GPR radar can constitute a very useful tool for
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.
Geoaccurate three-dimensional reconstruction via image-based geometry
NASA Astrophysics Data System (ADS)
Walvoord, Derek J.; Rossi, Adam J.; Paul, Bradley D.; Brower, Bernie; Pellechia, Matthew F.
2013-05-01
Recent technological advances in computing capabilities and persistent surveillance systems have led to increased focus on new methods of exploiting geospatial data, bridging traditional photogrammetric techniques and state-of-the-art multiple view geometry methodology. The structure from motion (SfM) problem in Computer Vision addresses scene reconstruction from uncalibrated cameras, and several methods exist to remove the inherent projective ambiguity. However, the reconstruction remains in an arbitrary world coordinate frame without knowledge of its relationship to a xed earth-based coordinate system. This work presents a novel approach for obtaining geoaccurate image-based 3-dimensional reconstructions in the absence of ground control points by using a SfM framework and the full physical sensor model of the collection system. Absolute position and orientation information provided by the imaging platform can be used to reconstruct the scene in a xed world coordinate system. Rather than triangulating pixels from multiple image-to-ground functions, each with its own random error, the relative reconstruction is computed via image-based geometry, i.e., geometry derived from image feature correspondences. In other words, the geolocation accuracy is improved using the relative distances provided by the SfM reconstruction. Results from the Exelis Wide-Area Motion Imagery (WAMI) system are provided to discuss conclusions and areas for future work.
Tracey, John; Miyazawa, Keisuke; Spijker, Peter; Miyata, Kazuki; Reischl, Bernhard; Canova, Filippo Federici; Rohl, Andrew L; Fukuma, Takeshi; Foster, Adam S
2016-10-14
Frequency modulation atomic force microscopy (FM-AFM) experiments were performed on the calcite (10[Formula: see text]4) surface in pure water, and a detailed analysis was made of the 2D images at a variety of frequency setpoints. We observed eight different contrast patterns that reproducibly appeared in different experiments and with different measurement parameters. We then performed systematic free energy calculations of the same system using atomistic molecular dynamics to obtain an effective force field for the tip-surface interaction. By using this force field in a virtual AFM simulation we found that each experimental contrast could be reproduced in our simulations by changing the setpoint, regardless of the experimental parameters. This approach offers a generic method for understanding the wide variety of contrast patterns seen on the calcite surface in water, and is generally applicable to AFM imaging in liquids.
NASA Astrophysics Data System (ADS)
Tracey, John; Miyazawa, Keisuke; Spijker, Peter; Miyata, Kazuki; Reischl, Bernhard; Federici Canova, Filippo; Rohl, Andrew L.; Fukuma, Takeshi; Foster, Adam S.
2016-10-01
Frequency modulation atomic force microscopy (FM-AFM) experiments were performed on the calcite (10\\bar{1}4) surface in pure water, and a detailed analysis was made of the 2D images at a variety of frequency setpoints. We observed eight different contrast patterns that reproducibly appeared in different experiments and with different measurement parameters. We then performed systematic free energy calculations of the same system using atomistic molecular dynamics to obtain an effective force field for the tip-surface interaction. By using this force field in a virtual AFM simulation we found that each experimental contrast could be reproduced in our simulations by changing the setpoint, regardless of the experimental parameters. This approach offers a generic method for understanding the wide variety of contrast patterns seen on the calcite surface in water, and is generally applicable to AFM imaging in liquids.
Tracey, John; Miyazawa, Keisuke; Spijker, Peter; Miyata, Kazuki; Reischl, Bernhard; Canova, Filippo Federici; Rohl, Andrew L; Fukuma, Takeshi; Foster, Adam S
2016-10-14
Frequency modulation atomic force microscopy (FM-AFM) experiments were performed on the calcite (10[Formula: see text]4) surface in pure water, and a detailed analysis was made of the 2D images at a variety of frequency setpoints. We observed eight different contrast patterns that reproducibly appeared in different experiments and with different measurement parameters. We then performed systematic free energy calculations of the same system using atomistic molecular dynamics to obtain an effective force field for the tip-surface interaction. By using this force field in a virtual AFM simulation we found that each experimental contrast could be reproduced in our simulations by changing the setpoint, regardless of the experimental parameters. This approach offers a generic method for understanding the wide variety of contrast patterns seen on the calcite surface in water, and is generally applicable to AFM imaging in liquids. PMID:27609045
NASA Astrophysics Data System (ADS)
Pan, Bing; Yu, Liping; Wu, Dafang
2014-02-01
The ideal pinhole imaging model commonly assumed for an ordinary two-dimensional digital image correlation (2D-DIC) system is neither perfect nor stable because of the existence of small out-of-plane motion of the test sample surface that occurred after loading, small out-of-plane motion of the sensor target due to temperature variation of a camera and unavoidable geometric distortion of an imaging lens. In certain cases, these disadvantages can lead to significant errors in the measured displacements and strains. Although a high-quality bilateral telecentric lens has been strongly recommended to be used in the 2D-DIC system as an essential optical component to achieve high-accuracy measurement, it is not generally applicable due to its fixed field of view, limited depth of focus and high cost. To minimize the errors associated with the imperfectness and instability of a common 2D-DIC system using a low-cost imaging lens, a generalized compensation method using a non-deformable reference sample is proposed in this work. With the proposed method, the displacement of the reference sample rigidly attached behind the test sample is first measured using 2D-DIC, and then it is fitted using a parametric model. The fitted parametric model is then used to correct the displacements of the deformed sample to remove the influences of these unfavorable factors. The validity of the proposed compensation method is first verified using out-of-plane translation, out-of-plane rotation, in-plane translation tests and their combinations. Uniaxial tensile tests of an aluminum specimen were also performed to quantitatively examine the strain accuracy of the proposed compensation method. Experiments show that the proposed compensation method is an easy-to-implement yet effective technique for achieving high-accuracy deformation measurement using an ordinary 2D-DIC system.
Sparsity-constrained three-dimensional image reconstruction for C-arm angiography.
Rashed, Essam A; al-Shatouri, Mohammad; Kudo, Hiroyuki
2015-07-01
X-ray C-arm is an important imaging tool in interventional radiology, road-mapping and radiation therapy because it provides accurate descriptions of vascular anatomy and therapeutic end point. In common interventional radiology, the C-arm scanner produces a set of two-dimensional (2D) X-ray projection data obtained with a detector by rotating the scanner gantry around the patient. Unlike conventional fluoroscopic imaging, three-dimensional (3D) C-arm computed tomography (CT) provides more accurate cross-sectional images, which are helpful for therapy planning, guidance and evaluation in interventional radiology. However, 3D vascular imaging using the conventional C-arm fluoroscopy encounters some geometry challenges. Inspired by the theory of compressed sensing, we developed an image reconstruction algorithm for conventional angiography C-arm scanners. The main challenge in this image reconstruction problem is the projection data limitations. We consider a small number of views acquired from a short rotation orbit with offset scan geometry. The proposed method, called sparsity-constrained angiography (SCAN), is developed using the alternating direction method of multipliers, and the results obtained from simulated and real data are encouraging. SCAN algorithm provides a framework to generate 3D vascular images using the conventional C-arm scanners in lower cost than conventional 3D imaging scanners.
Niu, Lili; Qian, Ming; Yan, Liang; Yu, Wentao; Jiang, Bo; Jin, Qiaofeng; Wang, Yanping; Shandas, Robin; Liu, Xin; Zheng, Hairong
2011-08-01
Many recent studies on ultrasonic particle image velocimetry (Echo PIV) showed that the accuracy of two-dimensional (2-D) flow velocity measured depends largely on the concentration of ultrasound contrast agents (UCAs) during imaging. This article presents a texture-based method for identifying the optimum microbubble concentration for Echo PIV measurements in real-time. The texture features, standard deviation of gray level, and contrast, energy and homogeneity of gray level co-occurrence matrix were extracted from ultrasound contrast images of rotational and pulsatile flow (10 MHz) in vitro and in vivo mouse common carotid arterial flow (40 MHz) with UCAs at various concentrations. The results showed that, at concentration of 0.8∼2 × 10³ bubbles/mL in vitro and 1∼5 × 10⁵ bubbles/mL in vivo, image texture features had a peak value or trough value, and velocity vectors with high accuracy can be obtained. Otherwise, poor quality velocity vectors were obtained. When the texture features were used as a feature set, the accuracy of K-nearest neighbor classifier can reach 86.4% in vitro and 87.5% in vivo, respectively. The texture-based method is shown to be able to quickly identify the optimum microbubble concentration and improve the accuracy for Echo PIV imaging.
Serial grouping of 2D-image regions with object-based attention in humans
Jeurissen, Danique; Self, Matthew W; Roelfsema, Pieter R
2016-01-01
After an initial stage of local analysis within the retina and early visual pathways, the human visual system creates a structured representation of the visual scene by co-selecting image elements that are part of behaviorally relevant objects. The mechanisms underlying this perceptual organization process are only partially understood. We here investigate the time-course of perceptual grouping of two-dimensional image-regions by measuring the reaction times of human participants and report that it is associated with the gradual spread of object-based attention. Attention spreads fastest over large and homogeneous areas and is slowed down at locations that require small-scale processing. We find that the time-course of the object-based selection process is well explained by a 'growth-cone' model, which selects surface elements in an incremental, scale-dependent manner. We discuss how the visual cortical hierarchy can implement this scale-dependent spread of object-based attention, leveraging the different receptive field sizes in distinct cortical areas. DOI: http://dx.doi.org/10.7554/eLife.14320.001 PMID:27291188
A Gaseous Compton Camera using a 2D-sensitive gaseous photomultiplier for Nuclear Medical Imaging
NASA Astrophysics Data System (ADS)
Azevedo, C. D. R.; Pereira, F. A.; Lopes, T.; Correia, P. M. M.; Silva, A. L. M.; Carramate, L. F. N. D.; Covita, D. S.; Veloso, J. F. C. A.
2013-12-01
A new Compton Camera (CC) concept based on a High Pressure Scintillation Chamber coupled to a position-sensitive Gaseous PhotoMultiplier for Nuclear Medical Imaging applications is proposed. The main goal of this work is to describe the development of a ϕ25×12 cm3 cylindrical prototype, which will be suitable for scintimammography and for small-animal imaging applications. The possibility to scale it to an useful human size device is also in study. The idea is to develop a device capable to compete with the standard Anger Camera. Despite the large success of the Anger Camera, it still presents some limitations, such as: low position resolution and fair energy resolutions for 140 keV. The CC arises a different solution as it provides information about the incoming photon direction, avoiding the use of a collimator, which is responsible for a huge reduction (10-4) of the sensitivity. The main problem of the CC's is related with the Doppler Broadening which is responsible for the loss of angular resolution. In this work, calculations for the Doppler Broadening in Xe, Ar, Ne and their mixtures are presented. Simulations of the detector performance together with discussion about the gas choice are also included .
Tangential 2-D Edge Imaging for GPI and Edge/Impurity Modeling
Dr. Ricardo Maqueda; Dr. Fred M. Levinton
2011-12-23
Nova Photonics, Inc. has a collaborative effort at the National Spherical Torus Experiment (NSTX). This collaboration, based on fast imaging of visible phenomena, has provided key insights on edge turbulence, intermittency, and edge phenomena such as edge localized modes (ELMs) and multi-faceted axisymmetric radiation from the edge (MARFE). Studies have been performed in all these areas. The edge turbulence/intermittency studies make use of the Gas Puff Imaging diagnostic developed by the Principal Investigator (Ricardo Maqueda) together with colleagues from PPPL. This effort is part of the International Tokamak Physics Activity (ITPA) edge, scrape-off layer and divertor group joint activity (DSOL-15: Inter-machine comparison of blob characteristics). The edge turbulence/blob study has been extended from the current location near the midplane of the device to the lower divertor region of NSTX. The goal of this effort was to study turbulence born blobs in the vicinity of the X-point region and their circuit closure on divertor sheaths or high density regions in the divertor. In the area of ELMs and MARFEs we have studied and characterized the mode structure and evolution of the ELM types observed in NSTX, as well as the study of the observed interaction between MARFEs and ELMs. This interaction could have substantial implications for future devices where radiative divertor regions are required to maintain detachment from the divertor plasma facing components.
SIMS of organics—Advances in 2D and 3D imaging and future outlook
Gilmore, Ian S.
2013-09-15
Secondary ion mass spectrometry (SIMS) has become a powerful technique for the label-free analysis of organics from cells to electronic devices. The development of cluster ion sources has revolutionized the field, increasing the sensitivity for organics by two or three orders of magnitude and for large clusters, such as C{sub 60} and argon clusters, allowing depth profiling of organics. The latter has provided the capability to generate stunning three dimensional images with depth resolutions of around 5 nm, simply unavailable by other techniques. Current state-of-the-art allows molecular images with a spatial resolution of around 500 nm to be achieved and future developments are likely to progress into the sub-100 nm regime. This review is intended to bring those with some familiarity with SIMS up-to-date with the latest developments for organics, the fundamental principles that underpin this and define the future progress. State-of-the-art examples are showcased and signposts to more in-depth reviews about specific topics given for the specialist.
NASA Astrophysics Data System (ADS)
Hawks, Michael R.; Jennings, Alan; Tervo, Ryan
2015-05-01
Chromotomography is a form of hyperspectral imaging that uses a prism to simultaneously record spectral and spatial information, like a slitless spectrometer. The prism is rotated to provide multiple projections of the 3D data cube on the 2D detector array. Tomographic reconstruction methods are then used to estimate the hyperspectral data cube from the projections. This type of system can collect hyperspectral imagery from fast transient events, but suffers from reconstruction artifacts due to the limited-angle problem. Several algorithms have been proposed in the literature to improve reconstruction, including filtered backprojection, projection onto convex sets, subspace constraint, and split- Bregman iteration. Here we present the first direct comparison of multiple methods against a variety of simulatedtargets. Results are compared based on both image quality and spectral accuracy of the reconstruction, where previous literature has emphasized imaging only. In addition, new algorithms and HSI quality metrics are proposed. We find the quality of the results depend strongly on the spatial and spectral content of the scene, and no single algorithm is consistently superior over a broad range of scenes.
Intensifying the response of distributed optical fibre sensors using 2D and 3D image restoration
Soto, Marcelo A.; Ramírez, Jaime A.; Thévenaz, Luc
2016-01-01
Distributed optical fibre sensors possess the unique capability of measuring the spatial and temporal map of environmental quantities that can be of great interest for several field applications. Although existing methods for performance enhancement have enabled important progresses in the field, they do not take full advantage of all information present in the measured data, still giving room for substantial improvement over the state-of-the-art. Here we propose and experimentally demonstrate an approach for performance enhancement that exploits the high level of similitude and redundancy contained on the multidimensional information measured by distributed fibre sensors. Exploiting conventional image and video processing, an unprecedented boost in signal-to-noise ratio and measurement contrast is experimentally demonstrated. The method can be applied to any white-noise-limited distributed fibre sensor and can remarkably provide a 100-fold improvement in the sensor performance with no hardware modification. PMID:26927698
Intensifying the response of distributed optical fibre sensors using 2D and 3D image restoration
NASA Astrophysics Data System (ADS)
Soto, Marcelo A.; Ramírez, Jaime A.; Thévenaz, Luc
2016-03-01
Distributed optical fibre sensors possess the unique capability of measuring the spatial and temporal map of environmental quantities that can be of great interest for several field applications. Although existing methods for performance enhancement have enabled important progresses in the field, they do not take full advantage of all information present in the measured data, still giving room for substantial improvement over the state-of-the-art. Here we propose and experimentally demonstrate an approach for performance enhancement that exploits the high level of similitude and redundancy contained on the multidimensional information measured by distributed fibre sensors. Exploiting conventional image and video processing, an unprecedented boost in signal-to-noise ratio and measurement contrast is experimentally demonstrated. The method can be applied to any white-noise-limited distributed fibre sensor and can remarkably provide a 100-fold improvement in the sensor performance with no hardware modification.
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.
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 Dictionary-Based Reconstruction for Diffusion Spectrum Imaging
Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar
2015-01-01
Diffusion Spectrum Imaging (DSI) 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 (TV) 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
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.
Fair-view image reconstruction with dual dictionaries.
Lu, Yang; Zhao, Jun; Wang, Ge
2012-01-01
In this paper, we formulate the problem of computed tomography (CT)under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively.Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV.
Few-view image reconstruction with dual dictionaries
Lu, Yang; Zhao, Jun; Wang, Ge
2011-01-01
In this paper, we formulate the problem of computed tomography (CT) under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively. Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV. PMID:22155989
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.
Bayesian image reconstruction for improving detection performance of muon tomography.
Wang, Guobao; Schultz, Larry J; Qi, Jinyi
2009-05-01
Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.
Reconstruction of 3D ultrasound images based on Cyclic Regularized Savitzky-Golay filters.
Toonkum, Pollakrit; Suwanwela, Nijasri C; Chinrungrueng, Chedsada
2011-02-01
This paper presents a new three-dimensional (3D) ultrasound reconstruction algorithm for generation of 3D images from a series of two-dimensional (2D) B-scans acquired in the mechanical linear scanning framework. Unlike most existing 3D ultrasound reconstruction algorithms, which have been developed and evaluated in the freehand scanning framework, the new algorithm has been designed to capitalize the regularity pattern of the mechanical linear scanning, where all the B-scan slices are precisely parallel and evenly spaced. The new reconstruction algorithm, referred to as the Cyclic Regularized Savitzky-Golay (CRSG) filter, is a new variant of the Savitzky-Golay (SG) smoothing filter. The CRSG filter has been improved upon the original SG filter in two respects: First, the cyclic indicator function has been incorporated into the least square cost function to enable the CRSG filter to approximate nonuniformly spaced data of the unobserved image intensities contained in unfilled voxels and reduce speckle noise of the observed image intensities contained in filled voxels. Second, the regularization function has been augmented to the least squares cost function as a mechanism to balance between the degree of speckle reduction and the degree of detail preservation. The CRSG filter has been evaluated and compared with the Voxel Nearest-Neighbor (VNN) interpolation post-processed by the Adaptive Speckle Reduction (ASR) filter, the VNN interpolation post-processed by the Adaptive Weighted Median (AWM) filter, the Distance-Weighted (DW) interpolation, and the Adaptive Distance-Weighted (ADW) interpolation, on reconstructing a synthetic 3D spherical image and a clinical 3D carotid artery bifurcation in the mechanical linear scanning framework. This preliminary evaluation indicates that the CRSG filter is more effective in both speckle reduction and geometric reconstruction of 3D ultrasound images than the other methods. PMID:20696448
Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja
2012-10-10
The feasibility of 2D-intensity and 3D-topography images from a non-invasive Chromatic White Light (CWL) sensor for the age determination of latent fingerprints is investigated. The proposed method might provide the means to solve the so far unresolved issue of determining a fingerprints age in forensics. Conducting numerous experiments for an indoor crime scene using selected surfaces, different influences on the aging of fingerprints are investigated and the resulting aging variability is determined in terms of inter-person, intra-person, inter-finger and intra-finger variation. Main influence factors are shown to be the sweat composition, temperature, humidity, wind, UV-radiation, surface type, contamination of the finger with water-containing substances, resolution and measured area size, whereas contact time, contact pressure and smearing of the print seem to be of minor importance. Such influences lead to a certain experimental variability in inter-person and intra-person variation, which is higher than the inter-finger and intra-finger variation. Comparing the aging behavior of 17 different features using 1490 time series with a total of 41,520 fingerprint images, the great potential of the CWL technique in combination with the binary pixel feature from prior work is shown. Performing three different experiments for the classification of fingerprints into the two time classes [0, 5 h] and [5, 24 h], a maximum classification performance of 79.29% (kappa=0.46) is achieved for a general case, which is further improved for special cases. The statistical significance of the two best-performing features (both binary pixel versions based on 2D-intensity images) is manually shown and a feature fusion is performed, highlighting the strong dependency of the features on each other. It is concluded that such method might be combined with additional capturing devices, such as microscopes or spectroscopes, to a very promising age estimation scheme. PMID:22658793
Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja
2012-10-10
The feasibility of 2D-intensity and 3D-topography images from a non-invasive Chromatic White Light (CWL) sensor for the age determination of latent fingerprints is investigated. The proposed method might provide the means to solve the so far unresolved issue of determining a fingerprints age in forensics. Conducting numerous experiments for an indoor crime scene using selected surfaces, different influences on the aging of fingerprints are investigated and the resulting aging variability is determined in terms of inter-person, intra-person, inter-finger and intra-finger variation. Main influence factors are shown to be the sweat composition, temperature, humidity, wind, UV-radiation, surface type, contamination of the finger with water-containing substances, resolution and measured area size, whereas contact time, contact pressure and smearing of the print seem to be of minor importance. Such influences lead to a certain experimental variability in inter-person and intra-person variation, which is higher than the inter-finger and intra-finger variation. Comparing the aging behavior of 17 different features using 1490 time series with a total of 41,520 fingerprint images, the great potential of the CWL technique in combination with the binary pixel feature from prior work is shown. Performing three different experiments for the classification of fingerprints into the two time classes [0, 5 h] and [5, 24 h], a maximum classification performance of 79.29% (kappa=0.46) is achieved for a general case, which is further improved for special cases. The statistical significance of the two best-performing features (both binary pixel versions based on 2D-intensity images) is manually shown and a feature fusion is performed, highlighting the strong dependency of the features on each other. It is concluded that such method might be combined with additional capturing devices, such as microscopes or spectroscopes, to a very promising age estimation scheme.
Scalar wave-optical reconstruction of plenoptic camera images.
Junker, André; Stenau, Tim; Brenner, Karl-Heinz
2014-09-01
We investigate the reconstruction of plenoptic camera images in a scalar wave-optical framework. Previous publications relating to this topic numerically simulate light propagation on the basis of ray tracing. However, due to continuing miniaturization of hardware components it can be assumed that in combination with low-aperture optical systems this technique may not be generally valid. Therefore, we study the differences between ray- and wave-optical object reconstructions of true plenoptic camera images. For this purpose we present a wave-optical reconstruction algorithm, which can be run on a regular computer. Our findings show that a wave-optical treatment is capable of increasing the detail resolution of reconstructed objects.
Tomographic mesh generation for OSEM reconstruction of SPECT images
NASA Astrophysics Data System (ADS)
Lu, Yao; Yu, Bo; Vogelsang, Levon; Krol, Andrzej; Xu, Yuesheng; Hu, Xiaofei; Feiglin, David
2009-02-01
To improve quality of OSEM SPECT reconstruction in the mesh domain, we implemented an adaptive mesh generation method that produces tomographic mesh consisting of triangular elements with size and density commensurate with geometric detail of the objects. Node density and element size change smoothly as a function of distance from the edges and edge curvature without creation of 'bad' elements. Tomographic performance of mesh-based OSEM reconstruction is controlled by the tomographic mesh structure, i.e. node density distribution, which in turn is ruled by the number of key points on the boundaries. A greedy algorithm is used to influence the distribution of nodes on the boundaries. The relationship between tomographic mesh properties and OSEM reconstruction quality has been investigated. We conclude that by selecting adequate number of key points, one can produce a tomographic mesh with lowest number of nodes that is sufficient to provide desired quality of reconstructed images, appropriate for the imaging system properties.
Prospective regularization design in prior-image-based reconstruction.
Dang, Hao; Siewerdsen, Jeffrey H; Stayman, J Webster
2015-12-21
Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in
Prospective regularization design in prior-image-based reconstruction
NASA Astrophysics Data System (ADS)
Dang, Hao; Siewerdsen, Jeffrey H.; Webster Stayman, J.
2015-12-01
Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in
Gabbour, Maya; Schnell, Susanne; Jarvis, Kelly; Robinson, Joshua D.; Markl, Michael
2015-01-01
Background Doppler echocardiography (echo) is the reference standard for blood flow velocity analysis, and two-dimensional (2-D) phase-contrast magnetic resonance imaging (MRI) is considered the reference standard for quantitative blood flow assessment. However, both clinical standard-of-care techniques are limited by 2-D acquisitions and single-direction velocity encoding and may make them inadequate to assess the complex three-dimensional hemodynamics seen in congenital heart disease. Four-dimensional flow MRI (4-D flow) enables qualitative and quantitative analysis of complex blood flow in the heart and great arteries. Objectives The objectives of this study are to compare 4-D flow with 2-D phase-contrast MRI for quantification of aortic and pulmonary flow and to evaluate the advantage of 4-D flow-based volumetric flow analysis compared to 2-D phase-contrast MRI and echo for peak velocity assessment in children and young adults. Materials and methods Two-dimensional phase-contrast MRI of the aortic root, main pulmonary artery (MPA), and right and left pulmonary arteries (RPA, LPA) and 4-D flow with volumetric coverage of the aorta and pulmonary arteries were performed in 50 patients (mean age: 13.1±6.4 years). Four-dimensional flow analyses included calculation of net flow and regurgitant fraction with 4-D flow analysis planes similarly positioned to 2-D planes. In addition, 4-D flow volumetric assessment of aortic root/ascending aorta and MPA peak velocities was performed and compared to 2-D phase-contrast MRI and echo. Results Excellent correlation and agreement were found between 2-D phase-contrast MRI and 4-D flow for net flow (r=0.97, P<0.001) and excellent correlation with good agreement was found for regurgitant fraction (r= 0.88, P<0.001) in all vessels. Two-dimensional phase-contrast MRI significantly underestimated aortic (P= 0.032) and MPA (P<0.001) peak velocities compared to echo, while volumetric 4-D flow analysis resulted in higher (aortic: P=0
Three-dimensional image reconstruction for electrical impedance tomography.
Kleinermann, F; Avis, N J; Judah, S K; Barber, D C
1996-11-01
Very little work has been conducted on three-dimensional aspects of electrical impedance tomography (EIT), partly due to the increased computational complexity over the two-dimensional aspects of EIT. Nevertheless, extending EIT to three-dimensional data acquisition and image reconstruction may afford significant advantages such as an increase in the size of the independent data set and improved spatial resolution. However, considerable challenges are associated with the software aspects of three-dimensional EIT systems due to the requirement for accurate three-dimensional forward problem modelling and the derivation of three-dimensional image reconstruction algorithms. This paper outlines the work performed to date to derive a three-dimensional image reconstruction algorithm for EIT based on the inversion of the sensitivity matrix approach for a finite right circular cylinder. A comparison in terms of the singular-value spectra and the singular vectors between the sensitivity matrices for a three-dimensional cylinder and a two-dimensional disc has been performed. This comparison shows that the three-dimensional image reconstruction algorithm recruits more central information at lower condition numbers than the two-dimensional image reconstruction algorithm.
Leong, Andrew F. T.; Islam, M. Sirajul; Kitchen, Marcus J.; Fouras, Andreas; Wallace, Megan J.; Hooper, Stuart B.
2013-04-15
Purpose: Described herein is a new technique for measuring regional lung air volumes from two-dimensional propagation-based phase contrast x-ray (PBI) images at very high spatial and temporal resolution. Phase contrast dramatically increases lung visibility and the outlined volumetric reconstruction technique quantifies dynamic changes in respiratory function. These methods can be used for assessing pulmonary disease and injury and for optimizing mechanical ventilation techniques for preterm infants using animal models. Methods: The volumetric reconstruction combines the algorithms of temporal subtraction and single image phase retrieval (SIPR) to isolate the image of the lungs from the thoracic cage in order to measure regional lung air volumes. The SIPR algorithm was used to recover the change in projected thickness of the lungs on a pixel-by-pixel basis (pixel dimensions {approx}16.2 {mu}m). The technique has been validated using numerical simulation and compared results of measuring regional lung air volumes with and without the use of temporal subtraction for removing the thoracic cage. To test this approach, a series of PBI images of newborn rabbit pups mechanically ventilated at different frequencies was employed. Results: Regional lung air volumes measured from PBI images of newborn rabbit pups showed on average an improvement of at least 20% in 16% of pixels within the lungs in comparison to that measured without the use of temporal subtraction. The majority of pixels that showed an improvement was found to be in regions occupied by bone. Applying the volumetric technique to sequences of PBI images of newborn rabbit pups, it is shown that lung aeration at birth can be highly heterogeneous. Conclusions: This paper presents an image segmentation technique based on temporal subtraction that has successfully been used to isolate the lungs from PBI chest images, allowing the change in lung air volume to be measured over regions as small as the pixel size. Using
MIA-QSAR: a simple 2D image-based approach for quantitative structure activity relationship analysis
NASA Astrophysics Data System (ADS)
Freitas, Matheus P.; Brown, Steven D.; Martins, José A.
2005-03-01
An accessible and quite simple QSAR method, based on 2D image analysis, is reported. A case study is carried out in order to compare this model with a previously reported sophisticated methodology. A well known set of ( S)- N-[(1-ethyl-2-pyrrolidinyl)methyl]-6-methoxybenzamides, compounds with affinity to the dopamine D 2 receptor subtype, was divided in 40 calibration compounds and 18 test compounds and the descriptors were generated from pixels of 2D structures of each compound, which can be drawn with aid of any appropriate program. Bilinear (conventional) PLS was utilized as the regression method and leave-one-out cross-validation was performed using the NIPALS algorithm. The good predicted Q2 value obtained for the series of test compounds (0.58), together with the similar prediction quality obtained to other data sets (nAChR ligands, HIV protease inhibitors, COX-2 inhibitors and anxiolytic agents), suggests that the model is robust and seems to be as applicable as more complex methods.
NASA Astrophysics Data System (ADS)
Pérez-Corona, M.; García, J. A.; Taller, G.; Polgár, D.; Bustos, E.; Plank, Z.
2016-02-01
The purpose of geophysical electrical surveys is to determine the subsurface resistivity distribution by making measurements on the ground surface. From these measurements, the true resistivity of the subsurface can be estimated. The ground resistivity is related to various geological parameters, such as the mineral and fluid content, porosity and degree of water saturation in the rock. Electrical resistivity surveys have been used for many decades in hydrogeological, mining and geotechnical investigations. More recently, they have been used for environmental surveys. To obtain a more accurate subsurface model than is possible with a simple 1-D model, a more complex model must be used. In a 2-D model, the resistivity values are allowed to vary in one horizontal direction (usually referred to as the x direction) but are assumed to be constant in the other horizontal (the y) direction. A more realistic model would be a fully 3-D model where the resistivity values are allowed to change in all three directions. In this research, a simulation of the cone penetration test and 2D imaging resistivity are used as tools to simulate the distribution of hydrocarbons in soil.
NASA Astrophysics Data System (ADS)
Kohn, S. A.; Aguirre, J. E.; Nunhokee, C. D.; Bernardi, G.; Pober, J. C.; Ali, Z. S.; Bradley, R. F.; Carilli, C. L.; DeBoer, D. R.; Gugliucci, N. E.; Jacobs, D. C.; Klima, P.; MacMahon, D. H. E.; Manley, J. R.; Moore, D. F.; Parsons, A. R.; Stefan, I. I.; Walbrugh, W. P.
2016-06-01
Current generation low-frequency interferometers constructed with the objective of detecting the high-redshift 21 cm background aim to generate power spectra of the brightness temperature contrast of neutral hydrogen in primordial intergalactic medium. Two-dimensional (2D) power spectra (power in Fourier modes parallel and perpendicular to the line of sight) that formed from interferometric visibilities have been shown to delineate a boundary between spectrally smooth foregrounds (known as the wedge) and spectrally structured 21 cm background emission (the EoR window). However, polarized foregrounds are known to possess spectral structure due to Faraday rotation, which can leak into the EoR window. In this work we create and analyze 2D power spectra from the PAPER-32 imaging array in Stokes I, Q, U, and V. These allow us to observe and diagnose systematic effects in our calibration at high signal-to-noise within the Fourier space most relevant to EoR experiments. We observe well-defined windows in the Stokes visibilities, with Stokes Q, U, and V power spectra sharing a similar wedge shape to that seen in Stokes I. With modest polarization calibration, we see no evidence that polarization calibration errors move power outside the wedge in any Stokes visibility to the noise levels attained. Deeper integrations will be required to confirm that this behavior persists to the depth required for EoR detection.
NASA Astrophysics Data System (ADS)
Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.
2015-08-01
The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.
Betancur, Julián; Simon, Antoine; Halbert, Edgar; Tavard, François; Carré, François; Hernández, Alfredo; Donal, Erwan; Schnell, Frédéric; Garreau, Mireille
2016-02-01
Describing and analyzing heart multiphysics requires the acquisition and fusion of multisensor cardiac images. Multisensor image fusion enables a combined analysis of these heterogeneous modalities. We propose to register intra-patient multiview 2D+t ultrasound (US) images with multiview late gadolinium-enhanced (LGE) images acquired during cardiac magnetic resonance imaging (MRI), in order to fuse mechanical and tissue state information. The proposed procedure registers both US and LGE to cine MRI. The correction of slice misalignment and the rigid registration of multiview LGE and cine MRI are studied, to select the most appropriate similarity measure. It showed that mutual information performs the best for LGE slice misalignment correction and for LGE and cine registration. Concerning US registration, dynamic endocardial contours resulting from speckle tracking echocardiography were exploited in a geometry-based dynamic registration. We propose the use of an adapted dynamic time warping procedure to synchronize cardiac dynamics in multiview US and cine MRI. The registration of US and LGE MRI was evaluated on a dataset of patients with hypertrophic cardiomyopathy. A visual assessment of 330 left ventricular regions from US images of 28 patients resulted in 92.7% of regions successfully aligned with cardiac structures in LGE. Successfully-aligned regions were then used to evaluate the abilities of strain indicators to predict the presence of fibrosis. Longitudinal peak-strain and peak-delay of aligned left ventricular regions were computed from corresponding regional strain curves from US. The Mann-Withney test proved that the expected values of these indicators change between the populations of regions with and without fibrosis (p < 0.01). ROC curves otherwise proved that the presence of fibrosis is one factor amongst others which modifies longitudinal peak-strain and peak-delay. PMID:26619189
An adaptive filtered back-projection for photoacoustic image reconstruction
Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong
2015-05-15
Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing
An adaptive filtered back-projection for photoacoustic image reconstruction
Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong
2015-01-01
Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing
Beyond maximum entropy: Fractal pixon-based image reconstruction
NASA Technical Reports Server (NTRS)
Puetter, R. 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 methods, including Goodness-of-Fit (e.g. Least-Squares and Lucy-Richardson) and Maximum Entropy (ME). 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.
Reconstruction of electrostatic force microscopy images
NASA Astrophysics Data System (ADS)
Strassburg, E.; Boag, A.; Rosenwaks, Y.
2005-08-01
An efficient algorithm to restore the actual surface potential image from Kelvin probe force microscopy measurements of semiconductors is presented. The three-dimensional potential of the tip-sample system is calculated using an integral equation-based boundary element method combined with modeling the semiconductor by an equivalent dipole-layer and image-charge model. The derived point spread function of the measuring tip is then used to restore the actual surface potential from the measured image, using noise filtration and deconvolution algorithms. The model is then used to restore high-resolution Kelvin probe microscopy images of semiconductor surfaces.
Muniraj, Inbarasan; Guo, Changliang; Lee, Byung-Geun; Sheridan, John T
2015-06-15
We present a method of securing multispectral 3D photon-counted integral imaging (PCII) using classical Hartley Transform (HT) based encryption by employing optical interferometry. This method has the simultaneous advantages of minimizing complexity by eliminating the need for holography recording and addresses the phase sensitivity problem encountered when using digital cameras. These together with single-channel multispectral 3D data compactness, the inherent properties of the classical photon counting detection model, i.e. sparse sensing and the capability for nonlinear transformation, permits better authentication of the retrieved 3D scene at various depth cues. Furthermore, the proposed technique works for both spatially and temporally incoherent illumination. To validate the proposed technique simulations were carried out for both the 2D and 3D cases. Experimental data is processed and the results support the feasibility of the encryption method. PMID:26193568
Gaitanis, Anastasios; Kontaxakis, George; Spyrou, George; Panayiotakis, George; Tzanakos, George
2010-09-01
We have studied the properties of the pixel updating coefficients in the 2D ordered subsets expectation maximization (OSEM) algorithm for iterative image reconstruction in positron emission tomography, in order to address the problem of image quality degradation-a known property of the technique after a number of iterations. The behavior of the updating coefficients has been extensively analyzed on synthetic coincidence data, using the necessary software tools. The experiments showed that the statistical properties of these coefficients can be correlated with the quality of the reconstructed images as a function of the activity distribution in the source and the number of subsets used. Considering the fact that these properties can be quantified during the reconstruction process of data from real scans where the activity distribution in the source is unknown the results of this study might be useful for the development of a stopping criterion for the OSEM algorithm.
NASA Astrophysics Data System (ADS)
Lebedev, Sergej; Sawall, Stefan; Kuchenbecker, Stefan; Faby, Sebastian; Knaup, Michael; Kachelrieß, Marc
2015-03-01
The reconstruction of CT images with low noise and highest spatial resolution is a challenging task. Usually, a trade-off between at least these two demands has to be found or several reconstructions with mutually exclusive properties, i.e. either low noise or high spatial resolution, have to be performed. Iterative reconstruction methods might be suitable tools to overcome these limitations and provide images of highest diagnostic quality with formerly mutually exclusive image properties. While image quality metrics like the modulation transfer function (MTF) or the point spread function (PSF) are well-defined in case of standard reconstructions, e.g. filtered backprojection, the iterative algorithms lack these metrics. To overcome this issue alternate methodologies like the model observers have been proposed recently to allow a quantification of a usually task-dependent image quality metric.1 As an alternative we recently proposed an iterative reconstruction method, the alpha-image reconstruction (AIR), providing well-defined image quality metrics on a per-voxel basis.2 In particular, the AIR algorithm seeks to find weighting images, the alpha-images, that are used to blend between basis images with mutually exclusive image properties. The result is an image with highest diagnostic quality that provides a high spatial resolution and a low noise level. As the estimation of the alpha-images is computationally demanding we herein aim at optimizing this process and highlight the favorable properties of AIR using patient measurements.
NASA Astrophysics Data System (ADS)
Fahrig, Rebecca; Fox, Allan J.; Holdsworth, David W.
1996-04-01
Treatment of subarachnoid aneurysms with endovascular techniques (e.g. placement of Guglielmi coils) is currently limited by the inability to visualize the neck of the aneurysm after the initial coils have been placed. Coils projecting into parent vessels may cause thrombosis, while incomplete filling leads to regrowth of the aneurysm. Since the procedure is performed using a gantry-mounted x-ray image intensifier (XRII), we have used this system to obtain 2- dimensional (2-D) images over approximately 200 degrees and reconstructed a 3-D image of the embolizing coil, residual aneurysm, and the parent vessel. The required data can be acquired, reconstructed and presented to the neuroradiologist during the interventional procedure. We have characterized an existing clinical C-arm radiographic system, and have developed correction procedures which provide a consistent and adequate data set for standard CT reconstruction using convolution-backprojection techniques. The angle of acquisition for each image is recorded using a hub-mounted angle encoder accurate to within plus or minus 0.3 degrees. We have characterized the XRII distortion over the rotation, and can correct images acquired at any known angle to within plus or minus 0.06 pixels. We have also measured the motion of the center of rotation (reproducible to within plus or minus 0.13 pixels) and correct for the displacement using an image shift and interpolation algorithm. Finally, we have investigated the effects on CT reconstruction of variable dilutions of contrast agent during the cardiac cycle, and have shown the contrast-to-noise ratio (CNR), in the absence of photon noise, to be 28. This is larger than the CNR which we achieve due to photon noise alone.
Wakeling, James M.
2014-01-01
When skeletal muscle fibres shorten, they must increase in their transverse dimensions in order to maintain a constant volume. In pennate muscle, this transverse expansion results in the fibres rotating to greater pennation angle, with a consequent reduction in their contractile velocity in a process known as gearing. Understanding the nature and extent of this transverse expansion is necessary to understand the mechanisms driving the changes in internal geometry of whole muscles during contraction. Current methodologies allow the fascicle lengths, orientations, and curvatures to be quantified, but not the transverse expansion. The purpose of this study was to develop and validate techniques for quantifying transverse strain in skeletal muscle fascicles during contraction from B-mode ultrasound images. Images were acquired from the medial and lateral gastrocnemii during cyclic contractions, enhanced using multiscale vessel enhancement filtering and the spatial frequencies resolved using 2D discrete Fourier transforms. The frequency information was resolved into the fascicle orientations that were validated against manually digitized values. The transverse fascicle strains were calculated from their wavelengths within the images. These methods showed that the transverse strain increases while the longitudinal fascicle length decreases; however, the extent of these strains was smaller than expected. PMID:25328509
Respiratory motion correction in emission tomography image reconstruction.
Reyes, Mauricio; Malandain, Grégoire; Koulibaly, Pierre Malick; González Ballester, Miguel A; Darcourt, Jacques
2005-01-01
In Emission Tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations and imprecise diagnosis. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested with improvements over the spatial activity distribution in lungs lesions, but with the disadvantages of requiring additional instrumentation or discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion correction directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the Maximum Likelihood Expectation Maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.
NASA Astrophysics Data System (ADS)
Gravel, Paul; Verhaeghe, Jeroen; Reader, Andrew J.
2013-01-01
This work explores the feasibility and impact of including both the motion correction and the image registration transformation parameters from positron emission tomography (PET) image space to magnetic resonance (MR), or stereotaxic, image space within the system matrix of PET image reconstruction. This approach is motivated by the fields of neuroscience and psychiatry, where PET is used to investigate differences in activation patterns between different groups of participants, requiring all images to be registered to a common spatial atlas. Currently, image registration is performed after image reconstruction which introduces interpolation effects into the final image. Furthermore, motion correction (also requiring registration) introduces a further level of interpolation, and the overall result of these operations can lead to resolution degradation and possibly artifacts. It is important to note that performing such operations on a post-reconstruction basis means, strictly speaking, that the final images are not ones which maximize the desired objective function (e.g. maximum likelihood (ML), or maximum a posteriori reconstruction (MAP)). To correctly seek parameter estimates in the desired spatial atlas which are in accordance with the chosen reconstruction objective function, it is necessary to include the transformation parameters for both motion correction and registration within the system modeling stage of image reconstruction. Such an approach not only respects the statistically chosen objective function (e.g. ML or MAP), but furthermore should serve to reduce the interpolation effects. To evaluate the proposed method, this work investigates registration (including motion correction) using 2D and 3D simulations based on the high resolution research tomograph (HRRT) PET scanner geometry, with and without resolution modeling, using the ML expectation maximization (MLEM) reconstruction algorithm. The quality of reconstruction was assessed using bias
Sparse representation for the ISAR image reconstruction
NASA Astrophysics Data System (ADS)
Hu, Mengqi; Montalbo, John; Li, Shuxia; Sun, Ligang; Qiao, Zhijun G.
2016-05-01
In this paper, a sparse representation of the data for an inverse synthetic aperture radar (ISAR) system is provided in two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization that recovers the image with far less samples, which is required by Nyquist-Shannon sampling theorem to increases the efficiency and decrease the cost of calculation in radar imaging.
Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Arefan, D.; Talebpour, A.; Ahmadinejhad, N.; Kamali Asl, A.
2015-01-01
Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU). At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU) card and the Graphics Processing Unit (GPU). It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU). PMID:26171373
Image reconstruction for hybrid true-color micro-CT.
Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge
2012-06-01
X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid "true-color" micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a "color diffusion" phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose.
Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc
2014-06-15
Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast
Local fingerprint image reconstruction based on gabor filtering
NASA Astrophysics Data System (ADS)
Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo
2012-06-01
In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.
A rapid reconstruction algorithm for three-dimensional scanning images
NASA Astrophysics Data System (ADS)
Xiang, Jiying; Wu, Zhen; Zhang, Ping; Huang, Dexiu
1998-04-01
A `simulated fluorescence' three-dimensional reconstruction algorithm, which is especially suitable for confocal images of partial transparent biological samples, is proposed in this paper. To make the retina projection of the object reappear and to avoid excessive memory consumption, the original image is rotated and compressed before the processing. A left image and a right image are mixed by different colors to increase the sense of stereo. The details originally hidden in deep layers are well exhibited with the aid of an `auxiliary directional source'. In addition, the time consumption is greatly reduced compared with conventional methods such as `ray tracing'. The realization of the algorithm is interpreted by a group of reconstructed images.
O'Connell, Rachel L; Stevens, Roger J G; Harris, Paul A; Rusby, Jennifer E
2015-08-01
Three-dimensional surface imaging (3D-SI) is being marketed as a tool in aesthetic breast surgery. It has recently also been studied in the objective evaluation of cosmetic outcome of oncological procedures. The aim of this review is to summarise the use of 3D-SI in oncoplastic, reconstructive and aesthetic breast surgery. An extensive literature review was undertaken to identify published studies. Two reviewers independently screened all abstracts and selected relevant articles using specific inclusion criteria. Seventy two articles relating to 3D-SI for breast surgery were identified. These covered endpoints such as image acquisition, calculations and data obtainable, comparison of 3D and 2D imaging and clinical research applications of 3D-SI. The literature provides a favourable view of 3D-SI. However, evidence of its superiority over current methods of clinical decision making, surgical planning, communication and evaluation of outcome is required before it can be accepted into mainstream practice.
NASA Astrophysics Data System (ADS)
Warren, L. M.; Cooke, J.; Given-Wilson, R. M.; Wallis, M. G.; Halling-Brown, M.; Mackenzie, A.; Chakraborty, D. P.; Bosmans, H.; Dance, D. R.; Young, K. C.
2013-03-01
Image processing (IP) is the last step in the digital mammography imaging chain before interpretation by a radiologist. Each manufacturer has their own IP algorithm(s) and the appearance of an image after IP can vary greatly depending upon the algorithm and version used. It is unclear whether these differences can affect cancer detection. This work investigates the effect of IP on the detection of non-calcification cancers by expert observers. Digital mammography images for 190 patients were collected from two screening sites using Hologic amorphous selenium detectors. Eighty of these cases contained non-calcification cancers. The images were processed using three versions of IP from Hologic - default (full enhancement), low contrast (intermediate enhancement) and pseudo screen-film (no enhancement). Seven experienced observers inspected the images and marked the location of regions suspected to be non-calcification cancers assigning a score for likelihood of malignancy. This data was analysed using JAFROC analysis. The observers also scored the clinical interpretation of the entire case using the BSBR classification scale. This was analysed using ROC analysis. The breast density in the region surrounding each cancer and the number of times each cancer was detected were calculated. IP did not have a significant effect on the radiologists' judgment of the likelihood of malignancy of individual lesions or their clinical interpretation of the entire case. No correlation was found between number of times each cancer was detected and the density of breast tissue surrounding that cancer.
NASA Astrophysics Data System (ADS)
Samala, Ravi K.; Chan, Heang-Ping; Lu, Yao; Hadjiiski, Lubomir; Wei, Jun; Helvie, Mark
2015-03-01
Computer-aided detection (CAD) has the potential to aid radiologists in detection of microcalcification clusters (MCs). CAD for digital breast tomosynthesis (DBT) can be developed by using the reconstructed volume, the projection views or other derivatives as input. We have developed a novel method of generating a single planar projection (PPJ) image from a regularized DBT volume to emphasize the high contrast objects such as microcalcifications while removing the anatomical background and noise. In this work, we adapted a CAD system developed for digital mammography (CADDM) to the PPJ image and compared its performance with our CAD system developed for DBT volumes (CADDBT) in the same set of cases. For microcalcification detection in the PPJ image using the CADDM system, the background removal preprocessing step designed for DM was not needed. The other methods and processing steps in the CADDM system were kept without modification while the parameters were optimized with a training set. The linear discriminant analysis classifier using cluster based features was retrained to generate a discriminant score to be used as decision variable. For view-based FROC analysis, at 80% sensitivity, an FP rate of 1.95/volume and 1.54/image were achieved, respectively, for CADDBT and CADDM in an independent test set. At a threshold of 1.2 FPs per image or per DBT volume, the nonparametric analysis of the area under the FROC curve shows that the optimized CADDM for PPJ is significantly better than CADDBT. However, the performance of CADDM drops at higher sensitivity or FP rate, resulting in similar overall performance between the two CAD systems. The higher sensitivity of the CADDM in the low FP rate region and vice versa for the CADDBT indicate that a joint CAD system combining detection in the DBT volume and the PPJ image has the potential to increase the sensitivity and reduce the FP rate.
Narayanan, M V; King, M A; Wernick, M N; Byrne, C L; Soares, E J; Pretorius, P H
2000-05-01
Spatiotemporal reconstruction of cardiac-gated SPECT images permits us to obtain valuable information related to cardiac function. However, the task of reconstructing this four-dimensional (4-D) data set is computation intensive. Typically, these studies are reconstructed frame-by-frame: a nonoptimal approach because temporal correlations in the signal are not accounted for. In this work, we show that the compression and signal decorrelation properties of the Karhunen-Loève (KL) transform may be used to greatly simplify the spatiotemporal reconstruction problem. The gated projections are first KL transformed in the temporal direction. This results in a sequence of KL-transformed projection images for which the signal components are uncorrelated along the time axis. As a result, the 4-D reconstruction task is simplified to a series of three-dimensional (3-D) reconstructions in the KL domain. The reconstructed KL components are subsequently inverse KL transformed to obtain the entire spatiotemporal reconstruction set. Our simulation and clinical results indicate that KL processing provides image sequences that are less noisy than are conventional frame-by-frame reconstructions. Additionally, by discarding high-order KL components that are dominated by noise, we can achieve savings in computation time because fewer reconstructions are needed in comparison to conventional frame-by-frame reconstructions.
A methodology to event reconstruction from trace images.
Milliet, Quentin; Delémont, Olivier; Sapin, Eric; Margot, Pierre
2015-03-01
The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally
Dictionary Approaches to Image Compression and Reconstruction
NASA Technical Reports Server (NTRS)
Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.
1998-01-01
This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.
Dictionary Approaches to Image Compression and Reconstruction
NASA Technical Reports Server (NTRS)
Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.
1998-01-01
This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as lambda, are discrete time signals, where y represents the dictionary index. A dictionary with a collection of these waveforms Is typically complete or over complete. Given such a dictionary, the goal is to obtain a representation Image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.
Joint model of motion and anatomy for PET image reconstruction
Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama
2007-12-15
Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem.
Chapman, K E; Thomas, A D; Wills, J W; Pfuhler, S; Doak, S H; Jenkins, G J S
2014-05-01
Recent restrictions on the testing of cosmetic ingredients in animals have resulted in the need to test the genotoxic potential of chemicals exclusively in vitro prior to licensing. However, as current in vitro tests produce some misleading positive results, sole reliance on such tests could prevent some chemicals with safe or beneficial exposure levels from being marketed. The 3D human reconstructed skin micronucleus (RSMN) assay is a promising new in vitro approach designed to assess genotoxicity of dermally applied compounds. The assay utilises a highly differentiated in vitro model of the human epidermis. For the first time, we have applied automated micronucleus detection to this assay using MetaSystems Metafer Slide Scanning Platform (Metafer), demonstrating concordance with manual scoring. The RSMN assay's fixation protocol was found to be compatible with the Metafer, providing a considerably shorter alternative to the recommended Metafer protocol. Lowest observed genotoxic effect levels (LOGELs) were observed for mitomycin-C at 4.8 µg/ml and methyl methanesulfonate (MMS) at 1750 µg/ml when applied topically to the skin surface. In-medium dosing with MMS produced a LOGEL of 20 µg/ml, which was very similar to the topical LOGEL when considering the total mass of MMS added. Comparisons between 3D medium and 2D LOGELs resulted in a 7-fold difference in total mass of MMS applied to each system, suggesting a protective function of the 3D microarchitecture. Interestingly, hydrogen peroxide (H2O2), a positive clastogen in 2D systems, tested negative in this assay. A non-genotoxic carcinogen, methyl carbamate, produced negative results, as expected. We also demonstrated expression of the DNA repair protein N-methylpurine-DNA glycosylase in EpiDerm™. Our preliminary validation here demonstrates that the RSMN assay may be a valuable follow-up to the current in vitro test battery, and together with its automation, could contribute to minimising unnecessary in vivo
Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.
Fromm, S A; Sachse, C
2016-01-01
Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method.
Penalized maximum-likelihood image reconstruction for lesion detection
NASA Astrophysics Data System (ADS)
Qi, Jinyi; Huesman, Ronald H.
2006-08-01
Detecting cancerous lesions is one major application in emission tomography. In this paper, we study penalized maximum-likelihood image reconstruction for this important clinical task. Compared to analytical reconstruction methods, statistical approaches can improve the image quality by accurately modelling the photon detection process and measurement noise in imaging systems. To explore the full potential of penalized maximum-likelihood image reconstruction for lesion detection, we derived simplified theoretical expressions that allow fast evaluation of the detectability of a random lesion. The theoretical results are used to design the regularization parameters to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the proposed penalty function, conventional penalty function, and a penalty function for isotropic point spread function. The lesion detectability is measured by a channelized Hotelling observer. The results show that the proposed penalty function outperforms the other penalty functions for lesion detection. The relative improvement is dependent on the size of the lesion. However, we found that the penalty function optimized for a 5 mm lesion still outperforms the other two penalty functions for detecting a 14 mm lesion. Therefore, it is feasible to use the penalty function designed for small lesions in image reconstruction, because detection of large lesions is relatively easy.
Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.
Fromm, S A; Sachse, C
2016-01-01
Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. PMID:27572732
Compressed/reconstructed test images for CRAF/Cassini
NASA Technical Reports Server (NTRS)
Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.
1991-01-01
A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.
Gadgetron: an open source framework for medical image reconstruction.
Hansen, Michael Schacht; Sørensen, Thomas Sangild
2013-06-01
This work presents a new open source framework for medical image reconstruction called the "Gadgetron." The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or "Gadgets" from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging.