Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction.

PubMed

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

2016-01-01

Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems.

Iterative image reconstruction for multienergy computed tomography via structure tensor total variation regularization

NASA Astrophysics Data System (ADS)

Zeng, Dong; Bian, Zhaoying; Gong, Changfei; Huang, Jing; He, Ji; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

2016-03-01

Multienergy computed tomography (MECT) has the potential to simultaneously offer multiple sets of energy- selective data belonging to specific energy windows. However, because sufficient photon counts are not available in the specific energy windows compared with that in the whole energy window, the MECT images reconstructed by the analytical approach often suffer from poor signal-to-noise (SNR) and strong streak artifacts. To eliminate this drawback, in this work we present a penalized weighted least-squares (PWLS) scheme by incorporating the new concept of structure tensor total variation (STV) regularization to improve the MECT images quality from low-milliampere-seconds (low-mAs) data acquisitions. Henceforth the present scheme is referred to as `PWLS- STV' for simplicity. Specifically, the STV regularization is derived by penalizing the eigenvalues of the structure tensor of every point in the MECT images. Thus it can provide more robust measures of image variation, which can eliminate the patchy artifacts often observed in total variation regularization. Subsequently, an alternating optimization algorithm was adopted to minimize the objective function. Experiments with a digital XCAT phantom clearly demonstrate that the present PWLS-STV algorithm can achieve more gains than the existing TV-based algorithms and the conventional filtered backpeojection (FBP) algorithm in terms of noise-induced artifacts suppression, resolution preservation, and material decomposition assessment.

Adaptive regularization of the NL-means: application to image and video denoising.

PubMed

Sutour, Camille; Deledalle, Charles-Alban; Aujol, Jean-François

2014-08-01

Image denoising is a central problem in image processing and it is often a necessary step prior to higher level analysis such as segmentation, reconstruction, or super-resolution. The nonlocal means (NL-means) perform denoising by exploiting the natural redundancy of patterns inside an image; they perform a weighted average of pixels whose neighborhoods (patches) are close to each other. This reduces significantly the noise while preserving most of the image content. While it performs well on flat areas and textures, it suffers from two opposite drawbacks: it might over-smooth low-contrasted areas or leave a residual noise around edges and singular structures. Denoising can also be performed by total variation minimization-the Rudin, Osher and Fatemi model-which leads to restore regular images, but it is prone to over-smooth textures, staircasing effects, and contrast losses. We introduce in this paper a variational approach that corrects the over-smoothing and reduces the residual noise of the NL-means by adaptively regularizing nonlocal methods with the total variation. The proposed regularized NL-means algorithm combines these methods and reduces both of their respective defaults by minimizing an adaptive total variation with a nonlocal data fidelity term. Besides, this model adapts to different noise statistics and a fast solution can be obtained in the general case of the exponential family. We develop this model for image denoising and we adapt it to video denoising with 3D patches.

Closed-form expressions for flip angle variation that maximize total signal in T1-weighted rapid gradient echo MRI.

PubMed

Drobnitzky, Matthias; Klose, Uwe

2017-03-01

Magnetization-prepared rapid gradient-echo (MPRAGE) sequences are commonly employed for T1-weighted structural brain imaging. Following a contrast preparation radiofrequency (RF) pulse, the data acquisition proceeds under nonequilibrium conditions of the relaxing longitudinal magnetization. Variation of the flip angle can be used to maximize total available signal. Simulated annealing or greedy algorithms have so far been published to numerically solve this problem, with signal-to-noise ratios optimized for clinical imaging scenarios by adhering to a predefined shape of the signal evolution. We propose an unconstrained optimization of the MPRAGE experiment that employs techniques from resource allocation theory. A new dynamic programming solution is introduced that yields closed-form expressions for optimal flip angle variation. Flip angle series are proposed that maximize total transverse magnetization (Mxy) for a range of physiologic T1 values. A 3D MPRAGE sequence is modified to allow for a controlled variation of the excitation angle. Experiments employing a T1 contrast phantom are performed at 3T. 1D acquisitions without phase encoding permit measurement of the temporal development of Mxy. Image mean signal and standard deviation for reference flip angle trains are compared in 2D measurements. Signal profiles at sharp phantom edges are acquired to access image blurring related to nonuniform Mxy development. A novel closed-form expression for flip angle variation is found that constitutes the optimal policy to reach maximum total signal. It numerically equals previously published results of other authors when evaluated under their simplifying assumptions. Longitudinal magnetization (Mz) is exhaustively used without causing abrupt changes in the measured MR signal, which is a prerequisite for artifact free images. Phantom experiments at 3T verify the expected benefit for total accumulated k-space signal when compared with published flip angle series. Describing the MR signal collection in MPRAGE sequences as a Bellman problem is a new concept. By means of recursively solving a series of overlapping subproblems, this leads to an elegant solution for the problem of maximizing total available MR signal in k-space. A closed-form expression for flip angle variation avoids the complexity of numerical optimization and eases access to controlled variation in an attempt to identify potential clinical applications. © 2017 American Association of Physicists in Medicine.

Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction

PubMed Central

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

2016-01-01

Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems. PMID:26901410

Blind image fusion for hyperspectral imaging with the directional total variation

NASA Astrophysics Data System (ADS)

Bungert, Leon; Coomes, David A.; Ehrhardt, Matthias J.; Rasch, Jennifer; Reisenhofer, Rafael; Schönlieb, Carola-Bibiane

2018-04-01

Hyperspectral imaging is a cutting-edge type of remote sensing used for mapping vegetation properties, rock minerals and other materials. A major drawback of hyperspectral imaging devices is their intrinsic low spatial resolution. In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality. This is accomplished by solving a variational problem in which the regularization functional is the directional total variation. To accommodate for possible mis-registrations between the two images, we consider a non-convex blind super-resolution problem where both a fused image and the corresponding convolution kernel are estimated. Using this approach, our model can realign the given images if needed. Our experimental results indicate that the non-convexity is negligible in practice and that reliable solutions can be computed using a variety of different optimization algorithms. Numerical results on real remote sensing data from plant sciences and urban monitoring show the potential of the proposed method and suggests that it is robust with respect to the regularization parameters, mis-registration and the shape of the kernel.

Adaptive optics image restoration algorithm based on wavefront reconstruction and adaptive total variation method

NASA Astrophysics Data System (ADS)

Li, Dongming; Zhang, Lijuan; Wang, Ting; Liu, Huan; Yang, Jinhua; Chen, Guifen

2016-11-01

To improve the adaptive optics (AO) image's quality, we study the AO image restoration algorithm based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF). Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution issue. The image restoration experiments are performed to verify the image restoration effect of our proposed algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44% respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is significantly improved.

Carbon Dioxide Fluctuations in Comet Hartley 2

NASA Image and Video Library

2010-11-04

The upper panel of this figure shows small images of comet Hartley 2 taken by NASA EPOXI mission over time. The lower panel is a graph showing the variation of total brightness, and the variation of the total amount of carbon dioxide, during the time.

Penalized weighted least-squares approach for multienergy computed tomography image reconstruction via structure tensor total variation regularization.

PubMed

Zeng, Dong; Gao, Yuanyuan; Huang, Jing; Bian, Zhaoying; Zhang, Hua; Lu, Lijun; Ma, Jianhua

2016-10-01

Multienergy computed tomography (MECT) allows identifying and differentiating different materials through simultaneous capture of multiple sets of energy-selective data belonging to specific energy windows. However, because sufficient photon counts are not available in each energy window compared with that in the whole energy window, the MECT images reconstructed by the analytical approach often suffer from poor signal-to-noise and strong streak artifacts. To address the particular challenge, this work presents a penalized weighted least-squares (PWLS) scheme by incorporating the new concept of structure tensor total variation (STV) regularization, which is henceforth referred to as 'PWLS-STV' for simplicity. Specifically, the STV regularization is derived by penalizing higher-order derivatives of the desired MECT images. Thus it could provide more robust measures of image variation, which can eliminate the patchy artifacts often observed in total variation (TV) regularization. Subsequently, an alternating optimization algorithm was adopted to minimize the objective function. Extensive experiments with a digital XCAT phantom and meat specimen clearly demonstrate that the present PWLS-STV algorithm can achieve more gains than the existing TV-based algorithms and the conventional filtered backpeojection (FBP) algorithm in terms of both quantitative and visual quality evaluations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

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

Kim, D; Kang, S; Kim, T

2014-06-01

Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studiesmore » to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)« less

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

PubMed

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

2018-04-12

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

Composite SAR imaging using sequential joint sparsity

NASA Astrophysics Data System (ADS)

Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.

2017-06-01

This paper investigates accurate and efficient ℓ1 regularization methods for generating synthetic aperture radar (SAR) images. Although ℓ1 regularization algorithms are already employed in SAR imaging, practical and efficient implementation in terms of real time imaging remain a challenge. Here we demonstrate that fast numerical operators can be used to robustly implement ℓ1 regularization methods that are as or more efficient than traditional approaches such as back projection, while providing superior image quality. In particular, we develop a sequential joint sparsity model for composite SAR imaging which naturally combines the joint sparsity methodology with composite SAR. Our technique, which can be implemented using standard, fractional, or higher order total variation regularization, is able to reduce the effects of speckle and other noisy artifacts with little additional computational cost. Finally we show that generalizing total variation regularization to non-integer and higher orders provides improved flexibility and robustness for SAR imaging.

Nonlocal Total-Variation-Based Speckle Filtering for Ultrasound Images.

PubMed

Wen, Tiexiang; Gu, Jia; Li, Ling; Qin, Wenjian; Wang, Lei; Xie, Yaoqin

2016-07-01

Ultrasound is one of the most important medical imaging modalities for its real-time and portable imaging advantages. However, the contrast resolution and important details are degraded by the speckle in ultrasound images. Many speckle filtering methods have been developed, but they are suffered from several limitations, difficult to reach a balance between speckle reduction and edge preservation. In this paper, an adaptation of the nonlocal total variation (NLTV) filter is proposed for speckle reduction in ultrasound images. The speckle is modeled via a signal-dependent noise distribution for the log-compressed ultrasound images. Instead of the Euclidian distance, the statistical Pearson distance is introduced in this study for the similarity calculation between image patches via the Bayesian framework. And the Split-Bregman fast algorithm is used to solve the adapted NLTV despeckling functional. Experimental results on synthetic and clinical ultrasound images and comparisons with some classical and recent algorithms are used to demonstrate its improvements in both speckle noise reduction and tissue boundary preservation for ultrasound images. © The Author(s) 2015.

A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford-Shah Image Segmentation

DTIC Science & Technology

2016-05-01

norm does not cap - ture the geometry completely. The L1−L2 in (c) does a better job than TV while L1 in (b) and L1−0.5L2 in (d) capture the squares most...and isotropic total variation (TV) norms into a relaxed formu- lation of the two phase Mumford-Shah (MS) model for image segmentation. We show...results exceeding those obtained by the MS model when using the standard TV norm to regular- ize partition boundaries. In particular, examples illustrating

Introduction of Total Variation Regularization into Filtered Backprojection Algorithm

NASA Astrophysics Data System (ADS)

Raczyński, L.; Wiślicki, W.; Klimaszewski, K.; Krzemień, W.; Kowalski, P.; Shopa, R. Y.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kisielewska-Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Sharma, N. G.; Sharma, S.; Silarski, M.; Skurzok, M.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.

In this paper we extend the state-of-the-art filtered backprojection (FBP) method with application of the concept of Total Variation regularization. We compare the performance of the new algorithm with the most common form of regularizing in the FBP image reconstruction via apodizing functions. The methods are validated in terms of cross-correlation coefficient between reconstructed and real image of radioactive tracer distribution using standard Derenzo-type phantom. We demonstrate that the proposed approach results in higher cross-correlation values with respect to the standard FBP method.

Iterative image reconstruction that includes a total variation regularization for radial MRI.

PubMed

Kojima, Shinya; Shinohara, Hiroyuki; Hashimoto, Takeyuki; Hirata, Masami; Ueno, Eiko

2015-07-01

This paper presents an iterative image reconstruction method for radial encodings in MRI based on a total variation (TV) regularization. The algebraic reconstruction method combined with total variation regularization (ART_TV) is implemented with a regularization parameter specifying the weight of the TV term in the optimization process. We used numerical simulations of a Shepp-Logan phantom, as well as experimental imaging of a phantom that included a rectangular-wave chart, to evaluate the performance of ART_TV, and to compare it with that of the Fourier transform (FT) method. The trade-off between spatial resolution and signal-to-noise ratio (SNR) was investigated for different values of the regularization parameter by experiments on a phantom and a commercially available MRI system. ART_TV was inferior to the FT with respect to the evaluation of the modulation transfer function (MTF), especially at high frequencies; however, it outperformed the FT with regard to the SNR. In accordance with the results of SNR measurement, visual impression suggested that the image quality of ART_TV was better than that of the FT for reconstruction of a noisy image of a kiwi fruit. In conclusion, ART_TV provides radial MRI with improved image quality for low-SNR data; however, the regularization parameter in ART_TV is a critical factor for obtaining improvement over the FT.

Research on compressive sensing reconstruction algorithm based on total variation model

NASA Astrophysics Data System (ADS)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Recovering fine details from under-resolved electron tomography data using higher order total variation ℓ 1 regularization

DOE PAGES

Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.; ...

2017-01-03

Over the last decade or so, reconstruction methods using ℓ 1 regularization, often categorized as compressed sensing (CS) algorithms, have significantly improved the capabilities of high fidelity imaging in electron tomography. The most popular ℓ 1 regularization approach within electron tomography has been total variation (TV) regularization. In addition to reducing unwanted noise, TV regularization encourages a piecewise constant solution with sparse boundary regions. In this paper we propose an alternative ℓ 1 regularization approach for electron tomography based on higher order total variation (HOTV). Like TV, the HOTV approach promotes solutions with sparse boundary regions. In smooth regions however,more » the solution is not limited to piecewise constant behavior. We demonstrate that this allows for more accurate reconstruction of a broader class of images – even those for which TV was designed for – particularly when dealing with pragmatic tomographic sampling patterns and very fine image features. In conclusion, we develop results for an electron tomography data set as well as a phantom example, and we also make comparisons with discrete tomography approaches.« less

Selection of regularization parameter in total variation image restoration.

PubMed

Liao, Haiyong; Li, Fang; Ng, Michael K

2009-11-01

We consider and study total variation (TV) image restoration. In the literature there are several regularization parameter selection methods for Tikhonov regularization problems (e.g., the discrepancy principle and the generalized cross-validation method). However, to our knowledge, these selection methods have not been applied to TV regularization problems. The main aim of this paper is to develop a fast TV image restoration method with an automatic selection of the regularization parameter scheme to restore blurred and noisy images. The method exploits the generalized cross-validation (GCV) technique to determine inexpensively how much regularization to use in each restoration step. By updating the regularization parameter in each iteration, the restored image can be obtained. Our experimental results for testing different kinds of noise show that the visual quality and SNRs of images restored by the proposed method is promising. We also demonstrate that the method is efficient, as it can restore images of size 256 x 256 in approximately 20 s in the MATLAB computing environment.

Noisy image magnification with total variation regularization and order-changed dictionary learning

NASA Astrophysics Data System (ADS)

Xu, Jian; Chang, Zhiguo; Fan, Jiulun; Zhao, Xiaoqiang; Wu, Xiaomin; Wang, Yanzi

2015-12-01

Noisy low resolution (LR) images are always obtained in real applications, but many existing image magnification algorithms can not get good result from a noisy LR image. We propose a two-step image magnification algorithm to solve this problem. The proposed algorithm takes the advantages of both regularization-based method and learning-based method. The first step is based on total variation (TV) regularization and the second step is based on sparse representation. In the first step, we add a constraint on the TV regularization model to magnify the LR image and at the same time to suppress the noise in it. In the second step, we propose an order-changed dictionary training algorithm to train the dictionaries which is dominated by texture details. Experimental results demonstrate that the proposed algorithm performs better than many other algorithms when the noise is not serious. The proposed algorithm can also provide better visual quality on natural LR images.

Selecting good regions to deblur via relative total variation

NASA Astrophysics Data System (ADS)

Li, Lerenhan; Yan, Hao; Fan, Zhihua; Zheng, Hanqing; Gao, Changxin; Sang, Nong

2018-03-01

Image deblurring is to estimate the blur kernel and to restore the latent image. It is usually divided into two stage, including kernel estimation and image restoration. In kernel estimation, selecting a good region that contains structure information is helpful to the accuracy of estimated kernel. Good region to deblur is usually expert-chosen or in a trial-anderror way. In this paper, we apply a metric named relative total variation (RTV) to discriminate the structure regions from smooth and texture. Given a blurry image, we first calculate the RTV of each pixel to determine whether it is the pixel in structure region, after which, we sample the image in an overlapping way. At last, the sampled region that contains the most structure pixels is the best region to deblur. Both qualitative and quantitative experiments show that our proposed method can help to estimate the kernel accurately.

Parallel algorithm of real-time infrared image restoration based on total variation theory

NASA Astrophysics Data System (ADS)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

Bayesian denoising in digital radiography: a comparison in the dental field.

PubMed

Frosio, I; Olivieri, C; Lucchese, M; Borghese, N A; Boccacci, P

2013-01-01

We compared two Bayesian denoising algorithms for digital radiographs, based on Total Variation regularization and wavelet decomposition. The comparison was performed on simulated radiographs with different photon counts and frequency content and on real dental radiographs. Four different quality indices were considered to quantify the quality of the filtered radiographs. The experimental results suggested that Total Variation is more suited to preserve fine anatomical details, whereas wavelets produce images of higher quality at global scale; they also highlighted the need for more reliable image quality indices. Copyright © 2012 Elsevier Ltd. All rights reserved.

A comparative study of new and current methods for dental micro-CT image denoising

PubMed Central

Lashgari, Mojtaba; Qin, Jie; Swain, Michael

2016-01-01

Objectives: The aim of the current study was to evaluate the application of two advanced noise-reduction algorithms for dental micro-CT images and to implement a comparative analysis of the performance of new and current denoising algorithms. Methods: Denoising was performed using gaussian and median filters as the current filtering approaches and the block-matching and three-dimensional (BM3D) method and total variation method as the proposed new filtering techniques. The performance of the denoising methods was evaluated quantitatively using contrast-to-noise ratio (CNR), edge preserving index (EPI) and blurring indexes, as well as qualitatively using the double-stimulus continuous quality scale procedure. Results: The BM3D method had the best performance with regard to preservation of fine textural features (CNREdge), non-blurring of the whole image (blurring index), the clinical visual score in images with very fine features and the overall visual score for all types of images. On the other hand, the total variation method provided the best results with regard to smoothing of images in texture-free areas (CNRTex-free) and in preserving the edges and borders of image features (EPI). Conclusions: The BM3D method is the most reliable technique for denoising dental micro-CT images with very fine textural details, such as shallow enamel lesions, in which the preservation of the texture and fine features is of the greatest importance. On the other hand, the total variation method is the technique of choice for denoising images without very fine textural details in which the clinician or researcher is interested mainly in anatomical features and structural measurements. PMID:26764583

Total variation approach for adaptive nonuniformity correction in focal-plane arrays.

PubMed

Vera, Esteban; Meza, Pablo; Torres, Sergio

2011-01-15

In this Letter we propose an adaptive scene-based nonuniformity correction method for fixed-pattern noise removal in imaging arrays. It is based on the minimization of the total variation of the estimated irradiance, and the resulting function is optimized by an isotropic total variation approach making use of an alternating minimization strategy. The proposed method provides enhanced results when applied to a diverse set of real IR imagery, accurately estimating the nonunifomity parameters of each detector in the focal-plane array at a fast convergence rate, while also forming fewer ghosting artifacts.

Multichannel blind iterative image restoration.

PubMed

Sroubek, Filip; Flusser, Jan

2003-01-01

Blind image deconvolution is required in many applications of microscopy imaging, remote sensing, and astronomical imaging. Unfortunately in a single-channel framework, serious conceptual and numerical problems are often encountered. Very recently, an eigenvector-based method (EVAM) was proposed for a multichannel framework which determines perfectly convolution masks in a noise-free environment if channel disparity, called co-primeness, is satisfied. We propose a novel iterative algorithm based on recent anisotropic denoising techniques of total variation and a Mumford-Shah functional with the EVAM restoration condition included. A linearization scheme of half-quadratic regularization together with a cell-centered finite difference discretization scheme is used in the algorithm and provides a unified approach to the solution of total variation or Mumford-Shah. The algorithm performs well even on very noisy images and does not require an exact estimation of mask orders. We demonstrate capabilities of the algorithm on synthetic data. Finally, the algorithm is applied to defocused images taken with a digital camera and to data from astronomical ground-based observations of the Sun.

Electron paramagnetic resonance image reconstruction with total variation and curvelets regularization

NASA Astrophysics Data System (ADS)

Durand, Sylvain; Frapart, Yves-Michel; Kerebel, Maud

2017-11-01

Spatial electron paramagnetic resonance imaging (EPRI) is a recent method to localize and characterize free radicals in vivo or in vitro, leading to applications in material and biomedical sciences. To improve the quality of the reconstruction obtained by EPRI, a variational method is proposed to inverse the image formation model. It is based on a least-square data-fidelity term and the total variation and Besov seminorm for the regularization term. To fully comprehend the Besov seminorm, an implementation using the curvelet transform and the L 1 norm enforcing the sparsity is proposed. It allows our model to reconstruct both image where acquisition information are missing and image with details in textured areas, thus opening possibilities to reduce acquisition times. To implement the minimization problem using the algorithm developed by Chambolle and Pock, a thorough analysis of the direct model is undertaken and the latter is inverted while avoiding the use of filtered backprojection (FBP) and of non-uniform Fourier transform. Numerical experiments are carried out on simulated data, where the proposed model outperforms both visually and quantitatively the classical model using deconvolution and FBP. Improved reconstructions on real data, acquired on an irradiated distal phalanx, were successfully obtained.

A novel scatter-matrix eigenvalues-based total variation (SMETV) regularization for medical image restoration

NASA Astrophysics Data System (ADS)

Huang, Zhenghua; Zhang, Tianxu; Deng, Lihua; Fang, Hao; Li, Qian

2015-12-01

Total variation(TV) based on regularization has been proven as a popular and effective model for image restoration, because of its ability of edge preserved. However, as the TV favors a piece-wise constant solution, the processing results in the flat regions of the image are easily produced "staircase effects", and the amplitude of the edges will be underestimated; the underlying cause of the problem is that the regularization parameter can not be changeable with spatial local information of image. In this paper, we propose a novel Scatter-matrix eigenvalues-based TV(SMETV) regularization with image blind restoration algorithm for deblurring medical images. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.

Total variation-based method for radar coincidence imaging with model mismatch for extended target

NASA Astrophysics Data System (ADS)

Cao, Kaicheng; Zhou, Xiaoli; Cheng, Yongqiang; Fan, Bo; Qin, Yuliang

2017-11-01

Originating from traditional optical coincidence imaging, radar coincidence imaging (RCI) is a staring/forward-looking imaging technique. In RCI, the reference matrix must be computed precisely to reconstruct the image as preferred; unfortunately, such precision is almost impossible due to the existence of model mismatch in practical applications. Although some conventional sparse recovery algorithms are proposed to solve the model-mismatch problem, they are inapplicable to nonsparse targets. We therefore sought to derive the signal model of RCI with model mismatch by replacing the sparsity constraint item with total variation (TV) regularization in the sparse total least squares optimization problem; in this manner, we obtain the objective function of RCI with model mismatch for an extended target. A more robust and efficient algorithm called TV-TLS is proposed, in which the objective function is divided into two parts and the perturbation matrix and scattering coefficients are updated alternately. Moreover, due to the ability of TV regularization to recover sparse signal or image with sparse gradient, TV-TLS method is also applicable to sparse recovering. Results of numerical experiments demonstrate that, for uniform extended targets, sparse targets, and real extended targets, the algorithm can achieve preferred imaging performance both in suppressing noise and in adapting to model mismatch.

A sequential solution for anisotropic total variation image denoising with interval constraints

NASA Astrophysics Data System (ADS)

Xu, Jingyan; Noo, Frédéric

2017-09-01

We show that two problems involving the anisotropic total variation (TV) and interval constraints on the unknown variables admit, under some conditions, a simple sequential solution. Problem 1 is a constrained TV penalized image denoising problem; problem 2 is a constrained fused lasso signal approximator. The sequential solution entails finding first the solution to the unconstrained problem, and then applying a thresholding to satisfy the constraints. If the interval constraints are uniform, this sequential solution solves problem 1. If the interval constraints furthermore contain zero, the sequential solution solves problem 2. Here uniform interval constraints refer to all unknowns being constrained to the same interval. A typical example of application is image denoising in x-ray CT, where the image intensities are non-negative as they physically represent linear attenuation coefficient in the patient body. Our results are simple yet seem unknown; we establish them using the Karush-Kuhn-Tucker conditions for constrained convex optimization.

Accelerating cross-validation with total variation and its application to super-resolution imaging

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Ikeda, Shiro; Akiyama, Kazunori; Kabashima, Yoshiyuki

2017-12-01

We develop an approximation formula for the cross-validation error (CVE) of a sparse linear regression penalized by ℓ_1-norm and total variation terms, which is based on a perturbative expansion utilizing the largeness of both the data dimensionality and the model. The developed formula allows us to reduce the necessary computational cost of the CVE evaluation significantly. The practicality of the formula is tested through application to simulated black-hole image reconstruction on the event-horizon scale with super resolution. The results demonstrate that our approximation reproduces the CVE values obtained via literally conducted cross-validation with reasonably good precision.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

A spatially-variant deconvolution method based on total variation for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Almasganj, Mohammad; Adabi, Saba; Fatemizadeh, Emad; Xu, Qiuyun; Sadeghi, Hamid; Daveluy, Steven; Nasiriavanaki, Mohammadreza

2017-03-01

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.

Block matching sparsity regularization-based image reconstruction for incomplete projection data in computed tomography

NASA Astrophysics Data System (ADS)

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

2018-02-01

In medical imaging many conventional regularization methods, such as total variation or total generalized variation, impose strong prior assumptions which can only account for very limited classes of images. A more reasonable sparse representation frame for images is still badly needed. Visually understandable images contain meaningful patterns, and combinations or collections of these patterns can be utilized to form some sparse and redundant representations which promise to facilitate image reconstructions. In this work, we propose and study block matching sparsity regularization (BMSR) and devise an optimization program using BMSR for computed tomography (CT) image reconstruction for an incomplete projection set. The program is built as a constrained optimization, minimizing the L1-norm of the coefficients of the image in the transformed domain subject to data observation and positivity of the image itself. To solve the program efficiently, a practical method based on the proximal point algorithm is developed and analyzed. In order to accelerate the convergence rate, a practical strategy for tuning the BMSR parameter is proposed and applied. The experimental results for various settings, including real CT scanning, have verified the proposed reconstruction method showing promising capabilities over conventional regularization.

Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study.

PubMed

Wang, Chunhao; Yin, Fang-Fang; Kirkpatrick, John P; Chang, Zheng

2017-08-01

To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant K trans in the extended Tofts model and blood flow F B and blood volume V B from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.

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

PubMed

Wang, Jin; Zhang, Chen; Wang, Yuanyuan

2017-05-30

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

Digital tomosynthesis (DTS) with a Circular X-ray tube: Its image reconstruction based on total-variation minimization and the image characteristics

NASA Astrophysics Data System (ADS)

Park, Y. O.; Hong, D. K.; Cho, H. S.; Je, U. K.; Oh, J. E.; Lee, M. S.; Kim, H. J.; Lee, S. H.; Jang, W. S.; Cho, H. M.; Choi, S. I.; Koo, Y. S.

2013-09-01

In this paper, we introduce an effective imaging system for digital tomosynthesis (DTS) with a circular X-ray tube, the so-called circular-DTS (CDTS) system, and its image reconstruction algorithm based on the total-variation (TV) minimization method for low-dose, high-accuracy X-ray imaging. Here, the X-ray tube is equipped with a series of cathodes distributed around a rotating anode, and the detector remains stationary throughout the image acquisition. We considered a TV-based reconstruction algorithm that exploited the sparsity of the image with substantially high image accuracy. We implemented the algorithm for the CDTS geometry and successfully reconstructed images of high accuracy. The image characteristics were investigated quantitatively by using some figures of merit, including the universal-quality index (UQI) and the depth resolution. For selected tomographic angles of 20, 40, and 60°, the corresponding UQI values in the tomographic view were estimated to be about 0.94, 0.97, and 0.98, and the depth resolutions were about 4.6, 3.1, and 1.2 voxels in full width at half maximum (FWHM), respectively. We expect the proposed method to be applicable to developing a next-generation dental or breast X-ray imaging system.

Investigation of optimization-based reconstruction with an image-total-variation constraint in PET

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Ye, Jinghan; Chen, Buxin; Perkins, Amy E.; Rose, Sean; Sidky, Emil Y.; Kao, Chien-Min; Xia, Dan; Tung, Chi-Hua; Pan, Xiaochuan

2016-08-01

Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.

Salt-and-pepper noise removal using modified mean filter and total variation minimization

NASA Astrophysics Data System (ADS)

Aghajarian, Mickael; McInroy, John E.; Wright, Cameron H. G.

2018-01-01

The search for effective noise removal algorithms is still a real challenge in the field of image processing. An efficient image denoising method is proposed for images that are corrupted by salt-and-pepper noise. Salt-and-pepper noise takes either the minimum or maximum intensity, so the proposed method restores the image by processing the pixels whose values are either 0 or 255 (assuming an 8-bit/pixel image). For low levels of noise corruption (less than or equal to 50% noise density), the method employs the modified mean filter (MMF), while for heavy noise corruption, noisy pixels values are replaced by the weighted average of the MMF and the total variation of corrupted pixels, which is minimized using convex optimization. Two fuzzy systems are used to determine the weights for taking average. To evaluate the performance of the algorithm, several test images with different noise levels are restored, and the results are quantitatively measured by peak signal-to-noise ratio and mean absolute error. The results show that the proposed scheme gives considerable noise suppression up to a noise density of 90%, while almost completely maintaining edges and fine details of the original image.

A MAP blind image deconvolution algorithm with bandwidth over-constrained

NASA Astrophysics Data System (ADS)

Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong

2018-03-01

We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.

Micro-CT image reconstruction based on alternating direction augmented Lagrangian method and total variation.

PubMed

Gopi, Varun P; Palanisamy, P; Wahid, Khan A; Babyn, Paul; Cooper, David

2013-01-01

Micro-computed tomography (micro-CT) plays an important role in pre-clinical imaging. The radiation from micro-CT can result in excess radiation exposure to the specimen under test, hence the reduction of radiation from micro-CT is essential. The proposed research focused on analyzing and testing an alternating direction augmented Lagrangian (ADAL) algorithm to recover images from random projections using total variation (TV) regularization. The use of TV regularization in compressed sensing problems makes the recovered image quality sharper by preserving the edges or boundaries more accurately. In this work TV regularization problem is addressed by ADAL which is a variant of the classic augmented Lagrangian method for structured optimization. The per-iteration computational complexity of the algorithm is two fast Fourier transforms, two matrix vector multiplications and a linear time shrinkage operation. Comparison of experimental results indicate that the proposed algorithm is stable, efficient and competitive with the existing algorithms for solving TV regularization problems. Copyright © 2013 Elsevier Ltd. All rights reserved.

Parameter selection in limited data cone-beam CT reconstruction using edge-preserving total variation algorithms

NASA Astrophysics Data System (ADS)

Lohvithee, Manasavee; Biguri, Ander; Soleimani, Manuchehr

2017-12-01

There are a number of powerful total variation (TV) regularization methods that have great promise in limited data cone-beam CT reconstruction with an enhancement of image quality. These promising TV methods require careful selection of the image reconstruction parameters, for which there are no well-established criteria. This paper presents a comprehensive evaluation of parameter selection in a number of major TV-based reconstruction algorithms. An appropriate way of selecting the values for each individual parameter has been suggested. Finally, a new adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm is presented, which implements the edge-preserving function for CBCT reconstruction with limited data. The proposed algorithm shows significant robustness compared to three other existing algorithms: ASD-POCS, AwASD-POCS and PCSD. The proposed AwPCSD algorithm is able to preserve the edges of the reconstructed images better with fewer sensitive parameters to tune.

Total Variation with Overlapping Group Sparsity for Image Deblurring under Impulse Noise

PubMed Central

Liu, Gang; Huang, Ting-Zhu; Liu, Jun; Lv, Xiao-Guang

2015-01-01

The total variation (TV) regularization method is an effective method for image deblurring in preserving edges. However, the TV based solutions usually have some staircase effects. In order to alleviate the staircase effects, we propose a new model for restoring blurred images under impulse noise. The model consists of an ℓ1-fidelity term and a TV with overlapping group sparsity (OGS) regularization term. Moreover, we impose a box constraint to the proposed model for getting more accurate solutions. The solving algorithm for our model is under the framework of the alternating direction method of multipliers (ADMM). We use an inner loop which is nested inside the majorization minimization (MM) iteration for the subproblem of the proposed method. Compared with other TV-based methods, numerical results illustrate that the proposed method can significantly improve the restoration quality, both in terms of peak signal-to-noise ratio (PSNR) and relative error (ReE). PMID:25874860

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

Blind motion image deblurring using nonconvex higher-order total variation model

NASA Astrophysics Data System (ADS)

Li, Weihong; Chen, Rui; Xu, Shangwen; Gong, Weiguo

2016-09-01

We propose a nonconvex higher-order total variation (TV) method for blind motion image deblurring. First, we introduce a nonconvex higher-order TV differential operator to define a new model of the blind motion image deblurring, which can effectively eliminate the staircase effect of the deblurred image; meanwhile, we employ an image sparse prior to improve the edge recovery quality. Second, to improve the accuracy of the estimated motion blur kernel, we use L1 norm and H1 norm as the blur kernel regularization term, considering the sparsity and smoothing of the motion blur kernel. Third, because it is difficult to solve the numerically computational complexity problem of the proposed model owing to the intrinsic nonconvexity, we propose a binary iterative strategy, which incorporates a reweighted minimization approximating scheme in the outer iteration, and a split Bregman algorithm in the inner iteration. And we also discuss the convergence of the proposed binary iterative strategy. Last, we conduct extensive experiments on both synthetic and real-world degraded images. The results demonstrate that the proposed method outperforms the previous representative methods in both quality of visual perception and quantitative measurement.

s-SMOOTH: Sparsity and Smoothness Enhanced EEG Brain Tomography

PubMed Central

Li, Ying; Qin, Jing; Hsin, Yue-Loong; Osher, Stanley; Liu, Wentai

2016-01-01

EEG source imaging enables us to reconstruct current density in the brain from the electrical measurements with excellent temporal resolution (~ ms). The corresponding EEG inverse problem is an ill-posed one that has infinitely many solutions. This is due to the fact that the number of EEG sensors is usually much smaller than that of the potential dipole locations, as well as noise contamination in the recorded signals. To obtain a unique solution, regularizations can be incorporated to impose additional constraints on the solution. An appropriate choice of regularization is critically important for the reconstruction accuracy of a brain image. In this paper, we propose a novel Sparsity and SMOOthness enhanced brain TomograpHy (s-SMOOTH) method to improve the reconstruction accuracy by integrating two recently proposed regularization techniques: Total Generalized Variation (TGV) regularization and ℓ1−2 regularization. TGV is able to preserve the source edge and recover the spatial distribution of the source intensity with high accuracy. Compared to the relevant total variation (TV) regularization, TGV enhances the smoothness of the image and reduces staircasing artifacts. The traditional TGV defined on a 2D image has been widely used in the image processing field. In order to handle 3D EEG source images, we propose a voxel-based Total Generalized Variation (vTGV) regularization that extends the definition of second-order TGV from 2D planar images to 3D irregular surfaces such as cortex surface. In addition, the ℓ1−2 regularization is utilized to promote sparsity on the current density itself. We demonstrate that ℓ1−2 regularization is able to enhance sparsity and accelerate computations than ℓ1 regularization. The proposed model is solved by an efficient and robust algorithm based on the difference of convex functions algorithm (DCA) and the alternating direction method of multipliers (ADMM). Numerical experiments using synthetic data demonstrate the advantages of the proposed method over other state-of-the-art methods in terms of total reconstruction accuracy, localization accuracy and focalization degree. The application to the source localization of event-related potential data further demonstrates the performance of the proposed method in real-world scenarios. PMID:27965529

Joint L1 and Total Variation Regularization for Fluorescence Molecular Tomography

PubMed Central

Dutta, Joyita; Ahn, Sangtae; Li, Changqing; Cherry, Simon R.; Leahy, Richard M.

2012-01-01

Fluorescence molecular tomography (FMT) is an imaging modality that exploits the specificity of fluorescent biomarkers to enable 3D visualization of molecular targets and pathways in vivo in small animals. Owing to the high degree of absorption and scattering of light through tissue, the FMT inverse problem is inherently illconditioned making image reconstruction highly susceptible to the effects of noise and numerical errors. Appropriate priors or penalties are needed to facilitate reconstruction and to restrict the search space to a specific solution set. Typically, fluorescent probes are locally concentrated within specific areas of interest (e.g., inside tumors). The commonly used L2 norm penalty generates the minimum energy solution, which tends to be spread out in space. Instead, we present here an approach involving a combination of the L1 and total variation norm penalties, the former to suppress spurious background signals and enforce sparsity and the latter to preserve local smoothness and piecewise constancy in the reconstructed images. We have developed a surrogate-based optimization method for minimizing the joint penalties. The method was validated using both simulated and experimental data obtained from a mouse-shaped phantom mimicking tissue optical properties and containing two embedded fluorescent sources. Fluorescence data was collected using a 3D FMT setup that uses an EMCCD camera for image acquisition and a conical mirror for full-surface viewing. A range of performance metrics were utilized to evaluate our simulation results and to compare our method with the L1, L2, and total variation norm penalty based approaches. The experimental results were assessed using Dice similarity coefficients computed after co-registration with a CT image of the phantom. PMID:22390906

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study.

PubMed

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-21

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed 'MPD-AwTTV'. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

NASA Astrophysics Data System (ADS)

Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

2016-11-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

NASA Astrophysics Data System (ADS)

Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

2018-06-01

Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.

Interior region-of-interest reconstruction using a small, nearly piecewise constant subregion

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

Taguchi, Katsuyuki; Xu Jingyan; Srivastava, Somesh

2011-03-15

Purpose: To develop a method to reconstruct an interior region-of-interest (ROI) image with sufficient accuracy that uses differentiated backprojection (DBP) projection onto convex sets (POCS) [H. Kudo et al., ''Tiny a priori knowledge solves the interior problem in computed tomography'', Phys. Med. Biol. 53, 2207-2231 (2008)] and a tiny knowledge that there exists a nearly piecewise constant subregion. Methods: The proposed method first employs filtered backprojection to reconstruct an image on which a tiny region P with a small variation in the pixel values is identified inside the ROI. Total variation minimization [H. Yu and G. Wang, ''Compressed sensing basedmore » interior tomography'', Phys. Med. Biol. 54, 2791-2805 (2009); W. Han et al., ''A general total variation minimization theorem for compressed sensing based interior tomography'', Int. J. Biomed. Imaging 2009, Article 125871 (2009)] is then employed to obtain pixel values in the subregion P, which serve as a priori knowledge in the next step. Finally, DBP-POCS is performed to reconstruct f(x,y) inside the ROI. Clinical data and the reconstructed image obtained by an x-ray computed tomography system (SOMATOM Definition; Siemens Healthcare) were used to validate the proposed method. The detector covers an object with a diameter of {approx}500 mm. The projection data were truncated either moderately to limit the detector coverage to diameter 350 mm of the object or severely to cover diameter 199 mm. Images were reconstructed using the proposed method. Results: The proposed method provided ROI images with correct pixel values in all areas except near the edge of the ROI. The coefficient of variation, i.e., the root mean square error divided by the mean pixel values, was less than 2.0% or 4.5% with the moderate or severe truncation cases, respectively, except near the boundary of the ROI. Conclusions: The proposed method allows for reconstructing interior ROI images with sufficient accuracy with a tiny knowledge that there exists a nearly piecewise constant subregion.« less

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

An interior-point method for total variation regularized positron emission tomography image reconstruction

NASA Astrophysics Data System (ADS)

Bai, Bing

2012-03-01

There has been a lot of work on total variation (TV) regularized tomographic image reconstruction recently. Many of them use gradient-based optimization algorithms with a differentiable approximation of the TV functional. In this paper we apply TV regularization in Positron Emission Tomography (PET) image reconstruction. We reconstruct the PET image in a Bayesian framework, using Poisson noise model and TV prior functional. The original optimization problem is transformed to an equivalent problem with inequality constraints by adding auxiliary variables. Then we use an interior point method with logarithmic barrier functions to solve the constrained optimization problem. In this method, a series of points approaching the solution from inside the feasible region are found by solving a sequence of subproblems characterized by an increasing positive parameter. We use preconditioned conjugate gradient (PCG) algorithm to solve the subproblems directly. The nonnegativity constraint is enforced by bend line search. The exact expression of the TV functional is used in our calculations. Simulation results show that the algorithm converges fast and the convergence is insensitive to the values of the regularization and reconstruction parameters.

Bayesian nonparametric dictionary learning for compressed sensing MRI.

PubMed

Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

2014-12-01

We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

A dictionary learning approach for Poisson image deblurring.

PubMed

Ma, Liyan; Moisan, Lionel; Yu, Jian; Zeng, Tieyong

2013-07-01

The restoration of images corrupted by blur and Poisson noise is a key issue in medical and biological image processing. While most existing methods are based on variational models, generally derived from a maximum a posteriori (MAP) formulation, recently sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, we propose in this paper a model containing three terms: a patch-based sparse representation prior over a learned dictionary, the pixel-based total variation regularization term and a data-fidelity term capturing the statistics of Poisson noise. The resulting optimization problem can be solved by an alternating minimization technique combined with variable splitting. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio value and the method noise, the proposed algorithm outperforms state-of-the-art methods.

Compressed sensing with gradient total variation for low-dose CBCT reconstruction

NASA Astrophysics Data System (ADS)

Seo, Chang-Woo; Cha, Bo Kyung; Jeon, Seongchae; Huh, Young; Park, Justin C.; Lee, Byeonghun; Baek, Junghee; Kim, Eunyoung

2015-06-01

This paper describes the improvement of convergence speed with gradient total variation (GTV) in compressed sensing (CS) for low-dose cone-beam computed tomography (CBCT) reconstruction. We derive a fast algorithm for the constrained total variation (TV)-based a minimum number of noisy projections. To achieve this task we combine the GTV with a TV-norm regularization term to promote an accelerated sparsity in the X-ray attenuation characteristics of the human body. The GTV is derived from a TV and enforces more efficient computationally and faster in convergence until a desired solution is achieved. The numerical algorithm is simple and derives relatively fast convergence. We apply a gradient projection algorithm that seeks a solution iteratively in the direction of the projected gradient while enforcing a non-negatively of the found solution. In comparison with the Feldkamp, Davis, and Kress (FDK) and conventional TV algorithms, the proposed GTV algorithm showed convergence in ≤18 iterations, whereas the original TV algorithm needs at least 34 iterations in reducing 50% of the projections compared with the FDK algorithm in order to reconstruct the chest phantom images. Future investigation includes improving imaging quality, particularly regarding X-ray cone-beam scatter, and motion artifacts of CBCT reconstruction.

Promote quantitative ischemia imaging via myocardial perfusion CT iterative reconstruction with tensor total generalized variation regularization

NASA Astrophysics Data System (ADS)

Gu, Chengwei; Zeng, Dong; Lin, Jiahui; Li, Sui; He, Ji; Zhang, Hao; Bian, Zhaoying; Niu, Shanzhou; Zhang, Zhang; Huang, Jing; Chen, Bo; Zhao, Dazhe; Chen, Wufan; Ma, Jianhua

2018-06-01

Myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect myocardial ischemia quantitatively. A limitation in MPCT is that an additional radiation dose is required compared to unenhanced CT due to its repeated dynamic data acquisition. Meanwhile, noise and streak artifacts in low-dose cases are the main factors that degrade the accuracy of quantifying myocardial ischemia and hamper the diagnostic utility of the filtered backprojection reconstructed MPCT images. Moreover, it is noted that the MPCT images are composed of a series of 2/3D images, which can be naturally regarded as a 3/4-order tensor, and the MPCT images are globally correlated along time and are sparse across space. To obtain higher fidelity ischemia from low-dose MPCT acquisitions quantitatively, we propose a robust statistical iterative MPCT image reconstruction algorithm by incorporating tensor total generalized variation (TTGV) regularization into a penalized weighted least-squares framework. Specifically, the TTGV regularization fuses the spatial correlation of the myocardial structure and the temporal continuation of the contrast agent intake during the perfusion. Then, an efficient iterative strategy is developed for the objective function optimization. Comprehensive evaluations have been conducted on a digital XCAT phantom and a preclinical porcine dataset regarding the accuracy of the reconstructed MPCT images, the quantitative differentiation of ischemia and the algorithm’s robustness and efficiency.

Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

PubMed Central

Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

2014-01-01

High radiation dose in CT scans increases a lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with Total Variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing an energy consisting of an edge-preserving TV norm and a data fidelity term posed by the x-ray projections. The edge-preserving TV term is proposed to preferentially perform smoothing only on non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original total variation norm. During the reconstruction process, the pixels at edges would be gradually identified and given small penalty weight. Our iterative algorithm is implemented on GPU to improve its speed. We test our reconstruction algorithm on a digital NCAT phantom, a physical chest phantom, and a Catphan phantom. Reconstruction results from a conventional FBP algorithm and a TV regularization method without edge preserving penalty are also presented for comparison purpose. The experimental results illustrate that both TV-based algorithm and our edge-preserving TV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under the low dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low contrast structures and therefore maintain acceptable spatial resolution. PMID:21860076

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization.

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization

PubMed Central

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate. PMID:27073853

Fetal head detection and measurement in ultrasound images by an iterative randomized Hough transform

NASA Astrophysics Data System (ADS)

Lu, Wei; Tan, Jinglu; Floyd, Randall C.

2004-05-01

This paper describes an automatic method for measuring the biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. A total of 217 ultrasound images were segmented by using a K-Mean classifier, and the head skull was detected in 214 of the 217 cases by an iterative randomized Hough transform developed for detection of incomplete curves in images with strong noise without user intervention. The automatic measurements were compared with conventional manual measurements by sonographers and a trained panel. The inter-run variations and differences between the automatic and conventional measurements were small compared with published inter-observer variations. The results showed that the automated measurements were as reliable as the expert measurements and more consistent. This method has great potential in clinical applications.

Accelerated Edge-Preserving Image Restoration Without Boundary Artifacts

PubMed Central

Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A.

2013-01-01

To reduce blur in noisy images, regularized image restoration methods have been proposed that use non-quadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a non-circulant model could prevent these artifacts at the cost of increased computational complexity. In this work we propose to use a circulant blur model combined with a masking operator that prevents wraparound artifacts. The resulting model is non-circulant, so we propose an efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies. Our variable splitting scheme, when combined with the AL framework and alternating minimization, leads to simple linear systems that can be solved non-iteratively using FFTs, eliminating the need for more expensive CG-type solvers. The proposed method can also efficiently tackle a variety of convex regularizers including edge-preserving (e.g., total-variation) and sparsity promoting (e.g., l1 norm) regularizers. Simulation results show fast convergence of the proposed method, along with improved image quality at the boundaries where the circulant model is inaccurate. PMID:23372080

A New Variational Approach for Multiplicative Noise and Blur Removal

PubMed Central

Ullah, Asmat; Chen, Wen; Khan, Mushtaq Ahmad; Sun, HongGuang

2017-01-01

This paper proposes a new variational model for joint multiplicative denoising and deblurring. It combines a total generalized variation filter (which has been proved to be able to reduce the blocky-effects by being aware of high-order smoothness) and shearlet transform (that effectively preserves anisotropic image features such as sharp edges, curves and so on). The new model takes the advantage of both regularizers since it is able to minimize the staircase effects while preserving sharp edges, textures and other fine image details. The existence and uniqueness of a solution to the proposed variational model is also discussed. The resulting energy functional is then solved by using alternating direction method of multipliers. Numerical experiments showing that the proposed model achieves satisfactory restoration results, both visually and quantitatively in handling the blur (motion, Gaussian, disk, and Moffat) and multiplicative noise (Gaussian, Gamma, or Rayleigh) reduction. A comparison with other recent methods in this field is provided as well. The proposed model can also be applied for restoring both single and multi-channel images contaminated with multiplicative noise, and permit cross-channel blurs when the underlying image has more than one channel. Numerical tests on color images are conducted to demonstrate the effectiveness of the proposed model. PMID:28141802

Mathematical filtering minimizes metallic halation of titanium implants in MicroCT images.

PubMed

Ha, Jee; Osher, Stanley J; Nishimura, Ichiro

2013-01-01

Microcomputed tomography (MicroCT) images containing titanium implant suffer from x-rays scattering, artifact and the implant surface is critically affected by metallic halation. To improve the metallic halation artifact, a nonlinear Total Variation denoising algorithm such as Split Bregman algorithm was applied to the digital data set of MicroCT images. This study demonstrated that the use of a mathematical filter could successfully reduce metallic halation, facilitating the osseointegration evaluation at the bone implant interface in the reconstructed images.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2010-09-01

regularization seeks the minimum- norm , least squares solution for phase retrieval. The retrieval result with Tikhonov regularization is still unsatisfactory...of norm , that can effectively reflect the accuracy of the retrieved data as an image, if ‖δ Ik+1−δ Ik‖ is less than a predefined threshold value β...pointed out that the proper norm for images is the total variation (TV) norm , which is the L1 norm of the gradient of the image function, and not the

Total variation based image deconvolution for extended depth-of-field microscopy images

NASA Astrophysics Data System (ADS)

Hausser, F.; Beckers, I.; Gierlak, M.; Kahraman, O.

2015-03-01

One approach for a detailed understanding of dynamical cellular processes during drug delivery is the use of functionalized biocompatible nanoparticles and fluorescent markers. An appropriate imaging system has to detect these moving particles so as whole cell volumes in real time with high lateral resolution in a range of a few 100 nm. In a previous study Extended depth-of-field microscopy (EDF-microscopy) has been applied to fluorescent beads and tradiscantia stamen hair cells and the concept of real-time imaging has been proved in different microscopic modes. In principle a phase retardation system like a programmable space light modulator or a static waveplate is incorporated in the light path and modulates the wavefront of light. Hence the focal ellipsoid is smeared out and images seem to be blurred in a first step. An image restoration by deconvolution using the known point-spread-function (PSF) of the optical system is necessary to achieve sharp microscopic images of an extended depth-of-field. This work is focused on the investigation and optimization of deconvolution algorithms to solve this restoration problem satisfactorily. This inverse problem is challenging due to presence of Poisson distributed noise and Gaussian noise, and since the PSF used for deconvolution exactly fits in just one plane within the object. We use non-linear Total Variation based image restoration techniques, where different types of noise can be treated properly. Various algorithms are evaluated for artificially generated 3D images as well as for fluorescence measurements of BPAE cells.

Low-dose cerebral perfusion computed tomography image restoration via low-rank and total variation regularizations

PubMed Central

Niu, Shanzhou; Zhang, Shanli; Huang, Jing; Bian, Zhaoying; Chen, Wufan; Yu, Gaohang; Liang, Zhengrong; Ma, Jianhua

2016-01-01

Cerebral perfusion x-ray computed tomography (PCT) is an important functional imaging modality for evaluating cerebrovascular diseases and has been widely used in clinics over the past decades. However, due to the protocol of PCT imaging with repeated dynamic sequential scans, the associative radiation dose unavoidably increases as compared with that used in conventional CT examinations. Minimizing the radiation exposure in PCT examination is a major task in the CT field. In this paper, considering the rich similarity redundancy information among enhanced sequential PCT images, we propose a low-dose PCT image restoration model by incorporating the low-rank and sparse matrix characteristic of sequential PCT images. Specifically, the sequential PCT images were first stacked into a matrix (i.e., low-rank matrix), and then a non-convex spectral norm/regularization and a spatio-temporal total variation norm/regularization were then built on the low-rank matrix to describe the low rank and sparsity of the sequential PCT images, respectively. Subsequently, an improved split Bregman method was adopted to minimize the associative objective function with a reasonable convergence rate. Both qualitative and quantitative studies were conducted using a digital phantom and clinical cerebral PCT datasets to evaluate the present method. Experimental results show that the presented method can achieve images with several noticeable advantages over the existing methods in terms of noise reduction and universal quality index. More importantly, the present method can produce more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps. PMID:27440948

Convex composite wavelet frame and total variation-based image deblurring using nonconvex penalty functions

NASA Astrophysics Data System (ADS)

Shen, Zhengwei; Cheng, Lishuang

2017-09-01

Total variation (TV)-based image deblurring method can bring on staircase artifacts in the homogenous region of the latent images recovered from the degraded images while a wavelet/frame-based image deblurring method will lead to spurious noise spikes and pseudo-Gibbs artifacts in the vicinity of discontinuities of the latent images. To suppress these artifacts efficiently, we propose a nonconvex composite wavelet/frame and TV-based image deblurring model. In this model, the wavelet/frame and the TV-based methods may complement each other, which are verified by theoretical analysis and experimental results. To further improve the quality of the latent images, nonconvex penalty function is used to be the regularization terms of the model, which may induce a stronger sparse solution and will more accurately estimate the relative large gradient or wavelet/frame coefficients of the latent images. In addition, by choosing a suitable parameter to the nonconvex penalty function, the subproblem that splits by the alternative direction method of multipliers algorithm from the proposed model can be guaranteed to be a convex optimization problem; hence, each subproblem can converge to a global optimum. The mean doubly augmented Lagrangian and the isotropic split Bregman algorithms are used to solve these convex subproblems where the designed proximal operator is used to reduce the computational complexity of the algorithms. Extensive numerical experiments indicate that the proposed model and algorithms are comparable to other state-of-the-art model and methods.

Global Electric Circuit Implications of Total Current Measurements over Electrified Clouds

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

2009-01-01

We determined total conduction (Wilson) currents and flash rates for 850 overflights of electrified clouds spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative Wilson currents. We combined these individual storm overflight statistics with global diurnal lightning variation data from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to estimate the thunderstorm and electrified shower cloud contributions to the diurnal variation in the global electric circuit. The contributions to the global electric circuit from lightning producing clouds are estimated by taking the mean current per flash derived from the overflight data for land and ocean overflights and combining it with the global lightning rates (for land and ocean) and their diurnal variation derived from the LIS/OTD data. We estimate the contribution of non-lightning producing electrified clouds by assuming several different diurnal variations and total non-electrified storm counts to produce estimates of the total storm currents (lightning and non-lightning producing storms). The storm counts and diurnal variations are constrained so that the resultant total current diurnal variation equals the diurnal variation in the fair weather electric field (+/-15%). These assumptions, combined with the airborne and satellite data, suggest that the total mean current in the global electric circuit ranges from 2.0 to 2.7 kA, which is greater than estimates made by others using other methods.

A spatially adaptive total variation regularization method for electrical resistance tomography

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2015-12-01

The total variation (TV) regularization method has been used to solve the ill-posed inverse problem of electrical resistance tomography (ERT), owing to its good ability to preserve edges. However, the quality of the reconstructed images, especially in the flat region, is often degraded by noise. To optimize the regularization term and the regularization factor according to the spatial feature and to improve the resolution of reconstructed images, a spatially adaptive total variation (SATV) regularization method is proposed. A kind of effective spatial feature indicator named difference curvature is used to identify which region is a flat or edge region. According to different spatial features, the SATV regularization method can automatically adjust both the regularization term and regularization factor. At edge regions, the regularization term is approximate to the TV functional to preserve the edges; in flat regions, it is approximate to the first-order Tikhonov (FOT) functional to make the solution stable. Meanwhile, the adaptive regularization factor determined by the spatial feature is used to constrain the regularization strength of the SATV regularization method for different regions. Besides, a numerical scheme is adopted for the implementation of the second derivatives of difference curvature to improve the numerical stability. Several reconstruction image metrics are used to quantitatively evaluate the performance of the reconstructed results. Both simulation and experimental results indicate that, compared with the TV (mean relative error 0.288, mean correlation coefficient 0.627) and FOT (mean relative error 0.295, mean correlation coefficient 0.638) regularization methods, the proposed SATV (mean relative error 0.259, mean correlation coefficient 0.738) regularization method can endure a relatively high level of noise and improve the resolution of reconstructed images.

Superresolution Interferometric Imaging with Sparse Modeling Using Total Squared Variation: Application to Imaging the Black Hole Shadow

NASA Astrophysics Data System (ADS)

Kuramochi, Kazuki; Akiyama, Kazunori; Ikeda, Shiro; Tazaki, Fumie; Fish, Vincent L.; Pu, Hung-Yi; Asada, Keiichi; Honma, Mareki

2018-05-01

We propose a new imaging technique for interferometry using sparse modeling, utilizing two regularization terms: the ℓ 1-norm and a new function named total squared variation (TSV) of the brightness distribution. First, we demonstrate that our technique may achieve a superresolution of ∼30% compared with the traditional CLEAN beam size using synthetic observations of two point sources. Second, we present simulated observations of three physically motivated static models of Sgr A* with the Event Horizon Telescope (EHT) to show the performance of proposed techniques in greater detail. Remarkably, in both the image and gradient domains, the optimal beam size minimizing root-mean-squared errors is ≲10% of the traditional CLEAN beam size for ℓ 1+TSV regularization, and non-convolved reconstructed images have smaller errors than beam-convolved reconstructed images. This indicates that TSV is well matched to the expected physical properties of the astronomical images and the traditional post-processing technique of Gaussian convolution in interferometric imaging may not be required. We also propose a feature-extraction method to detect circular features from the image of a black hole shadow and use it to evaluate the performance of the image reconstruction. With this method and reconstructed images, the EHT can constrain the radius of the black hole shadow with an accuracy of ∼10%–20% in present simulations for Sgr A*, suggesting that the EHT would be able to provide useful independent measurements of the mass of the supermassive black holes in Sgr A* and also another primary target, M87.

Observations of Fe XIV Line Intensity Variations in the Solar Corona During the 21 August 2017 Solar Eclipse

NASA Astrophysics Data System (ADS)

Johnson, Payton; Ladd, Edwin

2018-01-01

We present time- and spatially-resolved observations of the inner solar corona in the 5303 Å line of Fe XIV, taken during the 21 August 2017 solar eclipse from a field observing site in Crossville, TN. These observations are used to characterize the intensity variations in this coronal emission line, and to compare with oscillation predictions from models for heating the corona by magnetic wave dissipation.The observations were taken with two Explore Scientific ED 102CF 102 mm aperture triplet apochromatic refractors. One system used a DayStar custom-built 5 Å FWHM filter centered on the Fe XIV coronal spectral line and an Atik Titan camera for image collection. The setup produced images with a pixel size of 2.15 arcseconds (~1.5 Mm at the distance to the Sun), and a field of view of 1420 x 1060 arcseconds, covering approximately 20% of the entire solar limb centered near the emerging sunspot complex AR 2672. We obtained images with an exposure time of 0.22 seconds and a frame rate of 2.36 Hz, for a total of 361 images during totality.An identical, co-aligned telescope/camera system observed the same portion of the solar corona, but with a 100 Å FWHM Baader Planetarium solar continuum filter centered on a wavelength of 5400 Å. Images with an exposure time of 0.01 seconds were obtained with a frame rate of 4.05 Hz. These simultaneous observations are used as a control to monitor brightness variations not related to coronal line oscillations.

Adaptive-weighted Total Variation Minimization for Sparse Data toward Low-dose X-ray Computed Tomography Image Reconstruction

PubMed Central

Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong

2012-01-01

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, a piecewise-smooth X-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing noticeable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously-reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several noticeable gains, in terms of noise-resolution tradeoff plots and full width at half maximum values, as compared to the corresponding conventional TV-POCS algorithm. PMID:23154621

Adaptive-weighted total variation minimization for sparse data toward low-dose x-ray computed tomography image reconstruction.

PubMed

Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong

2012-12-07

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, piecewise-smooth x-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing notable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several notable gains, in terms of noise-resolution tradeoff plots and full-width at half-maximum values, as compared to the corresponding conventional TV-POCS algorithm.

Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced structure tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Han, Ce; Gan, Guanghui; Deng, Zhenxiang; Zhou, Yongqiang; Yi, Jinling; Zheng, Xiaomin; Xie, Congying; Jin, Xiance

2017-04-01

Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as ‘PWLS-ndiSTV’. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation.

Edge guided image reconstruction in linear scan CT by weighted alternating direction TV minimization.

PubMed

Cai, Ailong; Wang, Linyuan; Zhang, Hanming; Yan, Bin; Li, Lei; Xi, Xiaoqi; Li, Jianxin

2014-01-01

Linear scan computed tomography (CT) is a promising imaging configuration with high scanning efficiency while the data set is under-sampled and angularly limited for which high quality image reconstruction is challenging. In this work, an edge guided total variation minimization reconstruction (EGTVM) algorithm is developed in dealing with this problem. The proposed method is modeled on the combination of total variation (TV) regularization and iterative edge detection strategy. In the proposed method, the edge weights of intermediate reconstructions are incorporated into the TV objective function. The optimization is efficiently solved by applying alternating direction method of multipliers. A prudential and conservative edge detection strategy proposed in this paper can obtain the true edges while restricting the errors within an acceptable degree. Based on the comparison on both simulation studies and real CT data set reconstructions, EGTVM provides comparable or even better quality compared to the non-edge guided reconstruction and adaptive steepest descent-projection onto convex sets method. With the utilization of weighted alternating direction TV minimization and edge detection, EGTVM achieves fast and robust convergence and reconstructs high quality image when applied in linear scan CT with under-sampled data set.

Total variation superiorized conjugate gradient method for image reconstruction

NASA Astrophysics Data System (ADS)

Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.

2018-03-01

The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.

Stability, Visibility, and Histologic Analysis of a New Implanted Fiducial for Use as a Kilovoltage Radiographic or Radioactive Marker for Patient Positioning and Monitoring in Radiotherapy

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

Neustadter, David, E-mail: david.n@navotek.co; Tune, Michal; Zaretsky, Asaph

Purpose: To analyze the stability, visibility, and histology of a novel implantable soft-tissue marker (nonradioactive and radioactive) implanted in dog prostate and rabbit liver. Methods and Materials: A total of 34 nonradioactive and 35 radioactive markers were implanted in 1 dog and 16 rabbits. Stability was assessed by measuring intermarker distance (IMD) variation relative to IMDs at implantation. The IMDs were measured weekly for 4 months in the dog and biweekly for 2-4 weeks in the rabbits. Ultrasound and X-ray imaging were performed on all subjects. Computed tomography and MRI were performed on the dog. Histologic analysis was performed onmore » the rabbits after 2 or 4 months. Results: A total of 139 measurements had a mean ({+-} SD) absolute IMD variation of 1.1 {+-} 1.1 mm. These IMD variations are consistent with those reported in the literature as due to random organ deformation. The markers were visible, identifiable, and induced minimal or no image artifacts in all tested imaging modalities. Histologic analysis revealed that all pathologic changes were highly localized and not expected to be clinically significant. Conclusions: The markers were stable from the time of implantation. The markers were found to be compatible with all common medical imaging modalities. The markers caused no significant histologic effects. With respect to marker stability, visibility, and histologic analysis these implanted fiducials are appropriate for soft-tissue target positioning in radiotherapy.« less

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Total Variation Denoising and Support Localization of the Gradient

NASA Astrophysics Data System (ADS)

Chambolle, A.; Duval, V.; Peyré, G.; Poon, C.

2016-10-01

This paper describes the geometrical properties of the solutions to the total variation denoising method. A folklore statement is that this method is able to restore sharp edges, but at the same time, might introduce some staircasing (i.e. “fake” edges) in flat areas. Quite surprisingly, put aside numerical evidences, almost no theoretical result are available to backup these claims. The first contribution of this paper is a precise mathematical definition of the “extended support” (associated to the noise-free image) of TV denoising. This is intuitively the region which is unstable and will suffer from the staircasing effect. Our main result shows that the TV denoising method indeed restores a piece-wise constant image outside a small tube surrounding the extended support. Furthermore, the radius of this tube shrinks toward zero as the noise level vanishes and in some cases, an upper bound on the convergence rate is given.

Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Rossow, William B.

1991-01-01

The spatial and temporal stability of the distributions of satellite-measured visible and infrared radiances, caused by variations in clouds and surfaces, are investigated using bidimensional and monodimensional histograms and time-composite images. Similar analysis of the histograms of the original and time-composite images provides separation of the contributions of the space and time variations to the total variations. The variability of both the surfaces and clouds is found to be larger at scales much larger than the minimum resolved by satellite imagery. This study shows that the shapes of these histograms are distinctive characteristics of the different climate regimes and that particular attributes of these histograms can be related to several general, though not universal, properties of clouds and surface variations at regional and synoptic scales. There are also significant exceptions to these relationships in particular climate regimes. The characteristics of these radiance histograms provide a stable well defined descriptor of the cloud and surface properties.

Processing of multispectral thermal IR data for geologic applications

NASA Technical Reports Server (NTRS)

Kahle, A. B.; Madura, D. P.; Soha, J. M.

1979-01-01

Multispectral thermal IR data were acquired with a 24-channel scanner flown in an aircraft over the E. Tintic Utah mining district. These digital image data required extensive computer processing in order to put the information into a format useful for a geologic photointerpreter. Simple enhancement procedures were not sufficient to reveal the total information content because the data were highly correlated in all channels. The data were shown to be dominated by temperature variations across the scene, while the much more subtle spectral variations between the different rock types were of interest. The image processing techniques employed to analyze these data are described.

Measurement and characterization of RF nonuniformity over the heart at 3T using body coil transmission.

PubMed

Sung, Kyunghyun; Nayak, Krishna S

2008-03-01

To measure and characterize variations in the transmitted radio frequency (RF) (B1+) field in cardiac magnetic resonance imaging (MRI) at 3 Tesla. Knowledge of the B1+ field is necessary for the calibration of pulse sequences, image-based quantitation, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) optimization. A variation of the saturated double-angle method for cardiac B1+ mapping is described. A total of eight healthy volunteers and two cardiac patients were scanned using six parallel short-axis slices spanning the left ventricle (LV). B1+ profiles were analyzed to determine the amount of variation and dominant patterns of variation across the LV. A total of five to 10 measurements were obtained in each volunteer to determine an upper bound of measurement repeatability. The amount of flip angle variation was found to be 23% to 48% over the LV in mid-short-axis slices and 32% to 63% over the entire LV volume. The standard deviation (SD) of multiple flip angle measurements was <1.4 degrees over the LV in all subjects, indicating excellent repeatability of the proposed measurement method. The pattern of in-plane flip angle variation was found to be primarily unidirectional across the LV, with a residual variation of < or =3% in all subjects. The in-plane B1+ variation over the LV at 3T with body-coil transmission is on the order of 32% to 63% and is predominantly unidirectional in short-axis slices. Reproducible B1+ measurements over the whole heart can be obtained in a single breathhold of 16 heartbeats.

Dynamic re-weighted total variation technique and statistic Iterative reconstruction method for x-ray CT metal artifact reduction

NASA Astrophysics Data System (ADS)

Peng, Chengtao; Qiu, Bensheng; Zhang, Cheng; Ma, Changyu; Yuan, Gang; Li, Ming

2017-07-01

Over the years, the X-ray computed tomography (CT) has been successfully used in clinical diagnosis. However, when the body of the patient to be examined contains metal objects, the image reconstructed would be polluted by severe metal artifacts, which affect the doctor's diagnosis of disease. In this work, we proposed a dynamic re-weighted total variation (DRWTV) technique combined with the statistic iterative reconstruction (SIR) method to reduce the artifacts. The DRWTV method is based on the total variation (TV) and re-weighted total variation (RWTV) techniques, but it provides a sparser representation than TV and protects the tissue details better than RWTV. Besides, the DRWTV can suppress the artifacts and noise, and the SIR convergence speed is also accelerated. The performance of the algorithm is tested on both simulated phantom dataset and clinical dataset, which are the teeth phantom with two metal implants and the skull with three metal implants, respectively. The proposed algorithm (SIR-DRWTV) is compared with two traditional iterative algorithms, which are SIR and SIR constrained by RWTV regulation (SIR-RWTV). The results show that the proposed algorithm has the best performance in reducing metal artifacts and protecting tissue details.

Scattering images from autocorrelation functions of P-wave seismic velocity images: the case of Tenerife Island (Canary Islands, Spain)

NASA Astrophysics Data System (ADS)

García-Yeguas, A.; Sánchez-Alzola, A.; De Siena, L.; Prudencio, J.; Díaz-Moreno, A.; Ibáñez, J. M.

2018-03-01

We present a P-wave scattering image of the volcanic structures under Tenerife Island using the autocorrelation functions of P-wave vertical velocity fluctuations. We have applied a cluster analysis to total quality factor attenuation ( {Q}_t^{-1} ) and scattering quality factor attenuation ( {Q}_{PSc}^{-1} ) images to interpret the structures in terms of intrinsic and scattering attenuation variations on a 2D plane, corresponding to a depth of 2000 m, and check the robustness of the scattering imaging. The results show that scattering patterns are similar to total attenuation patterns in the south of the island. There are two main areas where patterns differ: at Cañadas-Teide-Pico Viejo Complex, high total attenuation and average-to-low scattering values are observed. We interpret the difference as induced by intrinsic attenuation. In the Santiago Ridge Zone (SRZ) region, high scattering values correspond to average total attenuation. In our interpretation, the anomaly is induced by an extended scatterer, geometrically related to the surficial traces of Garachico and El Chinyero historical eruptions and the area of highest seismic activity during the 2004-2008 seismic crises.

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

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

Wang, Jing; Gu, Xuejun

2013-10-15

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstructionmore » to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.« less

Bayesian Analysis of Hmi Images and Comparison to Tsi Variations and MWO Image Observables

NASA Astrophysics Data System (ADS)

Parker, D. G.; Ulrich, R. K.; Beck, J.; Tran, T. V.

2015-12-01

We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from June, 2010 to December, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables.The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment.Ulrich, R.K., Parker, D, Bertello, L. and Boyden, J. 2010, Solar Phys. , 261 , 11.

Classification of the venous architecture of the pineal gland by 7T MRI.

PubMed

Cho, Zang-Hee; Choi, Sang-Han; Chi, Je-Gun; Kim, Young-Bo

2011-10-01

Magnetic resonance imaging (MRI) at 7.0 Tesla (7T) can show many details of anatomical structures with unprecedented resolution and contrast. In this report, we describe for the first time the unexpected wide variation in pineal gland structure, as visualized by MR images obtained with 7T in a group of healthy young volunteers. A total of 34 volunteers (22 men and 12 women) were enrolled in the study. Their 7T MR images revealed such wide variations in pineal gland shape that it led us to attempt to classify the patterns seen in these pineal glands. Indeed, they were successfully correlated with a previous human cadaver study of venous structures by Tamaki et al., who classified the venous structures of the pineal gland into three categories. This is the first human in vivo pineal vein imaging study using 7T MRI. Pineal venous imaging may permit the early diagnosis of a pineal tumor. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Regional variation in thyroid cancer incidence in Belgium is associated with variation in thyroid imaging and thyroid disease management.

PubMed

Van den Bruel, Annick; Francart, Julie; Dubois, Cecile; Adam, Marielle; Vlayen, Joan; De Schutter, Harlinde; Stordeur, Sabine; Decallonne, Brigitte

2013-10-01

Increased thyroid cancer incidence is at least partially attributed to increased detection and shows considerable regional variation. We investigated whether regional variation in cancer incidence was associated with variations in thyroid disease management. We conducted a retrospective population-based cohort study that involved linking data from the Belgian Health Insurance database and the Belgian Cancer Registry to compare thyroid-related procedures between regions with high and low cancer incidence. Primary outcome measures were rates of TSH testing, imaging, fine-needle aspiration cytology (FNAC), and thyroid surgery. Secondary study outcomes were proportions of subjects with thyrotoxicosis and nodular disease treated with surgery, of subjects treated with surgery preceded by FNAC or with synchronous lymph node dissection, and of thyroid cancer diagnosis after surgery. The rate of TSH testing was similar, but the rate of imaging was lower in the low incidence region. The rate of FNAC was similar, whereas the rate of surgery was lower in the low incidence region (34 [95% CI 33; 35 ] vs 80 [95% CI 79; 81 ] per 100,000 person years in the high incidence region; P < .05). In the low incidence region compared to the high incidence region, surgery represented a less chosen therapy for euthyroid nodular disease patients (47% [95% CI 46; 48] vs 69% [95% CI 68; 70]; P < .05), proportionally more surgery was preceded by FNAC, more cancer was diagnosed after total thyroidectomy, and thyroid cancer patients had more preoperative FNAC and synchronous lymph node dissection. Regional variation in thyroid cancer incidence, most marked for low-risk disease, is associated with different usage of thyroid imaging and surgery, supporting variable detection as a key determinant in geographic variation.

Application of convolutional artificial neural networks to echocardiograms for differentiating congenital heart diseases in a pediatric population

NASA Astrophysics Data System (ADS)

Perrin, Douglas P.; Bueno, Alejandra; Rodriguez, Andrea; Marx, Gerald R.; del Nido, Pedro J.

2017-03-01

In this paper we describe a pilot study, where machine learning methods are used to differentiate between congenital heart diseases. Our approach was to apply convolutional neural networks (CNNs) to echocardiographic images from five different pediatric populations: normal, coarctation of the aorta (CoA), hypoplastic left heart syndrome (HLHS), transposition of the great arteries (TGA), and single ventricle (SV). We used a single network topology that was trained in a pairwise fashion in order to evaluate the potential to differentiate between patient populations. In total we used 59,151 echo frames drawn from 1,666 clinical sequences. Approximately 80% of the data was used for training, and the remainder for validation. Data was split at sequence boundaries to avoid having related images in the training and validation sets. While training was done with echo images/frames, evaluation was performed for both single frame discrimination as well as sequence discrimination (by majority voting). In total 10 networks were generated and evaluated. Unlike other domains where this network topology has been used, in ultrasound there is low visual variation between classes. This work shows the potential for CNNs to be applied to this low-variation domain of medical imaging for disease discrimination.

Space-based Coronagraphic Imaging Polarimetry of the TW Hydrae Disk: Shedding New Light on Self-shadowing Effects

NASA Astrophysics Data System (ADS)

Poteet, Charles A.; Chen, Christine H.; Hines, Dean C.; Perrin, Marshall D.; Debes, John H.; Pueyo, Laurent; Schneider, Glenn; Mazoyer, Johan; Kolokolova, Ludmilla

2018-06-01

We present Hubble Space Telescope Near-Infrared Camera and Multi-Object Spectrometer coronagraphic imaging polarimetry of the TW Hydrae protoplanetary disk. These observations simultaneously measure the total and polarized intensity, allowing direct measurement of the polarization fraction across the disk. In accord with the self-shadowing hypothesis recently proposed by Debes et al., we find that the total and polarized intensity of the disk exhibits strong azimuthal asymmetries at projected distances consistent with the previously reported bright and dark ring-shaped structures (∼45–99 au). The sinusoidal-like variations possess a maximum brightness at position angles near ∼268°–300° and are up to ∼28% stronger in total intensity. Furthermore, significant radial and azimuthal variations are also detected in the polarization fraction of the disk. In particular, we find that regions of lower polarization fraction are associated with annuli of increased surface brightness, suggesting that the relative proportion of multiple-to-single scattering is greater along the ring and gap structures. Moreover, we find strong (∼20%) azimuthal variation in the polarization fraction along the shadowed region of the disk. Further investigation reveals that the azimuthal variation is not the result of disk flaring effects, but is instead from a decrease in the relative contribution of multiple-to-single scattering within the shadowed region. Employing a two-layer scattering surface, we hypothesize that the diminished contribution in multiple scattering may result from shadowing by an inclined inner disk, which prevents direct stellar light from reaching the optically thick underlying surface component.

Joint MR-PET reconstruction using a multi-channel image regularizer

PubMed Central

Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

2016-01-01

While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy. PMID:28055827

Reducing the number of reconstructions needed for estimating channelized observer performance

NASA Astrophysics Data System (ADS)

Pineda, Angel R.; Miedema, Hope; Brenner, Melissa; Altaf, Sana

2018-03-01

A challenge for task-based optimization is the time required for each reconstructed image in applications where reconstructions are time consuming. Our goal is to reduce the number of reconstructions needed to estimate the area under the receiver operating characteristic curve (AUC) of the infinitely-trained optimal channelized linear observer. We explore the use of classifiers which either do not invert the channel covariance matrix or do feature selection. We also study the assumption that multiple low contrast signals in the same image of a non-linear reconstruction do not significantly change the estimate of the AUC. We compared the AUC of several classifiers (Hotelling, logistic regression, logistic regression using Firth bias reduction and the least absolute shrinkage and selection operator (LASSO)) with a small number of observations both for normal simulated data and images from a total variation reconstruction in magnetic resonance imaging (MRI). We used 10 Laguerre-Gauss channels and the Mann-Whitney estimator for AUC. For this data, our results show that at small sample sizes feature selection using the LASSO technique can decrease bias of the AUC estimation with increased variance and that for large sample sizes the difference between these classifiers is small. We also compared the use of multiple signals in a single reconstructed image to reduce the number of reconstructions in a total variation reconstruction for accelerated imaging in MRI. We found that AUC estimation using multiple low contrast signals in the same image resulted in similar AUC estimates as doing a single reconstruction per signal leading to a 13x reduction in the number of reconstructions needed.

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms.

PubMed

Tang, Jie; Nett, Brian E; Chen, Guang-Hong

2009-10-07

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

2016-03-01

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

Tropical Atlantic Dust and Smoke Aerosol Variations Related to the Madden-Julian Oscillation in MODIS and MISR Observations

NASA Technical Reports Server (NTRS)

Guo, Yanjuan; Tian, Baijun; Kahn, Ralph A.; Kalashnikova, Olga; Wong, Sun; Waliser, Duane E.

2013-01-01

In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) fine mode fraction and Multi-angle Imaging SpectroRadiometer (MISR) nonspherical fraction data are used to derive dust and smoke aerosol optical thickness (T(sub dust) and T(sub smoke)) over the tropical Atlantic in a complementary way: due to its wider swath, MODIS has 3-4 times greater sampling than MISR, but MISR dust discrimination is based on particle shape retrievals, whereas an empirical scheme is used for MODIS. MODIS and MISR show very similar dust and smoke winter climatologies. T(sub dust) is the dominant aerosol component over the tropical Atlantic, accounting for 40-70 percent of the total aerosol optical thickness (AOT), whereas T(sub smoke) is significantly smaller than T(sub dust). The consistency and high correlation between these climatologies and their daily variations lends confidence to their use for investigating the relative dust and smoke contributions to the total AOT variation associated with the Madden-Julian Oscillation (MJO). The temporal evolution and spatial patterns of the tdus anomalies associated with the MJO are consistent between MODIS and MISR: the magnitude of MJO-realted T(sub dust) anomalies is comparable to or even larger than that of the total T, while the T(sub smoke) anomaly represents about 15 percent compared to the total, which is quite different from their relative magnitudes to the total T on the climatological time scale. This suggests that dust and smoke are not influenced by the MJO in the same way. Based on correlation analysis, dust is strongly influenced by the MJO-modulated trade wind and precipitation anomalies, and can last as long as one MJO phase, whereas smoke is less affected.

WE-G-207-04: Non-Local Total-Variation (NLTV) Combined with Reweighted L1-Norm for Compressed Sensing Based CT Reconstruction

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

Kim, H; Chen, J; Pouliot, J

2015-06-15

Purpose: Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total-variation (TV) in L1-minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non-local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1-norm into it for more precise reconstruction. Methods: TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes moremore » global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1-min., designed for approximation to ideal L0-min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1-min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV. Results: In both cases, conventional and reweighted NLTV outperform TV min. in signal-to-noise ratio (SNR) and root-mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1-norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process. Conclusion: NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1-norm, while maintaining greater robustness to the noise effect than TV min.« less

Image superresolution by midfrequency sparse representation and total variation regularization

NASA Astrophysics Data System (ADS)

Xu, Jian; Chang, Zhiguo; Fan, Jiulun; Zhao, Xiaoqiang; Wu, Xiaomin; Wang, Yanzi

2015-01-01

Machine learning has provided many good tools for superresolution, whereas existing methods still need to be improved in many aspects. On one hand, the memory and time cost should be reduced. On the other hand, the step edges of the results obtained by the existing methods are not clear enough. We do the following work. First, we propose a method to extract the midfrequency features for dictionary learning. This method brings the benefit of a reduction of the memory and time complexity without sacrificing the performance. Second, we propose a detailed wiping-off total variation (DWO-TV) regularization model to reconstruct the sharp step edges. This model adds a novel constraint on the downsampling version of the high-resolution image to wipe off the details and artifacts and sharpen the step edges. Finally, step edges produced by the DWO-TV regularization and the details provided by learning are fused. Experimental results show that the proposed method offers a desirable compromise between low time and memory cost and the reconstruction quality.

Time-series MODIS image-based retrieval and distribution analysis of total suspended matter concentrations in Lake Taihu (China).

PubMed

Zhang, Yuchao; Lin, Shan; Liu, Jianping; Qian, Xin; Ge, Yi

2010-09-01

Although there has been considerable effort to use remotely sensed images to provide synoptic maps of total suspended matter (TSM), there are limited studies on universal TSM retrieval models. In this paper, we have developed a TSM retrieval model for Lake Taihu using TSM concentrations measured in situ and a time series of quasi-synchronous MODIS 250 m images from 2005. After simple geometric and atmospheric correction, we found a significant relationship (R = 0.8736, N = 166) between in situ measured TSM concentrations and MODIS band normalization difference of band 3 and band 1. From this, we retrieved TSM concentrations in eight regions of Lake Taihu in 2007 and analyzed the characteristic distribution and variation of TSM. Synoptic maps of model-estimated TSM of 2007 showed clear geographical and seasonal variations. TSM in Central Lake and Southern Lakeshore were consistently higher than in other regions, while TSM in East Taihu was generally the lowest among the regions throughout the year. Furthermore, a wide range of TSM concentrations appeared from winter to summer. TSM in winter could be several times that in summer.

Normal variation in sagittal spinal alignment parameters in adult patients: an EOS study using serial imaging.

PubMed

Hey, Hwee Weng Dennis; Tan, Kian Loong Melvin; Moorthy, Vikaesh; Lau, Eugene Tze-Chun; Lau, Leok-Lim; Liu, Gabriel; Wong, Hee-Kit

2018-03-01

To describe normal variations in sagittal spinal radiographic parameters over an interval period and establish physiological norms and guidelines for which these images should be interpreted. Data were prospectively collected from a continuous series of adult patients with first-episode mild low back pain presenting to a single institution. The sagittal parameters of two serial radiographic images taken 6-months apart were obtained with the EOS ® slot scanner. Measured parameters include CL, TK, TL, LL, PI, PT, SS, and end and apical vertebrae. Chi-squared test and Wilcoxon Signed Rank test were used to compare categorical and continuous variables, respectively. Sixty patients with a total of 120 whole-body sagittal X-rays were analysed. Mean age was 52.1 years (SD 21.2). Mean interval between the first and second X-rays was 126.2 days (SD 47.2). Small variations (< 1°) occur for all except PT (1.2°), CL (1.2°), and SVA (2.9 cm). Pelvic tilt showed significant difference between two images (p = 0.035). Subgroup analysis based on the time interval between X-rays, and between the first and second X-rays, did not show significant differences. Consistent findings were found for end and apical vertebrae of the thoracic and lumbar spine between the first and second X-rays for sagittal curve shapes. Radiographic sagittal parameters vary between serial images and reflect dynamism in spinal balancing. SVA and PT are predisposed to the widest variation. SVA has the largest variation between individuals of low pelvic tilt. Therefore, interpretation of these parameters should be patient specific and relies on trends rather than a one-time assessment.

Aerosol Optical Depth Retrievals from High-Resolution Commercial Satellite Imagery Over Areas of High Surface Reflectance

DTIC Science & Technology

2006-06-01

angle Imaging SpectroRadiometer MODIS Moderate Resolution Imaging Spectroradiometer NGA National Geospatial Intelligence Agency POI Principles of...and µ , the cosine of the viewing zenith angle and the effect of the variation of each of these variables on total optical depth. Extraterrestrial ...Eq. (34). Additionally, solar zenith angle also plays a role in the third term on the RHS of Eq. (34) by modifying extraterrestrial spectral solar

Common celiacomesenteric trunk: a computed tomography radiological study.

PubMed

Özgökçe, Mesut; Ayyıldız, Veysel Atilla; Oğul, Hayri; Arslan, Harun; Batur, Abdussamet; Yavuz, Alpaslan; İnce, Suat; Yüce, Deniz

2018-03-03

There is an increasing trend for administration of invasive radiological interventions, laparoscopic surgery, and transplantation procedures in recent years, and determining the vascular variations prior to these procedures is crucially important. Celiacomesenteric trunk (CMT) is among these variations. This study aimed to retrospectively evaluate this rare anomaly by computed tomography (CT). A total of 1000 CT angiography images were analyzed retrospectively, and the patients with mesenteric and celiac arteries arising from the abdominal aorta with a single root were identified. The level that CMT arose, and its branching patterns were determined individually for all patients. Ten patients (6 males and 4 females) with a mean age of 50.2 years (17-87 years) had CMT in CT images. The knowledge of variations in the CMT prior to vascular or laparoscopic interventions will contribute to early intervention in case of a complication, or to avoid from a potential damage.

High quality 4D cone-beam CT reconstruction using motion-compensated total variation regularization

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ma, Jianhua; Bian, Zhaoying; Zeng, Dong; Feng, Qianjin; Chen, Wufan

2017-04-01

Four dimensional cone-beam computed tomography (4D-CBCT) has great potential clinical value because of its ability to describe tumor and organ motion. But the challenge in 4D-CBCT reconstruction is the limited number of projections at each phase, which result in a reconstruction full of noise and streak artifacts with the conventional analytical algorithms. To address this problem, in this paper, we propose a motion compensated total variation regularization approach which tries to fully explore the temporal coherence of the spatial structures among the 4D-CBCT phases. In this work, we additionally conduct motion estimation/motion compensation (ME/MC) on the 4D-CBCT volume by using inter-phase deformation vector fields (DVFs). The motion compensated 4D-CBCT volume is then viewed as a pseudo-static sequence, of which the regularization function was imposed on. The regularization used in this work is the 3D spatial total variation minimization combined with 1D temporal total variation minimization. We subsequently construct a cost function for a reconstruction pass, and minimize this cost function using a variable splitting algorithm. Simulation and real patient data were used to evaluate the proposed algorithm. Results show that the introduction of additional temporal correlation along the phase direction can improve the 4D-CBCT image quality.

Short term variations in Jupiter's synchrotron radiation derived from VLA data analysis

NASA Astrophysics Data System (ADS)

Kita, H.; Misawa, H.; Tsuchiya, F.; Morioka, A.

2011-12-01

Jupiter's synchrotron radiation (JSR) is the emission from relativistic electrons in the strong magnetic field of the inner magnetosphere, and it is the most effective prove for remote sensing of Jupiter's radiation belt from the Earth. Although JSR has been thought to be stable for a long time, intensive observations for JSR have made after the collisions of comet P/SL9 to Jupiter in 1994, and these observations revealed short term variations of JSR on time scale of days to weeks. However, the mechanisms which cause the short term variations of total flux density and brightness distribution have not been revealed well. In order to reveal the mechanism of short term variations of JSR more precisely, we have made radio image analysis using the NRAO (National Radio Astronomy Observatory) archived data of the VLA [*]. Brice and McDonough [1973, Icarus] proposed a scenario for the short term variations: i.e, the solar UV/EUV heating for Jupiter's upper atmosphere drives neutral wind perturbations and then the induced dynamo electric field leads to enhancement of radial diffusion. It is also suggested that induced dynamo electric field produce dawn-dusk electric potential difference, which cause dawn-dusk asymmetry in electron spatial distribution and emission distribution. So far the following results have been indicated for the short term variations. Miyoshi et al. [1999, GRL] showed that a short term variation event at 2.3GHz is well correlate to solar UV/EUV flux variations. Tsuchiya et al. [2010, Adv. Geosci.] showed that JSR at 325MHz and 785MHz have short term variations. These JSR observations confirmed the existence of the short term variation which is caused by solar UV/EUV. However, the effect of solar UV/EUV heating on the spatial distribution of JSR has never been confirmed, so this study is the first attempt to confirm the solar UV/EUV effect on spatial distribution of JSR. We have selected the data observed from 28th Jan. to 5th Feb. 2000 at 327MHz. During the period, solar UV/EUV flux expected on Jupiter showed almost monotonic increase. It is expected from the analysis for the period that the enhancement of radial diffusion caused by solar UV/EUV heating produces total flux enhancement and dawn-dusk asymmetry of the emission distribution of the JSR. We can therefore examine the scenario by measuring total flux density and dawn-dusk peak emission ratio of JSR, and their relationships to the variation of solar UV/EUV activity. A preliminary result shows that total flux density variations occurred corresponding to the solar UV/EUV variations, but we couldn't find variations in the dawn-dusk asymmetry above the one rms level calculated from the background image. *The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.

SU-F-BRCD-09: Total Variation (TV) Based Fast Convergent Iterative CBCT Reconstruction with GPU Acceleration.

PubMed

Xu, Q; Yang, D; Tan, J; Anastasio, M

2012-06-01

To improve image quality and reduce imaging dose in CBCT for radiation therapy applications and to realize near real-time image reconstruction based on use of a fast convergence iterative algorithm and acceleration by multi-GPUs. An iterative image reconstruction that sought to minimize a weighted least squares cost function that employed total variation (TV) regularization was employed to mitigate projection data incompleteness and noise. To achieve rapid 3D image reconstruction (< 1 min), a highly optimized multiple-GPU implementation of the algorithm was developed. The convergence rate and reconstruction accuracy were evaluated using a modified 3D Shepp-Logan digital phantom and a Catphan-600 physical phantom. The reconstructed images were compared with the clinical FDK reconstruction results. Digital phantom studies showed that only 15 iterations and 60 iterations are needed to achieve algorithm convergence for 360-view and 60-view cases, respectively. The RMSE was reduced to 10-4 and 10-2, respectively, by using 15 iterations for each case. Our algorithm required 5.4s to complete one iteration for the 60-view case using one Tesla C2075 GPU. The few-view study indicated that our iterative algorithm has great potential to reduce the imaging dose and preserve good image quality. For the physical Catphan studies, the images obtained from the iterative algorithm possessed better spatial resolution and higher SNRs than those obtained from by use of a clinical FDK reconstruction algorithm. We have developed a fast convergence iterative algorithm for CBCT image reconstruction. The developed algorithm yielded images with better spatial resolution and higher SNR than those produced by a commercial FDK tool. In addition, from the few-view study, the iterative algorithm has shown great potential for significantly reducing imaging dose. We expect that the developed reconstruction approach will facilitate applications including IGART and patient daily CBCT-based treatment localization. © 2012 American Association of Physicists in Medicine.

A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

Investigation of iterative image reconstruction in low-dose breast CT

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Nonlocal variational model and filter algorithm to remove multiplicative noise

NASA Astrophysics Data System (ADS)

Chen, Dai-Qiang; Zhang, Hui; Cheng, Li-Zhi

2010-07-01

The nonlocal (NL) means filter proposed by Buades, Coll, and Morel (SIAM Multiscale Model. Simul. 4(2), 490-530, 2005), which makes full use of the redundancy information in images, has shown to be very efficient for image denoising with Gauss noise added. On the basis of the NL method and a striver to minimize the conditional mean-square error, we design a NL means filter to remove multiplicative noise, and combining the NL filter to regularity method, we propose a NL total variational (TV) model and present a fast iterated algorithm for it. Experiments demonstrate that our algorithm is better than TV method; it is superior in preserving small structures and textures and can obtain an improvement in peak signal-to-noise ratio.

System for verifiable CT radiation dose optimization based on image quality. part II. process control system.

PubMed

Larson, David B; Malarik, Remo J; Hall, Seth M; Podberesky, Daniel J

2013-10-01

To evaluate the effect of an automated computed tomography (CT) radiation dose optimization and process control system on the consistency of estimated image noise and size-specific dose estimates (SSDEs) of radiation in CT examinations of the chest, abdomen, and pelvis. This quality improvement project was determined not to constitute human subject research. An automated system was developed to analyze each examination immediately after completion, and to report individual axial-image-level and study-level summary data for patient size, image noise, and SSDE. The system acquired data for 4 months beginning October 1, 2011. Protocol changes were made by using parameters recommended by the prediction application, and 3 months of additional data were acquired. Preimplementation and postimplementation mean image noise and SSDE were compared by using unpaired t tests and F tests. Common-cause variation was differentiated from special-cause variation by using a statistical process control individual chart. A total of 817 CT examinations, 490 acquired before and 327 acquired after the initial protocol changes, were included in the study. Mean patient age and water-equivalent diameter were 12.0 years and 23.0 cm, respectively. The difference between actual and target noise increased from -1.4 to 0.3 HU (P < .01) and the standard deviation decreased from 3.9 to 1.6 HU (P < .01). Mean SSDE decreased from 11.9 to 7.5 mGy, a 37% reduction (P < .01). The process control chart identified several special causes of variation. Implementation of an automated CT radiation dose optimization system led to verifiable simultaneous decrease in image noise variation and SSDE. The automated nature of the system provides the opportunity for consistent CT radiation dose optimization on a broad scale. © RSNA, 2013.

An iterative shrinkage approach to total-variation image restoration.

PubMed

Michailovich, Oleg V

2011-05-01

The problem of restoration of digital images from their degraded measurements plays a central role in a multitude of practically important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modeled by an ill-conditioned operator. In such a situation, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some a priori information about its properties. Such a priori information--commonly referred to as simply priors--is essential for image restoration, rendering it stable and robust to noise. Moreover, using the priors makes the recovered images exhibit some plausible features of their original counterpart. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used in this case is defined by the Rudin-Osher-Fatemi model, which results in total variation (TV) based image restoration. The current arsenal of algorithms for TV-based image restoration is vast. In this present paper, a different approach to the solution of the problem is proposed based upon the method of iterative shrinkage (aka iterated thresholding). In the proposed method, the TV-based image restoration is performed through a recursive application of two simple procedures, viz. linear filtering and soft thresholding. Therefore, the method can be identified as belonging to the group of first-order algorithms which are efficient in dealing with images of relatively large sizes. Another valuable feature of the proposed method consists in its working directly with the TV functional, rather then with its smoothed versions. Moreover, the method provides a single solution for both isotropic and anisotropic definitions of the TV functional, thereby establishing a useful connection between the two formulae. Finally, a number of standard examples of image deblurring are demonstrated, in which the proposed method can provide restoration results of superior quality as compared to the case of sparse-wavelet deconvolution.

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review.

PubMed

Goez, Manuel Mauricio; Torres-Madroñero, Maria Constanza; Röthlisberger, Sarah; Delgado-Trejos, Edilson

2018-02-01

Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image. Copyright © 2018 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Production and hosting by Elsevier B.V. All rights reserved.

Bayesian Analysis Of HMI Solar Image Observables And Comparison To TSI Variations And MWO Image Observables

NASA Astrophysics Data System (ADS)

Parker, D. G.; Ulrich, R. K.; Beck, J.

2014-12-01

We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from May, 2010 to June, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables. The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment. Ulrich, R.K., Parker, D, Bertello, L. and Boyden, J. 2010, Solar Phys. , 261 , 11.

Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation

NASA Astrophysics Data System (ADS)

Han, Hao; Gao, Hao; Xing, Lei

2017-08-01

Excessive radiation exposure is still a major concern in 4D cone-beam computed tomography (4D-CBCT) due to its prolonged scanning duration. Radiation dose can be effectively reduced by either under-sampling the x-ray projections or reducing the x-ray flux. However, 4D-CBCT reconstruction under such low-dose protocols is prone to image artifacts and noise. In this work, we propose a novel joint regularization-based iterative reconstruction method for low-dose 4D-CBCT. To tackle the under-sampling problem, we employ spatiotemporal tensor framelet (STF) regularization to take advantage of the spatiotemporal coherence of the patient anatomy in 4D images. To simultaneously suppress the image noise caused by photon starvation, we also incorporate spatiotemporal nonlocal total variation (SNTV) regularization to make use of the nonlocal self-recursiveness of anatomical structures in the spatial and temporal domains. Under the joint STF-SNTV regularization, the proposed iterative reconstruction approach is evaluated first using two digital phantoms and then using physical experiment data in the low-dose context of both under-sampled and noisy projections. Compared with existing approaches via either STF or SNTV regularization alone, the presented hybrid approach achieves improved image quality, and is particularly effective for the reconstruction of low-dose 4D-CBCT data that are not only sparse but noisy.

A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

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

Hub, Martina; Thieke, Christian; Kessler, Marc L.

2012-04-15

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts formore » the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.« less

A stochastic approach to estimate the uncertainty of dose mapping caused by uncertainties in b-spline registration

PubMed Central

Hub, Martina; Thieke, Christian; Kessler, Marc L.; Karger, Christian P.

2012-01-01

Purpose: In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation. Methods: This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known. Results: The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected. Conclusions: An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well. PMID:22482640

Cardiac imaging with multi-sector data acquisition in volumetric CT: variation of effective temporal resolution and its potential clinical consequences

NASA Astrophysics Data System (ADS)

Tang, Xiangyang; Hsieh, Jiang; Taha, Basel H.; Vass, Melissa L.; Seamans, John L.; Okerlund, Darin R.

2009-02-01

With increasing longitudinal detector dimension available in diagnostic volumetric CT, step-and-shoot scan is becoming popular for cardiac imaging. In comparison to helical scan, step-and-shoot scan decouples patient table movement from cardiac gating/triggering, which facilitates the cardiac imaging via multi-sector data acquisition, as well as the administration of inter-cycle heart beat variation (arrhythmia) and radiation dose efficiency. Ideally, a multi-sector data acquisition can improve temporal resolution at a factor the same as the number of sectors (best scenario). In reality, however, the effective temporal resolution is jointly determined by gantry rotation speed and patient heart beat rate, which may significantly lower than the ideal or no improvement (worst scenario). Hence, it is clinically relevant to investigate the behavior of effective temporal resolution in cardiac imaging with multi-sector data acquisition. In this study, a 5-second cine scan of a porcine heart, which cascades 6 porcine cardiac cycles, is acquired. In addition to theoretical analysis and motion phantom study, the clinical consequences due to the effective temporal resolution variation are evaluated qualitative or quantitatively. By employing a 2-sector image reconstruction strategy, a total of 15 (the permutation of P(6, 2)) cases between the best and worst scenarios are studied, providing informative guidance for the design and optimization of CT cardiac imaging in volumetric CT with multi-sector data acquisition.

Estimation of Noise Properties for TV-regularized Image Reconstruction in Computed Tomography

PubMed Central

Sánchez, Adrian A.

2016-01-01

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR. PMID:26308968

Estimation of noise properties for TV-regularized image reconstruction in computed tomography.

PubMed

Sánchez, Adrian A

2015-09-21

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.

Estimation of noise properties for TV-regularized image reconstruction in computed tomography

NASA Astrophysics Data System (ADS)

Sánchez, Adrian A.

2015-09-01

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128× 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.

Magnetic Resonance-Based Electrical Property Tomography (MR- EPT) for Prostate Cancer Grade Imaging

DTIC Science & Technology

2014-07-01

TV 2D 5 10 15 2 4 6 8 10 12 14 i 5 10 15 2 4 6 8 10 12 14 Figure 10. Prostate-like gelatin phantom with one inclusion (5mm, play dough ...magnitude image (TSE) and reconstructions. 11 c) Multiple Inclusions Two 5 mm diameter inclusions ( play dough to provide significant conductivity...reconstruction, 2D inverse reconstruction with Total Variation, 3D inverse reconstruction 10 b) Single inclusion A single 5 mm diameter inclusion ( play

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

A sparsity-based simplification method for segmentation of spectral-domain optical coherence tomography images

NASA Astrophysics Data System (ADS)

Meiniel, William; Gan, Yu; Olivo-Marin, Jean-Christophe; Angelini, Elsa

2017-08-01

Optical coherence tomography (OCT) has emerged as a promising image modality to characterize biological tissues. With axio-lateral resolutions at the micron-level, OCT images provide detailed morphological information and enable applications such as optical biopsy and virtual histology for clinical needs. Image enhancement is typically required for morphological segmentation, to improve boundary localization, rather than enrich detailed tissue information. We propose to formulate image enhancement as an image simplification task such that tissue layers are smoothed while contours are enhanced. For this purpose, we exploit a Total Variation sparsity-based image reconstruction, inspired by the Compressed Sensing (CS) theory, but specialized for images with structures arranged in layers. We demonstrate the potential of our approach on OCT human heart and retinal images for layers segmentation. We also compare our image enhancement capabilities to the state-of-the-art denoising techniques.

Correction of aeroheating-induced intensity nonuniformity in infrared images

NASA Astrophysics Data System (ADS)

Liu, Li; Yan, Luxin; Zhao, Hui; Dai, Xiaobing; Zhang, Tianxu

2016-05-01

Aeroheating-induced intensity nonuniformity effects severely influence the effective performance of an infrared (IR) imaging system in high-speed flight. In this paper, we propose a new approach to the correction of intensity nonuniformity in IR images. The basic assumption is that the low-frequency intensity bias is additive and smoothly varying so that it can be modeled as a bivariate polynomial and estimated by using an isotropic total variation (TV) model. A half quadratic penalty method is applied to the isotropic form of TV discretization. And an alternating minimization algorithm is adopted for solving the optimization model. The experimental results of simulated and real aerothermal images show that the proposed correction method can effectively improve IR image quality.

SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

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

Lee, M; Woo, B; Kim, J

Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automaticallymore » from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.« less

Compressed sensing for ultrasound computed tomography.

PubMed

van Sloun, Ruud; Pandharipande, Ashish; Mischi, Massimo; Demi, Libertario

2015-06-01

Ultrasound computed tomography (UCT) allows the reconstruction of quantitative tissue characteristics, such as speed of sound, mass density, and attenuation. Lowering its acquisition time would be beneficial; however, this is fundamentally limited by the physical time of flight and the number of transmission events. In this letter, we propose a compressed sensing solution for UCT. The adopted measurement scheme is based on compressed acquisitions, with concurrent randomised transmissions in a circular array configuration. Reconstruction of the image is then obtained by combining the born iterative method and total variation minimization, thereby exploiting variation sparsity in the image domain. Evaluation using simulated UCT scattering measurements shows that the proposed transmission scheme performs better than uniform undersampling, and is able to reduce acquisition time by almost one order of magnitude, while maintaining high spatial resolution.

SU-C-207-05: A Comparative Study of Noise-Reduction Algorithms for Low-Dose Cone-Beam Computed Tomography

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

Mukherjee, S; Yao, W

2015-06-15

Purpose: To study different noise-reduction algorithms and to improve the image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low-dose cone-beam CT, the reconstructed image is contaminated with excessive quantum noise. In this study, three well-developed noise reduction algorithms namely, a) penalized weighted least square (PWLS) method, b) split-Bregman total variation (TV) method, and c) compressed sensing (CS) method were studied and applied to the images of a computer–simulated “Shepp-Logan” phantom and a physical CATPHAN phantom. Up to 20% additive Gaussian noise was added to the Shepp-Logan phantom. The CATPHAN phantom was scannedmore » by a Varian OBI system with 100 kVp, 4 ms and 20 mA. For comparing the performance of these algorithms, peak signal-to-noise ratio (PSNR) of the denoised images was computed. Results: The algorithms were shown to have the potential in reducing the noise level for low-dose CBCT images. For Shepp-Logan phantom, an improvement of PSNR of 2 dB, 3.1 dB and 4 dB was observed using PWLS, TV and CS respectively, while for CATPHAN, the improvement was 1.2 dB, 1.8 dB and 2.1 dB, respectively. Conclusion: Penalized weighted least square, total variation and compressed sensing methods were studied and compared for reducing the noise on a simulated phantom and a physical phantom scanned by low-dose CBCT. The techniques have shown promising results for noise reduction in terms of PSNR improvement. However, reducing the noise without compromising the smoothness and resolution of the image needs more extensive research.« less

Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

NASA Astrophysics Data System (ADS)

Wang, Tonghe; Zhu, Lei

2016-09-01

Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an average error of less than 1%.

Prospective study of cone-beam computed tomography image-guided radiotherapy for prone accelerated partial breast irradiation.

PubMed

Jozsef, Gabor; DeWyngaert, J Keith; Becker, Stewart J; Lymberis, Stella; Formenti, Silvia C

2011-10-01

To report setup variations during prone accelerated partial breast irradiation (APBI). New York University (NYU) 07-582 is an institutional review board-approved protocol of cone-beam computed tomography (CBCT) to deliver image-guided ABPI in the prone position. Eligible are postmenopausal women with pT1 breast cancer excised with negative margins and no nodal involvement. A total dose of 30 Gy in five daily fractions of 6 Gy are delivered to the planning target volume (the tumor cavity with 1.5-cm margin) by image-guided radiotherapy. Patients are set up prone, on a dedicated mattress, used for both simulation and treatment. After positioning with skin marks and lasers, CBCTs are performed and the images are registered to the planning CT. The resulting shifts (setup corrections) are recorded in the three principal directions and applied. Portal images are taken for verification. If they differ from the planning digital reconstructed radiographs, the patient is reset, and a new CBCT is taken. 70 consecutive patients have undergone a total of 343 CBCTs: 7 patients had four of five planned CBCTs performed. Seven CBCTs (2%) required to be repeated because of misalignment in the comparison between portal and digital reconstructed radiograph image after the first CBCT. The mean shifts and standard deviations in the anterior-posterior (AP), superior-inferior (SI), and medial-lateral (ML) directions were -0.19 (0.54), -0.02 (0.33), and -0.02 (0.43) cm, respectively. The average root mean squares of the daily shifts were 0.50 (0.28), 0.29 (0.17), and 0.38 (0.20). A conservative margin formula resulted in a recommended margin of 1.26, 0.73, 0.96 cm in the AP, SI, and ML directions. CBCTs confirmed that the NYU prone APBI setup and treatment technique are reproducible, with interfraction variation comparable to those reported for supine setup. The currently applied margin (1.5 cm) adequately compensates for the setup variation detected. Copyright © 2011 Elsevier Inc. All rights reserved.

Hessian-based norm regularization for image restoration with biomedical applications.

PubMed

Lefkimmiatis, Stamatios; Bourquard, Aurélien; Unser, Michael

2012-03-01

We present nonquadratic Hessian-based regularization methods that can be effectively used for image restoration problems in a variational framework. Motivated by the great success of the total-variation (TV) functional, we extend it to also include second-order differential operators. Specifically, we derive second-order regularizers that involve matrix norms of the Hessian operator. The definition of these functionals is based on an alternative interpretation of TV that relies on mixed norms of directional derivatives. We show that the resulting regularizers retain some of the most favorable properties of TV, i.e., convexity, homogeneity, rotation, and translation invariance, while dealing effectively with the staircase effect. We further develop an efficient minimization scheme for the corresponding objective functions. The proposed algorithm is of the iteratively reweighted least-square type and results from a majorization-minimization approach. It relies on a problem-specific preconditioned conjugate gradient method, which makes the overall minimization scheme very attractive since it can be applied effectively to large images in a reasonable computational time. We validate the overall proposed regularization framework through deblurring experiments under additive Gaussian noise on standard and biomedical images.

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, Guoqing

1992-01-01

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Cumulative Total India Freshwater Losses as Seen by NASA GRACE, 2002-15

NASA Image and Video Library

2015-12-08

Cumulative total freshwater losses in South Asia from 2002 to 2015 (in inches) observed by NASA's Gravity Recovery and Climate Experiment (GRACE) mission. Total water refers to all of the snow, surface water, soil water and groundwater combined. Groundwater depletion in India and Bangladesh continue to dominate total water losses in the region. The persistent drought along the Malaysian Peninsula is also apparent. Regions of increasing total water experience strong interannual variations in the Asian monsoon. Image updated from Rodell et al., 2009. Citation of Record: Rodell, M., I. Velicogna and J. Famiglietti, Satellite-based estimates of groundwater depletion in India, Nature, doi:10.1038/nature08238. http://photojournal.jpl.nasa.gov/catalog/PIA20206

A mixed-order nonlinear diffusion compressed sensing MR image reconstruction.

PubMed

Joy, Ajin; Paul, Joseph Suresh

2018-03-07

Avoid formation of staircase artifacts in nonlinear diffusion-based MR image reconstruction without compromising computational speed. Whereas second-order diffusion encourages the evolution of pixel neighborhood with uniform intensities, fourth-order diffusion considers smooth region to be not necessarily a uniform intensity region but also a planar region. Therefore, a controlled application of fourth-order diffusivity function is used to encourage second-order diffusion to reconstruct the smooth regions of the image as a plane rather than a group of blocks, while not being strong enough to introduce the undesirable speckle effect. Proposed method is compared with second- and fourth-order nonlinear diffusion reconstruction, total variation (TV), total generalized variation, and higher degree TV using in vivo data sets for different undersampling levels with application to dictionary learning-based reconstruction. It is observed that the proposed technique preserves sharp boundaries in the image while preventing the formation of staircase artifacts in the regions of smoothly varying pixel intensities. It also shows reduced error measures compared with second-order nonlinear diffusion reconstruction or TV and converges faster than TV-based methods. Because nonlinear diffusion is known to be an effective alternative to TV for edge-preserving reconstruction, the crucial aspect of staircase artifact removal is addressed. Reconstruction is found to be stable for the experimentally determined range of fourth-order regularization parameter, and therefore not does not introduce a parameter search. Hence, the computational simplicity of second-order diffusion is retained. © 2018 International Society for Magnetic Resonance in Medicine.

Iterative image-domain ring artifact removal in cone-beam CT

NASA Astrophysics Data System (ADS)

Liang, Xiaokun; Zhang, Zhicheng; Niu, Tianye; Yu, Shaode; Wu, Shibin; Li, Zhicheng; Zhang, Huailing; Xie, Yaoqin

2017-07-01

Ring artifacts in cone beam computed tomography (CBCT) images are caused by pixel gain variations using flat-panel detectors, and may lead to structured non-uniformities and deterioration of image quality. The purpose of this study is to propose a method of general ring artifact removal in CBCT images. This method is based on the polar coordinate system, where the ring artifacts manifest as stripe artifacts. Using relative total variation, the CBCT images are first smoothed to generate template images with fewer image details and ring artifacts. By subtracting the template images from the CBCT images, residual images with image details and ring artifacts are generated. As the ring artifact manifests as a stripe artifact in a polar coordinate system, the artifact image can be extracted by mean value from the residual image; the image details are generated by subtracting the artifact image from the residual image. Finally, the image details are compensated to the template image to generate the corrected images. The proposed framework is iterated until the differences in the extracted ring artifacts are minimized. We use a 3D Shepp-Logan phantom, Catphan©504 phantom, uniform acrylic cylinder, and images from a head patient to evaluate the proposed method. In the experiments using simulated data, the spatial uniformity is increased by 1.68 times and the structural similarity index is increased from 87.12% to 95.50% using the proposed method. In the experiment using clinical data, our method shows high efficiency in ring artifact removal while preserving the image structure and detail. The iterative approach we propose for ring artifact removal in cone-beam CT is practical and attractive for CBCT guided radiation therapy.

Multiscale properties of weighted total variation flow with applications to denoising and registration.

PubMed

Athavale, Prashant; Xu, Robert; Radau, Perry; Nachman, Adrian; Wright, Graham A

2015-07-01

Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions. Copyright © 2015. Published by Elsevier B.V.

A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT

NASA Astrophysics Data System (ADS)

Yan, Hao; Cervino, Laura; Jia, Xun; Jiang, Steve B.

2012-04-01

While compressed sensing (CS)-based algorithms have been developed for the low-dose cone beam CT (CBCT) reconstruction, a clear understanding of the relationship between the image quality and imaging dose at low-dose levels is needed. In this paper, we qualitatively investigate this subject in a comprehensive manner with extensive experimental and simulation studies. The basic idea is to plot both the image quality and imaging dose together as functions of the number of projections and mAs per projection over the whole clinically relevant range. On this basis, a clear understanding of the tradeoff between the image quality and imaging dose can be achieved and optimal low-dose CBCT scan protocols can be developed to maximize the dose reduction while minimizing the image quality loss for various imaging tasks in image-guided radiation therapy (IGRT). Main findings of this work include (1) under the CS-based reconstruction framework, image quality has little degradation over a large range of dose variation. Image quality degradation becomes evident when the imaging dose (approximated with the x-ray tube load) is decreased below 100 total mAs. An imaging dose lower than 40 total mAs leads to a dramatic image degradation, and thus should be used cautiously. Optimal low-dose CBCT scan protocols likely fall in the dose range of 40-100 total mAs, depending on the specific IGRT applications. (2) Among different scan protocols at a constant low-dose level, the super sparse-view reconstruction with the projection number less than 50 is the most challenging case, even with strong regularization. Better image quality can be acquired with low mAs protocols. (3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is around 72.8 total mAs or below and when the ROI is a low-contrast or high-resolution object. Based on our results, the optimal number of projections is around 90 to 120. (4) The clinically acceptable lowest imaging dose level is task dependent. In our study, 72.8 mAs is a safe dose level for visualizing low-contrast objects, while 12.2 total mAs is sufficient for detecting high-contrast objects of diameter greater than 3 mm.

Holistic and component plant phenotyping using temporal image sequence.

PubMed

Das Choudhury, Sruti; Bashyam, Srinidhi; Qiu, Yumou; Samal, Ashok; Awada, Tala

2018-01-01

Image-based plant phenotyping facilitates the extraction of traits noninvasively by analyzing large number of plants in a relatively short period of time. It has the potential to compute advanced phenotypes by considering the whole plant as a single object (holistic phenotypes) or as individual components, i.e., leaves and the stem (component phenotypes), to investigate the biophysical characteristics of the plants. The emergence timing, total number of leaves present at any point of time and the growth of individual leaves during vegetative stage life cycle of the maize plants are significant phenotypic expressions that best contribute to assess the plant vigor. However, image-based automated solution to this novel problem is yet to be explored. A set of new holistic and component phenotypes are introduced in this paper. To compute the component phenotypes, it is essential to detect the individual leaves and the stem. Thus, the paper introduces a novel method to reliably detect the leaves and the stem of the maize plants by analyzing 2-dimensional visible light image sequences captured from the side using a graph based approach. The total number of leaves are counted and the length of each leaf is measured for all images in the sequence to monitor leaf growth. To evaluate the performance of the proposed algorithm, we introduce University of Nebraska-Lincoln Component Plant Phenotyping Dataset (UNL-CPPD) and provide ground truth to facilitate new algorithm development and uniform comparison. The temporal variation of the component phenotypes regulated by genotypes and environment (i.e., greenhouse) are experimentally demonstrated for the maize plants on UNL-CPPD. Statistical models are applied to analyze the greenhouse environment impact and demonstrate the genetic regulation of the temporal variation of the holistic phenotypes on the public dataset called Panicoid Phenomap-1. The central contribution of the paper is a novel computer vision based algorithm for automated detection of individual leaves and the stem to compute new component phenotypes along with a public release of a benchmark dataset, i.e., UNL-CPPD. Detailed experimental analyses are performed to demonstrate the temporal variation of the holistic and component phenotypes in maize regulated by environment and genetic variation with a discussion on their significance in the context of plant science.

CATE 2016 Indonesia: Image Calibration, Intensity Calibration, and Drift Scan

NASA Astrophysics Data System (ADS)

Hare, H. S.; Kovac, S. A.; Jensen, L.; McKay, M. A.; Bosh, R.; Watson, Z.; Mitchell, A. M.; Penn, M. J.

2016-12-01

The citizen Continental America Telescopic Eclipse (CATE) experiment aims to provide equipment for 60 sites across the path of totality for the United States August 21st, 2017 total solar eclipse. The opportunity to gather ninety minutes of continuous images of the solar corona is unmatched by any other previous eclipse event. In March of 2016, 5 teams were sent to Indonesia to test CATE equipment and procedures on the March 9th, 2016 total solar eclipse. Also, a goal of the trip was practice and gathering data to use in testing data reduction methods. Of the five teams, four collected data. While in Indonesia, each group participated in community outreach in the location of their site. The 2016 eclipse allowed CATE to test the calibration techniques for the 2017 eclipse. Calibration dark current and flat field images were collected to remove variation across the cameras. Drift scan observations provided information to rotationally align the images from each site. These image's intensity values allowed for intensity calibration for each of the sites. A GPS at each site corrected for major computer errors in time measurement of images. Further refinement of these processes is required before the 2017 eclipse. This work was made possible through the NSO Training for the 2017 Citizen CATE Experiment funded by NASA (NASA NNX16AB92A).

Morphology and time variation of the Jovian Far UV aurora: Hubble Space Telescope observations

NASA Technical Reports Server (NTRS)

Gerard, Jean-Claude; Dols, Vincent; Paresce, Francesco; Prange, Renee

1993-01-01

High spatial resolution images of the north polar region of Jupiter have been obtained with the Faint Object Camera (FOC) on board the Hubble Space Telescope (HST). The first set of two images collected 87 min apart in February 1992 shows a bright (approximately or equal to 180 kR) emission superimposed on the background in rotation with the planet. Both Ly alpha images show common regions of enhanced emission but differences are also observed, possibly due to temporal variations. The second group of images obtained on June 23 and 26, 1992 isolates a spectral region near 153 nm dominated by the H2 Lyman bands and continuum. Both pictures exhibit a narrow arc structure fitting the L = 30 magnetotail field line footprint in the morning sector and a broader diffuse aurora in the afternoon. They show no indication of an evening twilight enhancement. Although the central meridian longitudes were similar, significant differences are seen in the two exposures, especially in the region of diffuse emission, and interpreted as signatures of temporal variations. The total power radiated in the H2 bands is approximately or equal to 2 x 10(exp 12) W, in agreement with previous UV spectrometer observations. The high local H2 emission rates (approximately 450 kR) imply a particle precipitation carrying an energy flux of about 5 x 10(exp -2) W/sq m.

Venus in motion: An animated video catalog of Pioneer Venus Orbiter Cloud Photopolarimeter images

NASA Technical Reports Server (NTRS)

Limaye, Sanjay S.

1992-01-01

Images of Venus acquired by the Pioneer Venus Orbiter Cloud Photopolarimeter (OCPP) during the 1982 opportunity have been utilized to create a short video summary of the data. The raw roll by roll images were first navigated using the spacecraft attitude and orbit information along with the CPP instrument pointing information. The limb darkening introduced by the variation of solar illumination geometry and the viewing angle was then modelled and removed. The images were then projected to simulate a view obtained from a fixed perspective with the observer at 10 Venus radii away and located above a Venus latitude of 30 degrees south and a longitude 60 degrees west. A total of 156 images from the 1982 opportunity have been animated at different dwell rates.

Photon-efficient super-resolution laser radar

NASA Astrophysics Data System (ADS)

Shin, Dongeek; Shapiro, Jeffrey H.; Goyal, Vivek K.

2017-08-01

The resolution achieved in photon-efficient active optical range imaging systems can be low due to non-idealities such as propagation through a diffuse scattering medium. We propose a constrained optimization-based frame- work to address extremes in scarcity of photons and blurring by a forward imaging kernel. We provide two algorithms for the resulting inverse problem: a greedy algorithm, inspired by sparse pursuit algorithms; and a convex optimization heuristic that incorporates image total variation regularization. We demonstrate that our framework outperforms existing deconvolution imaging techniques in terms of peak signal-to-noise ratio. Since our proposed method is able to super-resolve depth features using small numbers of photon counts, it can be useful for observing fine-scale phenomena in remote sensing through a scattering medium and through-the-skin biomedical imaging applications.

The Sun's Seismic Radius as Measured from the Fundamental Modes of Oscillations and Its Implications for the TSI Variations

NASA Astrophysics Data System (ADS)

Jain, Kiran; Tripathy, S. C.; Hill, F.

2018-05-01

In this Letter we explore the relationship between the solar seismic radius and total solar irradiance (TSI) during the last two solar cycles using the uninterrupted data from space-borne instruments on board the Solar and Heliospheric Observatory (SoHO) and the Solar Dynamics Observatory (SDO). The seismic radius is calculated from the fundamental (f) modes of solar oscillations utilizing the observations from SoHO/Michelson Doppler Imager (MDI) and SDO/Helioseismic and Magnetic Imager (HMI), and the TSI measurements are obtained from SoHO/VIRGO. Our study suggests that the major contribution to the TSI variation arises from the changes in magnetic field, while the radius variation plays a secondary role. We find that the solar irradiance increases with decreasing seismic radius; however, the anti-correlation between them is moderately weak. The estimated maximum change in seismic radius during a solar cycle is about 5 km, and is consistent in both solar cycles 23 and 24. Previous studies ;suggest a radius change at the surface of the order of 0.06 arcsec to explain the 0.1% variation in the TSI values during the solar cycle; however, our inferred seismic radius change is significantly smaller, hence the TSI variations cannot be fully explained by the temporal changes in seismic radius.

CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

PubMed

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-04-01

Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Moving object detection via low-rank total variation regularization

NASA Astrophysics Data System (ADS)

Wang, Pengcheng; Chen, Qian; Shao, Na

2016-09-01

Moving object detection is a challenging task in video surveillance. Recently proposed Robust Principal Component Analysis (RPCA) can recover the outlier patterns from the low-rank data under some mild conditions. However, the l-penalty in RPCA doesn't work well in moving object detection because the irrepresentable condition is often not satisfied. In this paper, a method based on total variation (TV) regularization scheme is proposed. In our model, image sequences captured with a static camera are highly related, which can be described using a low-rank matrix. Meanwhile, the low-rank matrix can absorb background motion, e.g. periodic and random perturbation. The foreground objects in the sequence are usually sparsely distributed and drifting continuously, and can be treated as group outliers from the highly-related background scenes. Instead of l-penalty, we exploit the total variation of the foreground. By minimizing the total variation energy, the outliers tend to collapse and finally converge to be the exact moving objects. The TV-penalty is superior to the l-penalty especially when the outlier is in the majority for some pixels, and our method can estimate the outlier explicitly with less bias but higher variance. To solve the problem, a joint optimization function is formulated and can be effectively solved through the inexact Augmented Lagrange Multiplier (ALM) method. We evaluate our method along with several state-of-the-art approaches in MATLAB. Both qualitative and quantitative results demonstrate that our proposed method works effectively on a large range of complex scenarios.

Accelerated Optical Projection Tomography Applied to In Vivo Imaging of Zebrafish

PubMed Central

Correia, Teresa; Yin, Jun; Ramel, Marie-Christine; Andrews, Natalie; Katan, Matilda; Bugeon, Laurence; Dallman, Margaret J.; McGinty, James; Frankel, Paul; French, Paul M. W.; Arridge, Simon

2015-01-01

Optical projection tomography (OPT) provides a non-invasive 3-D imaging modality that can be applied to longitudinal studies of live disease models, including in zebrafish. Current limitations include the requirement of a minimum number of angular projections for reconstruction of reasonable OPT images using filtered back projection (FBP), which is typically several hundred, leading to acquisition times of several minutes. It is highly desirable to decrease the number of required angular projections to decrease both the total acquisition time and the light dose to the sample. This is particularly important to enable longitudinal studies, which involve measurements of the same fish at different time points. In this work, we demonstrate that the use of an iterative algorithm to reconstruct sparsely sampled OPT data sets can provide useful 3-D images with 50 or fewer projections, thereby significantly decreasing the minimum acquisition time and light dose while maintaining image quality. A transgenic zebrafish embryo with fluorescent labelling of the vasculature was imaged to acquire densely sampled (800 projections) and under-sampled data sets of transmitted and fluorescence projection images. The under-sampled OPT data sets were reconstructed using an iterative total variation-based image reconstruction algorithm and compared against FBP reconstructions of the densely sampled data sets. To illustrate the potential for quantitative analysis following rapid OPT data acquisition, a Hessian-based method was applied to automatically segment the reconstructed images to select the vasculature network. Results showed that 3-D images of the zebrafish embryo and its vasculature of sufficient visual quality for quantitative analysis can be reconstructed using the iterative algorithm from only 32 projections—achieving up to 28 times improvement in imaging speed and leading to total acquisition times of a few seconds. PMID:26308086

Monitoring of hourly variations in coastal water turbidity using the geostationary ocean color imager (GOCI)

NASA Astrophysics Data System (ADS)

Choi, J.; Ryu, J.

2011-12-01

Temporal variations of suspended sediment concentration (SSC) in coastal water are the key to understanding the pattern of sediment movement within coastal area, in particular, such as in the west coast of the Korean Peninsula which is influenced by semi-diurnal tides. Remote sensing techniques can effectively monitor the distribution and dynamic changes in seawater properties across wide areas. Thus, SSC on the sea surface has been investigated using various types of satellite-based sensors. An advantage of Geostationary Ocean Color Imager (GOCI), the world's first geostationary ocean color observation satellite, over other ocean color satellite images is that it can obtain data every hour during the day and makes it possible to monitor the ocean in real time. In this study, hourly variations in turbidity on the coastal waters were estimated quantitatively using GOCI. Thirty three water samples were obtained on the coastal water surface in southern Gyeonggi Bay, located on the west coast of Korea. Water samples were filtered using 25-mm glass fiber filters (GF/F) for the estimation of SSC. The radiometric characteristics of the surface water, such as the total water-leaving radiance (LwT, W/m2/nm/sr), the sky radiance (Lsky, W/m2/nm/sr) and the downwelling irradiance, were also measured at each sampling location. In situ optical properties of the surface water were converted into remote sensing reflectance (Rrs) and then were used to develop an algorithm to generate SSC images in the study area. GOCI images acquired on the same day as the samples acquisition were used to generate the map of turbidity and to estimate the difference in SSC displayed in each image. The estimation of the time-series variation in SSC in a coastal, shallow-water area affected by tides was successfully achieved using GOCI data that had been acquired at hourly intervals during the daytime.

Limited data tomographic image reconstruction via dual formulation of total variation minimization

NASA Astrophysics Data System (ADS)

Jang, Kwang Eun; Sung, Younghun; Lee, Kangeui; Lee, Jongha; Cho, Seungryong

2011-03-01

The X-ray mammography is the primary imaging modality for breast cancer screening. For the dense breast, however, the mammogram is usually difficult to read due to tissue overlap problem caused by the superposition of normal tissues. The digital breast tomosynthesis (DBT) that measures several low dose projections over a limited angle range may be an alternative modality for breast imaging, since it allows the visualization of the cross-sectional information of breast. The DBT, however, may suffer from the aliasing artifact and the severe noise corruption. To overcome these problems, a total variation (TV) regularized statistical reconstruction algorithm is presented. Inspired by the dual formulation of TV minimization in denoising and deblurring problems, we derived a gradient-type algorithm based on statistical model of X-ray tomography. The objective function is comprised of a data fidelity term derived from the statistical model and a TV regularization term. The gradient of the objective function can be easily calculated using simple operations in terms of auxiliary variables. After a descending step, the data fidelity term is renewed in each iteration. Since the proposed algorithm can be implemented without sophisticated operations such as matrix inverse, it provides an efficient way to include the TV regularization in the statistical reconstruction method, which results in a fast and robust estimation for low dose projections over the limited angle range. Initial tests with an experimental DBT system confirmed our finding.

Neuronal correlates of the five factor model (FFM) of human personality: Multimodal imaging in a large healthy sample.

PubMed

Bjørnebekk, Astrid; Fjell, Anders M; Walhovd, Kristine B; Grydeland, Håkon; Torgersen, Svenn; Westlye, Lars T

2013-01-15

Advances in neuroimaging techniques have recently provided glimpse into the neurobiology of complex traits of human personality. Whereas some intriguing findings have connected aspects of personality to variations in brain morphology, the relations are complex and our current understanding is incomplete. Therefore, we aimed to provide a comprehensive investigation of brain-personality relations using a multimodal neuroimaging approach in a large sample comprising 265 healthy individuals. The NEO Personality Inventory was used to provide measures of core aspects of human personality, and imaging phenotypes included measures of total and regional brain volumes, regional cortical thickness and arealization, and diffusion tensor imaging indices of white matter (WM) microstructure. Neuroticism was the trait most clearly linked to brain structure. Higher neuroticism including facets reflecting anxiety, depression and vulnerability to stress was associated with smaller total brain volume, widespread decrease in WM microstructure, and smaller frontotemporal surface area. Higher scores on extraversion were associated with thinner inferior frontal gyrus, and conscientiousness was negatively associated with arealization of the temporoparietal junction. No reliable associations between brain structure and agreeableness and openness, respectively, were found. The results provide novel evidence of the associations between brain structure and variations in human personality, and corroborate previous findings of a consistent neuroanatomical basis of negative emotionality. Copyright © 2012 Elsevier Inc. All rights reserved.

Assessing cardiac function from total-variation-regularized 4D C-arm CT in the presence of angular undersampling

NASA Astrophysics Data System (ADS)

Taubmann, O.; Haase, V.; Lauritsch, G.; Zheng, Y.; Krings, G.; Hornegger, J.; Maier, A.

2017-04-01

Time-resolved tomographic cardiac imaging using an angiographic C-arm device may support clinicians during minimally invasive therapy by enabling a thorough analysis of the heart function directly in the catheter laboratory. However, clinically feasible acquisition protocols entail a highly challenging reconstruction problem which suffers from sparse angular sampling of the trajectory. Compressed sensing theory promises that useful images can be recovered despite massive undersampling by means of sparsity-based regularization. For a multitude of reasons—most notably the desired reduction of scan time, dose and contrast agent required—it is of great interest to know just how little data is actually sufficient for a certain task. In this work, we apply a convex optimization approach based on primal-dual splitting to 4D cardiac C-arm computed tomography. We examine how the quality of spatially and temporally total-variation-regularized reconstruction degrades when using as few as 6.9+/- 1.2 projection views per heart phase. First, feasible regularization weights are determined in a numerical phantom study, demonstrating the individual benefits of both regularizers. Secondly, a task-based evaluation is performed in eight clinical patients. Semi-automatic segmentation-based volume measurements of the left ventricular blood pool performed on strongly undersampled images show a correlation of close to 99% with measurements obtained from less sparsely sampled data.

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.

PubMed

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC.

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method

PubMed Central

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC. PMID:28005929

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

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

Zhang, Wenkun; Zhang, Hanming; Li, Lei

2016-08-15

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem,more » we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.« less

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

NASA Astrophysics Data System (ADS)

Zhang, Wenkun; Zhang, Hanming; Li, Lei; Wang, Linyuan; Cai, Ailong; Li, Zhongguo; Yan, Bin

2016-08-01

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.

Compressed sensing for rapid late gadolinium enhanced imaging of the left atrium: A preliminary study.

PubMed

Kamesh Iyer, Srikant; Tasdizen, Tolga; Burgon, Nathan; Kholmovski, Eugene; Marrouche, Nassir; Adluru, Ganesh; DiBella, Edward

2016-09-01

Current late gadolinium enhancement (LGE) imaging of left atrial (LA) scar or fibrosis is relatively slow and requires 5-15min to acquire an undersampled (R=1.7) 3D navigated dataset. The GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) based parallel imaging method is the current clinical standard for accelerating 3D LGE imaging of the LA and permits an acceleration factor ~R=1.7. Two compressed sensing (CS) methods have been developed to achieve higher acceleration factors: a patch based collaborative filtering technique tested with acceleration factor R~3, and a technique that uses a 3D radial stack-of-stars acquisition pattern (R~1.8) with a 3D total variation constraint. The long reconstruction time of these CS methods makes them unwieldy to use, especially the patch based collaborative filtering technique. In addition, the effect of CS techniques on the quantification of percentage of scar/fibrosis is not known. We sought to develop a practical compressed sensing method for imaging the LA at high acceleration factors. In order to develop a clinically viable method with short reconstruction time, a Split Bregman (SB) reconstruction method with 3D total variation (TV) constraints was developed and implemented. The method was tested on 8 atrial fibrillation patients (4 pre-ablation and 4 post-ablation datasets). Blur metric, normalized mean squared error and peak signal to noise ratio were used as metrics to analyze the quality of the reconstructed images, Quantification of the extent of LGE was performed on the undersampled images and compared with the fully sampled images. Quantification of scar from post-ablation datasets and quantification of fibrosis from pre-ablation datasets showed that acceleration factors up to R~3.5 gave good 3D LGE images of the LA wall, using a 3D TV constraint and constrained SB methods. This corresponds to reducing the scan time by half, compared to currently used GRAPPA methods. Reconstruction of 3D LGE images using the SB method was over 20 times faster than standard gradient descent methods. Copyright © 2016 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

We propose a hybrid metal artifact reduction (MAR) approach for computed tomography (CT) that is computationally more efficient than a fully iterative reconstruction method, but at the same time achieves superior image quality to the interpolation-based in-painting techniques. Our proposed MAR method, an image-based artifact subtraction approach, utilizes an intermediate prior image reconstructed via PDART to recover the background information underlying the high density objects. For comparison, prior images generated by total-variation minimization (TVM) algorithm, as a realization of fully iterative approach, were also utilized as intermediate images. From the simulation and real experimental results, it has been shown that PDART drastically accelerates the reconstruction to an acceptable quality of prior images. Incorporating PDART-reconstructed prior images in the proposed MAR scheme achieved higher quality images than those by a conventional in-painting method. Furthermore, the results were comparable to the fully iterative MAR that uses high-quality TVM prior images.

Accelerated high-resolution photoacoustic tomography via compressed sensing

NASA Astrophysics Data System (ADS)

Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward

2016-12-01

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.

Reconstruction of solar UV irradiance since 1974

NASA Astrophysics Data System (ADS)

Krivova, N. A.; Solanki, S. K.; Wenzler, T.; Podlipnik, B.

2009-09-01

Variations of the solar UV irradiance are an important driver of chemical and physical processes in the Earth's upper atmosphere and may also influence global climate. Here we reconstruct solar UV irradiance in the range 115-400 nm over the period 1974-2007 by making use of the recently developed empirical extension of the Spectral And Total Irradiance Reconstruction (SATIRE) models employing Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) data. The evolution of the solar photospheric magnetic flux, which is a central input to the model, is described by the magnetograms and continuum images recorded at the Kitt Peak National Solar Observatory between 1974 and 2003 and by the Michelson Doppler Imager instrument on SOHO since 1996. The reconstruction extends the available observational record by 1.5 solar cycles. The reconstructed Ly-α irradiance agrees well with the composite time series by Woods et al. (2000). The amplitude of the irradiance variations grows with decreasing wavelength and in the wavelength regions of special interest for studies of the Earth's climate (Ly-α and oxygen absorption continuum and bands between 130 and 350 nm) is 1-2 orders of magnitude stronger than in the visible or if integrated over all wavelengths (total solar irradiance).

Diurnal Variation of Tropical Ice Cloud Microphysics: Evidence from Global Precipitation Measurement Microwave Imager Polarimetric Measurements

NASA Astrophysics Data System (ADS)

Gong, Jie; Zeng, Xiping; Wu, Dong L.; Li, Xiaowen

2018-01-01

The diurnal variation of tropical ice clouds has been well observed and examined in terms of the occurring frequency and total mass but rarely from the viewpoint of ice microphysical parameters. It accounts for a large portion of uncertainties in evaluating ice clouds' role on global radiation and hydrological budgets. Owing to the advantage of precession orbit design and paired polarized observations at a high-frequency microwave band that is particularly sensitive to ice particle microphysical properties, 3 years of polarimetric difference (PD) measurements using the 166 GHz channel of Global Precipitation Measurement Microwave Imager (GPM-GMI) are compiled to reveal a strong diurnal cycle over tropical land (30°S-30°N) with peak amplitude varying up to 38%. Since the PD signal is dominantly determined by ice crystal size, shape, and orientation, the diurnal cycle observed by GMI can be used to infer changes in ice crystal properties. Moreover, PD change is found to lead the diurnal changes of ice cloud occurring frequency and total ice mass by about 2 h, which strongly implies that understanding ice microphysics is critical to predict, infer, and model ice cloud evolution and precipitation processes.

The assessment of facial variation in 4747 British school children.

PubMed

Toma, Arshed M; Zhurov, Alexei I; Playle, Rebecca; Marshall, David; Rosin, Paul L; Richmond, Stephen

2012-12-01

The aim of this study is to identify key components contributing to facial variation in a large population-based sample of 15.5-year-old children (2514 females and 2233 males). The subjects were recruited from the Avon Longitudinal Study of Parents and Children. Three-dimensional facial images were obtained for each subject using two high-resolution Konica Minolta laser scanners. Twenty-one reproducible facial landmarks were identified and their coordinates were recorded. The facial images were registered using Procrustes analysis. Principal component analysis was then employed to identify independent groups of correlated coordinates. For the total data set, 14 principal components (PCs) were identified which explained 82 per cent of the total variance, with the first three components accounting for 46 per cent of the variance. Similar results were obtained for males and females separately with only subtle gender differences in some PCs. Facial features may be treated as a multidimensional statistical continuum with respect to the PCs. The first three PCs characterize the face in terms of height, width, and prominence of the nose. The derived PCs may be useful to identify and classify faces according to a scale of normality.

Novel Fourier-based iterative reconstruction for sparse fan projection using alternating direction total variation minimization

NASA Astrophysics Data System (ADS)

Zhao, Jin; Han-Ming, Zhang; Bin, Yan; Lei, Li; Lin-Yuan, Wang; Ai-Long, Cai

2016-03-01

Sparse-view x-ray computed tomography (CT) imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform (NUFFT) is presented in this work along with advanced total variation (TV) regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively. Projected supported by the National High Technology Research and Development Program of China (Grant No. 2012AA011603) and the National Natural Science Foundation of China (Grant No. 61372172).

Deep learning with domain adaptation for accelerated projection-reconstruction MR.

PubMed

Han, Yoseob; Yoo, Jaejun; Kim, Hak Hee; Shin, Hee Jung; Sung, Kyunghyun; Ye, Jong Chul

2018-09-01

The radial k-space trajectory is a well-established sampling trajectory used in conjunction with magnetic resonance imaging. However, the radial k-space trajectory requires a large number of radial lines for high-resolution reconstruction. Increasing the number of radial lines causes longer acquisition time, making it more difficult for routine clinical use. On the other hand, if we reduce the number of radial lines, streaking artifact patterns are unavoidable. To solve this problem, we propose a novel deep learning approach with domain adaptation to restore high-resolution MR images from under-sampled k-space data. The proposed deep network removes the streaking artifacts from the artifact corrupted images. To address the situation given the limited available data, we propose a domain adaptation scheme that employs a pre-trained network using a large number of X-ray computed tomography (CT) or synthesized radial MR datasets, which is then fine-tuned with only a few radial MR datasets. The proposed method outperforms existing compressed sensing algorithms, such as the total variation and PR-FOCUSS methods. In addition, the calculation time is several orders of magnitude faster than the total variation and PR-FOCUSS methods. Moreover, we found that pre-training using CT or MR data from similar organ data is more important than pre-training using data from the same modality for different organ. We demonstrate the possibility of a domain-adaptation when only a limited amount of MR data is available. The proposed method surpasses the existing compressed sensing algorithms in terms of the image quality and computation time. © 2018 International Society for Magnetic Resonance in Medicine.

In vivo integrated photoacoustic and confocal microscopy of hemoglobin oxygen saturation and oxygen partial pressure.

PubMed

Wang, Yu; Hu, Song; Maslov, Konstantin; Zhang, Yu; Xia, Younan; Wang, Lihong V

2011-04-01

We developed dual-modality microscope integrating photoacoustic microscopy (PAM) and fluorescence confocal microscopy (FCM) to noninvasively image hemoglobin oxygen saturation (sO₂) and oxygen partial pressure (pO₂) in vivo in single blood vessels with high spatial resolution. While PAM measures sO₂ by imaging hemoglobin optical absorption at two wavelengths, FCM quantifies pO₂ using phosphorescence quenching. The variations of sO₂ and pO₂ values in multiple orders of vessel branches under hyperoxic (100% oxygen) and normoxic (21% oxygen) conditions correlate well with the oxygen-hemoglobin dissociation curve. In addition, the total concentration of hemoglobin is imaged by PAM at an isosbestic wavelength.

Development of image analysis software for quantification of viable cells in microchips.

PubMed

Georg, Maximilian; Fernández-Cabada, Tamara; Bourguignon, Natalia; Karp, Paola; Peñaherrera, Ana B; Helguera, Gustavo; Lerner, Betiana; Pérez, Maximiliano S; Mertelsmann, Roland

2018-01-01

Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way.

MRI and Additive Manufacturing of Nasal Alar Constructs for Patient-specific Reconstruction.

PubMed

Visscher, Dafydd O; van Eijnatten, Maureen; Liberton, Niels P T J; Wolff, Jan; Hofman, Mark B M; Helder, Marco N; Don Griot, J Peter W; Zuijlen, Paul P M van

2017-08-30

Surgical reconstruction of cartilaginous defects remains a major challenge. In the current study, we aimed to identify an imaging strategy for the development of patient-specific constructs that aid in the reconstruction of nasal deformities. Magnetic Resonance Imaging (MRI) was performed on a human cadaver head to find the optimal MRI sequence for nasal cartilage. This sequence was subsequently used on a volunteer. Images of both were assessed by three independent researchers to determine measurement error and total segmentation time. Three dimensionally (3D) reconstructed alar cartilage was then additively manufactured. Validity was assessed by comparing manually segmented MR images to the gold standard (micro-CT). Manual segmentation allowed delineation of the nasal cartilages. Inter- and intra-observer agreement was acceptable in the cadaver (coefficient of variation 4.6-12.5%), but less in the volunteer (coefficient of variation 0.6-21.9%). Segmentation times did not differ between observers (cadaver P = 0.36; volunteer P = 0.6). The lateral crus of the alar cartilage was consistently identified by all observers, whereas part of the medial crus was consistently missed. This study suggests that MRI is a feasible imaging modality for the development of 3D alar constructs for patient-specific reconstruction.

Efficient image enhancement using sparse source separation in the Retinex theory

NASA Astrophysics Data System (ADS)

Yoon, Jongsu; Choi, Jangwon; Choe, Yoonsik

2017-11-01

Color constancy is the feature of the human vision system (HVS) that ensures the relative constancy of the perceived color of objects under varying illumination conditions. The Retinex theory of machine vision systems is based on the HVS. Among Retinex algorithms, the physics-based algorithms are efficient; however, they generally do not satisfy the local characteristics of the original Retinex theory because they eliminate global illumination from their optimization. We apply the sparse source separation technique to the Retinex theory to present a physics-based algorithm that satisfies the locality characteristic of the original Retinex theory. Previous Retinex algorithms have limited use in image enhancement because the total variation Retinex results in an overly enhanced image and the sparse source separation Retinex cannot completely restore the original image. In contrast, our proposed method preserves the image edge and can very nearly replicate the original image without any special operation.

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring.

PubMed

Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi

2017-01-18

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.

Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients.

PubMed

Yue, Yong; Osipov, Arsen; Fraass, Benedick; Sandler, Howard; Zhang, Xiao; Nissen, Nicholas; Hendifar, Andrew; Tuli, Richard

2017-02-01

To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients. Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis. Median age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%). Locoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive RT.

Modeling and optimization of a time-resolved proton radiographic imaging system for proton cancer treatment

NASA Astrophysics Data System (ADS)

Han, Bin

This dissertation describes a research project to test the clinical utility of a time-resolved proton radiographic (TRPR) imaging system by performing comprehensive Monte Carlo simulations of a physical device coupled with realistic lung cancer patient anatomy defined by 4DCT for proton therapy. A time-resolved proton radiographic imaging system was modeled through Monte Carlo simulations. A particle-tracking feature was employed to evaluate the performance of the proton imaging system, especially in its ability to visualize and quantify proton range variations during respiration. The Most Likely Path (MLP) algorithm was developed to approximate the multiple Coulomb scattering paths of protons for the purpose of image reconstruction. Spatial resolution of ˜ 1 mm and range resolution of 1.3% of the total range were achieved using the MLP algorithm. Time-resolved proton radiographs of five patient cases were reconstructed to track tumor motion and to calculate water equivalent length variations. By comparing with direct 4DCT measurement, the accuracy of tumor tracking was found to be better than 2 mm in five patient cases. Utilizing tumor tracking information to reduce margins to the planning target volume, a gated treatment plan was compared with un-gated treatment plan. The equivalent uniform dose (EUD) and the normal tissue complication probability (NTCP) were used to quantify the gain in the quality of treatments. The EUD of the OARs was found to be reduced up to 11% and the corresponding NTCP of organs at risk (OARs) was found to be reduced up to 16.5%. These results suggest that, with image guidance by proton radiography, dose to OARs can be reduced and the corresponding NTCPs can be significantly reduced. The study concludes that the proton imaging system can accurately track the motion of the tumor and detect the WEL variations, leading to potential gains in using image-guided proton radiography for lung cancer treatments.

Temporal and spatial variations of sea surface temperature in the East China Sea

NASA Astrophysics Data System (ADS)

Tseng, Chente; Lin, Chiyuan; Chen, Shihchin; Shyu, Chungzen

2000-03-01

Sea surface temperature of the East China Sea (ECS) were analyzed using the NOAA/AVHRR SST images. These satellite images reveal surface features of ECS including mainly the Kuroshio Current, Kuroshio Branch Current, Taiwan Warm Current, China coastal water, Changjiang diluted water and Yellow Sea mixed cold water. The SST of ECS ranges from 27 to 29°C in summer; some cold eddies were found off northeast Taiwan and to the south of Changjiang mouth. SST anomalies at the center of these eddies were about 2-5°C. The strongest front usually occurs in May each year and its temperature gradient is about 5-6°C over a cross-shelf distance of 30 nautical miles. The Yellow Sea mixed cold water also provides a contrast from China Coastal waters shoreward of the 50 m isobath; cross-shore temperature gradient is about 6-8°C over 30 nautical miles. The Kuroshio intrudes into ECS preferably at two locations. The first is off northeast Taiwan; the subsurface water of Kuroshio is upwelled onto the shelf while the main current is deflected seaward. The second site is located at 31°N and 128°E, which is generally considered as the origin of the Tsushima Warm Current. More quantitatively, a 2-year time series of monthly SST images is examined using EOF analysis to determine the spatial and temporal variations in the northwestern portion of ECS. The first spatial EOF mode accounts for 47.4% of total spatial variance and reveals the Changjiang plume and coastal cold waters off China. The second and third EOF modes account for 16.4 and 9.6% of total variance, respectively, and their eigenvector images show the intrusion of Yellow Sea mixed cold waters and the China coastal water. The fourth EOF mode accounts for 5.4% of total variance and reveals cold eddies around Chusan Islands. The temporal variance EOF analysis is less revealing in this study area.

Accelerated echo planar J-resolved spectroscopic imaging in prostate cancer: a pilot validation of non-linear reconstruction using total variation and maximum entropy.

PubMed

Nagarajan, Rajakumar; Iqbal, Zohaib; Burns, Brian; Wilson, Neil E; Sarma, Manoj K; Margolis, Daniel A; Reiter, Robert E; Raman, Steven S; Thomas, M Albert

2015-11-01

The overlap of metabolites is a major limitation in one-dimensional (1D) spectral-based single-voxel MRS and multivoxel-based MRSI. By combining echo planar spectroscopic imaging (EPSI) with a two-dimensional (2D) J-resolved spectroscopic (JPRESS) sequence, 2D spectra can be recorded in multiple locations in a single slice of prostate using four-dimensional (4D) echo planar J-resolved spectroscopic imaging (EP-JRESI). The goal of the present work was to validate two different non-linear reconstruction methods independently using compressed sensing-based 4D EP-JRESI in prostate cancer (PCa): maximum entropy (MaxEnt) and total variation (TV). Twenty-two patients with PCa with a mean age of 63.8 years (range, 46-79 years) were investigated in this study. A 4D non-uniformly undersampled (NUS) EP-JRESI sequence was implemented on a Siemens 3-T MRI scanner. The NUS data were reconstructed using two non-linear reconstruction methods, namely MaxEnt and TV. Using both TV and MaxEnt reconstruction methods, the following observations were made in cancerous compared with non-cancerous locations: (i) higher mean (choline + creatine)/citrate metabolite ratios; (ii) increased levels of (choline + creatine)/spermine and (choline + creatine)/myo-inositol; and (iii) decreased levels of (choline + creatine)/(glutamine + glutamate). We have shown that it is possible to accelerate the 4D EP-JRESI sequence by four times and that the data can be reliably reconstructed using the TV and MaxEnt methods. The total acquisition duration was less than 13 min and we were able to detect and quantify several metabolites. Copyright © 2015 John Wiley & Sons, Ltd.

Optical observational programs at the Indian Institute of Astrophysics

NASA Astrophysics Data System (ADS)

Singh, Jagdev; Ravindra, B.

The Indian Institute of Astrophysics has been making optical observations of the sun for more than a century by taking images of the sun in continuum to study the photosphere, Ca-K line and H-alpha line in order to study the chromosphere by using the same instruments which are used to study the long term variations of the magnetic fields on the sun. The digitizers have been developed using uniform light sources, imaging optics without any vignetting in the required FOV and large format 4K×4K CCD cameras to digitize the data for scientific studies. At the Solar Tower Telescope we have performed very high resolution spectroscopic observations around Ca-K line to investigate the variations and delineate the contribution of various features to the solar cycle variations. Solar coronal studies have been done during the occurrence of total solar eclipses and with a coronagraph to study the coronal heating. Here we discuss the systematic temporal variations observed in the green and red emission profiles using high spectral and temporal observations during the 2006, 2009 and 2010 total solar eclipses. The TWIN telescope a new facility has been fabricated and installed at Kodaikanal observatory to continue the synoptic observations of the sun and a space-based coronagraph is also being designed and fabricated in collaboration with various laboratories of ISRO (LEOS, ISAC and SAC) and USO. In this article we present the summary of results of optical observational programs carried out at Kodaikanal Observatory and during the eclipse expeditions where authors have played a leading role. Furthermore, this review is not complete in all respects of all the observational programs carried out at the Kodaikanal observatory.

The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications

PubMed Central

Casadevall, Arturo; Fang, Ferric C.

2016-01-01

ABSTRACT Inaccurate data in scientific papers can result from honest error or intentional falsification. This study attempted to determine the percentage of published papers that contain inappropriate image duplication, a specific type of inaccurate data. The images from a total of 20,621 papers published in 40 scientific journals from 1995 to 2014 were visually screened. Overall, 3.8% of published papers contained problematic figures, with at least half exhibiting features suggestive of deliberate manipulation. The prevalence of papers with problematic images has risen markedly during the past decade. Additional papers written by authors of papers with problematic images had an increased likelihood of containing problematic images as well. As this analysis focused only on one type of data, it is likely that the actual prevalence of inaccurate data in the published literature is higher. The marked variation in the frequency of problematic images among journals suggests that journal practices, such as prepublication image screening, influence the quality of the scientific literature. PMID:27273827

Speckle reduction in optical coherence tomography using two-step iteration method (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wang, Xianghong; Liu, Xinyu; Wang, Nanshuo; Yu, Xiaojun; Bo, En; Chen, Si; Liu, Linbo

2017-02-01

Optical coherence tomography (OCT) provides high resolution and cross-sectional images of biological tissue and is widely used for diagnosis of ocular diseases. However, OCT images suffer from speckle noise, which typically considered as multiplicative noise in nature, reducing the image resolution and contrast. In this study, we propose a two-step iteration (TSI) method to suppress those noises. We first utilize augmented Lagrange method to recover a low-rank OCT image and remove additive Gaussian noise, and then employ the simple and efficient split Bregman method to solve the Total-Variation Denoising model. We validated such proposed method using images of swine, rabbit and human retina. Results demonstrate that our TSI method outperforms the other popular methods in achieving higher peak signal-to-noise ratio (PSNR) and structure similarity (SSIM) while preserving important structural details, such as tiny capillaries and thin layers in retinal OCT images. In addition, the results of our TSI method show clearer boundaries and maintains high image contrast, which facilitates better image interpretations and analyses.

Image-guided filtering for improving photoacoustic tomographic image reconstruction.

PubMed

Awasthi, Navchetan; Kalva, Sandeep Kumar; Pramanik, Manojit; Yalavarthy, Phaneendra K

2018-06-01

Several algorithms exist to solve the photoacoustic image reconstruction problem depending on the expected reconstructed image features. These reconstruction algorithms promote typically one feature, such as being smooth or sharp, in the output image. Combining these features using a guided filtering approach was attempted in this work, which requires an input and guiding image. This approach act as a postprocessing step to improve commonly used Tikhonov or total variational regularization method. The result obtained from linear backprojection was used as a guiding image to improve these results. Using both numerical and experimental phantom cases, it was shown that the proposed guided filtering approach was able to improve (as high as 11.23 dB) the signal-to-noise ratio of the reconstructed images with the added advantage being computationally efficient. This approach was compared with state-of-the-art basis pursuit deconvolution as well as standard denoising methods and shown to outperform them. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Spectral CT Reconstruction with Image Sparsity and Spectral Mean

PubMed Central

Zhang, Yi; Xi, Yan; Yang, Qingsong; Cong, Wenxiang; Zhou, Jiliu

2017-01-01

Photon-counting detectors can acquire x-ray intensity data in different energy bins. The signal to noise ratio of resultant raw data in each energy bin is generally low due to the narrow bin width and quantum noise. To address this problem, here we propose an image reconstruction approach for spectral CT to simultaneously reconstructs x-ray attenuation coefficients in all the energy bins. Because the measured spectral data are highly correlated among the x-ray energy bins, the intra-image sparsity and inter-image similarity are important prior acknowledge for image reconstruction. Inspired by this observation, the total variation (TV) and spectral mean (SM) measures are combined to improve the quality of reconstructed images. For this purpose, a linear mapping function is used to minimalize image differences between energy bins. The split Bregman technique is applied to perform image reconstruction. Our numerical and experimental results show that the proposed algorithms outperform competing iterative algorithms in this context. PMID:29034267

Partial differential equation transform — Variational formulation and Fourier analysis

PubMed Central

Wang, Yang; Wei, Guo-Wei; Yang, Siyang

2011-01-01

Nonlinear partial differential equation (PDE) models are established approaches for image/signal processing, data analysis and surface construction. Most previous geometric PDEs are utilized as low-pass filters which give rise to image trend information. In an earlier work, we introduced mode decomposition evolution equations (MoDEEs), which behave like high-pass filters and are able to systematically provide intrinsic mode functions (IMFs) of signals and images. Due to their tunable time-frequency localization and perfect reconstruction, the operation of MoDEEs is called a PDE transform. By appropriate selection of PDE transform parameters, we can tune IMFs into trends, edges, textures, noise etc., which can be further utilized in the secondary processing for various purposes. This work introduces the variational formulation, performs the Fourier analysis, and conducts biomedical and biological applications of the proposed PDE transform. The variational formulation offers an algorithm to incorporate two image functions and two sets of low-pass PDE operators in the total energy functional. Two low-pass PDE operators have different signs, leading to energy disparity, while a coupling term, acting as a relative fidelity of two image functions, is introduced to reduce the disparity of two energy components. We construct variational PDE transforms by using Euler-Lagrange equation and artificial time propagation. Fourier analysis of a simplified PDE transform is presented to shed light on the filter properties of high order PDE transforms. Such an analysis also offers insight on the parameter selection of the PDE transform. The proposed PDE transform algorithm is validated by numerous benchmark tests. In one selected challenging example, we illustrate the ability of PDE transform to separate two adjacent frequencies of sin(x) and sin(1.1x). Such an ability is due to PDE transform’s controllable frequency localization obtained by adjusting the order of PDEs. The frequency selection is achieved either by diffusion coefficients or by propagation time. Finally, we explore a large number of practical applications to further demonstrate the utility of proposed PDE transform. PMID:22207904

Performance evaluation of algebraic reconstruction technique (ART) for prototype chest digital tomosynthesis (CDT) system

NASA Astrophysics Data System (ADS)

Lee, Haenghwa; Choi, Sunghoon; Jo, Byungdu; Kim, Hyemi; Lee, Donghoon; Kim, Dohyeon; Choi, Seungyeon; Lee, Youngjin; Kim, Hee-Joung

2017-03-01

Chest digital tomosynthesis (CDT) is a new 3D imaging technique that can be expected to improve the detection of subtle lung disease over conventional chest radiography. Algorithm development for CDT system is challenging in that a limited number of low-dose projections are acquired over a limited angular range. To confirm the feasibility of algebraic reconstruction technique (ART) method under variations in key imaging parameters, quality metrics were conducted using LUNGMAN phantom included grand-glass opacity (GGO) tumor. Reconstructed images were acquired from the total 41 projection images over a total angular range of +/-20°. We evaluated contrast-to-noise ratio (CNR) and artifacts spread function (ASF) to investigate the effect of reconstruction parameters such as number of iterations, relaxation parameter and initial guess on image quality. We found that proper value of ART relaxation parameter could improve image quality from the same projection. In this study, proper value of relaxation parameters for zero-image (ZI) and back-projection (BP) initial guesses were 0.4 and 0.6, respectively. Also, the maximum CNR values and the minimum full width at half maximum (FWHM) of ASF were acquired in the reconstructed images after 20 iterations and 3 iterations, respectively. According to the results, BP initial guess for ART method could provide better image quality than ZI initial guess. In conclusion, ART method with proper reconstruction parameters could improve image quality due to the limited angular range in CDT system.

COMPUTED TOMOGRAPHIC APPEARANCE OF THE TEMPOROMANDIBULAR JOINT IN 1018 ASYMPTOMATIC HORSES: A MULTI-INSTITUTION STUDY.

PubMed

Carmalt, James L; Kneissl, Sibylle; Rawlinson, Jennifer E; Zwick, Timo; Zekas, Lisa; Ohlerth, Stefanie; Bienert-Zeit, Astrid

2016-05-01

Published descriptions of nonseptic arthritis of the equine temporomandibular joint (TMJ) are rare and large studies investigating variations in the TMJ for asymptomatic horses are lacking. The objectives of this cross-sectional, retrospective, multi-institutional study were to describe anatomical variations in the TMJ detected using computed tomography (CT) in an equid population asymptomatic for TMJ disease and determine whether these variations were associated with patient signalment, reason for CT examination, or CT slice width. Medical records at eight hospitals were searched for horses that had head/neck CT scans and no clinical signs of TMJ disease. Age, breed, sex, clinical presentation, and CT slice width data were recorded. Alterations in CT contour and density of the mandibular condyles, mandibular fossae, and TMJ intra-articular discs were described for each horse. Generalized logistic regression was used to test associations between anatomical variations and horse age. A total of 1018 horses were sampled. Anatomical variations were found in TMJ CT images for 40% of horses and 29% of joints. These were dichotomous with regard to age. Horses <1 year old commonly had alterations in the shape and density of the mandibular condyle. Older horses commonly had spherical hypodensities within the mandibular condyles consistent with bone cysts; and hyperdense regions of the intra-articular disc consistent with dystrophic mineralization. Findings indicated that TMJ anatomic variations were common in CT images of younger and older horses asymptomatic for TMJ disease. Future studies are needed to more definitively characterize these CT variations using gross pathology and histopathology. © 2016 American College of Veterinary Radiology.

Supplemental Analysis on Compressed Sensing Based Interior Tomography

PubMed Central

Yu, Hengyong; Yang, Jiansheng; Jiang, Ming; Wang, Ge

2010-01-01

Recently, in the compressed sensing framework we proved that an interior ROI can be exactly reconstructed via the total variation minimization if the ROI is piecewise constant. In the proofs, we implicitly utilized the property that if an artifact image assumes a constant value within the ROI then this constant must be zero. Here we prove this property in the space of square integrable functions. PMID:19717891

Cerebral Microbleeds: Burden Assessment by Using Quantitative Susceptibility Mapping

PubMed Central

Liu, Tian; Surapaneni, Krishna; Lou, Min; Cheng, Liuquan; Spincemaille, Pascal

2012-01-01

Purpose: To assess quantitative susceptibility mapping (QSM) for reducing the inconsistency of standard magnetic resonance (MR) imaging sequences in measurements of cerebral microbleed burden. Materials and Methods: This retrospective study was HIPAA compliant and institutional review board approved. Ten patients (5.6%) were selected from among 178 consecutive patients suspected of having experienced a stroke who were imaged with a multiecho gradient-echo sequence at 3.0 T and who had cerebral microbleeds on T2*-weighted images. QSM was performed for various ranges of echo time by using both the magnitude and phase components in the morphology-enabled dipole inversion method. Cerebral microbleed size was measured by two neuroradiologists on QSM images, T2*-weighted images, susceptibility-weighted (SW) images, and R2* maps calculated by using different echo times. The sum of susceptibility over a region containing a cerebral microbleed was also estimated on QSM images as its total susceptibility. Measurement differences were assessed by using the Student t test and the F test; P < .05 was considered to indicate a statistically significant difference. Results: When echo time was increased from approximately 20 to 40 msec, the measured cerebral microbleed volume increased by mean factors of 1.49 ± 0.86 (standard deviation), 1.64 ± 0.84, 2.30 ± 1.20, and 2.30 ± 1.19 for QSM, R2*, T2*-weighted, and SW images, respectively (P < .01). However, the measured total susceptibility with QSM did not show significant change over echo time (P = .31), and the variation was significantly smaller than any of the volume increases (P < .01 for each). Conclusion: The total susceptibility of a cerebral microbleed measured by using QSM is a physical property that is independent of echo time. © RSNA, 2011 PMID:22056688

Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images

PubMed Central

Dysli, Chantal; Enzmann, Volker; Sznitman, Raphael; Zinkernagel, Martin S.

2015-01-01

Purpose Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. Methods Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b+Prph2Rd2/J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. Results Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. Conclusions Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. Translational Relevance The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions. PMID:26336634

Measurements and analysis in imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Hoeller, Timothy L.

2009-02-01

A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results to baseline data using F-statistics. Self-parings over time are also useful. Special and common causes are identified apart from aging in applying the statistical methods. In the future, implementation of imaging measurement methods by research staff, doctors, and concerned patient partners result in improved health diagnosis, reporting, and cause determination. The long-term prospects for quantified measurements are better quality in imaging analysis with applications of higher utility for heath care providers.

MO-G-17A-07: Improved Image Quality in Brain F-18 FDG PET Using Penalized-Likelihood Image Reconstruction Via a Generalized Preconditioned Alternating Projection Algorithm: The First Patient Results

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

Schmidtlein, CR; Beattie, B; Humm, J

2014-06-15

Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1stmore » order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved with clinical OSEM reconstructions.« less

Direct EUV/X-Ray Modulation of the Ionosphere During the August 2017 Total Solar Eclipse

NASA Astrophysics Data System (ADS)

Mrak, Sebastijan; Semeter, Joshua; Drob, Douglas; Huba, J. D.

2018-05-01

The great American total solar eclipse of 21 August 2017 offered a fortuitous opportunity to study the response of the atmosphere and ionosphere using a myriad of ground instruments. We have used the network of U.S. Global Positioning System receivers to examine perturbations in maps of ionospheric total electron content (TEC). Coherent large-scale variations in TEC have been interpreted by others as gravity wave-induced traveling ionospheric disturbances. However, the solar disk had two active regions at that time, one near the center of the disk and one at the edge, which resulted in an irregular illumination pattern in the extreme ultraviolet (EUV)/X-ray bands. Using detailed EUV occultation maps calculated from the National Aeronautics and Space Administration Solar Dynamics Observatory Atmospheric Imaging Assembly images, we show excellent agreement between TEC perturbations and computed gradients in EUV illumination. The results strongly suggest that prominent large-scale TEC disturbances were consequences of direct EUV modulation, rather than gravity wave-induced traveling ionospheric disturbances.

Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization.

PubMed

Kainz, Philipp; Pfeiffer, Michael; Urschler, Martin

2017-01-01

Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses.

Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

PubMed Central

Kainz, Philipp; Pfeiffer, Michael

2017-01-01

Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses. PMID:29018612

Image segmentation on adaptive edge-preserving smoothing

NASA Astrophysics Data System (ADS)

He, Kun; Wang, Dan; Zheng, Xiuqing

2016-09-01

Nowadays, typical active contour models are widely applied in image segmentation. However, they perform badly on real images with inhomogeneous subregions. In order to overcome the drawback, this paper proposes an edge-preserving smoothing image segmentation algorithm. At first, this paper analyzes the edge-preserving smoothing conditions for image segmentation and constructs an edge-preserving smoothing model inspired by total variation. The proposed model has the ability to smooth inhomogeneous subregions and preserve edges. Then, a kind of clustering algorithm, which reasonably trades off edge-preserving and subregion-smoothing according to the local information, is employed to learn the edge-preserving parameter adaptively. At last, according to the confidence level of segmentation subregions, this paper constructs a smoothing convergence condition to avoid oversmoothing. Experiments indicate that the proposed algorithm has superior performance in precision, recall, and F-measure compared with other segmentation algorithms, and it is insensitive to noise and inhomogeneous-regions.

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer

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

Lee, D; Pollock, S; Keall, P

Purpose: Breathing consistency variations can cause respiratory-related motion blurring and artifacts and increase in MRI scan time due to inadequate respiratory-gating and discarding of breathing cycles. In a previous study the concept of audiovisual biofeedback (AV) guided respiratory-gated MRI was tested with healthy volunteers and it demonstrated image quality improvement on anatomical structures and scan time reduction. This study tests the applicability of AV-guided respiratorygated MRI for lung cancer in a prospective patient study. Methods: Image quality and scan time were investigated in thirteen lung cancer patients who underwent two 3T MRI sessions. In the first MRI session (pre-treatment), respiratory-gatedmore » MR images with free breathing (FB) and AV were acquired at inhalation and exhalation. An RF navigator placed on the liver dome was employed for the respiratory-gated MRI. This was repeated in the second MRI session (mid-treatment). Lung tumors were delineated on each dataset. FB and AV were compared in terms of (1) tumor definition assessed by lung tumor contours and (2) intra-patient scan time variation using the total image acquisition time of inhalation and exhalation datasets from the first and second MRI sessions across 13 lung cancer patients. Results: Compared to FB AV-guided respiratory-gated MRI improved image quality for contouring tumors with sharper boundaries and less blurring resulted in the improvement of tumor definition. Compared to FB the variation of intra-patient scan time with AV was reduced by 48% (p<0.001) from 54 s to 28 s. Conclusion: This study demonstrated that AV-guided respiratorygated MRI improved the quality of tumor images and fixed tumor definition for lung cancer. These results suggest that audiovisual biofeedback breathing guidance has the potential to control breathing for adequate respiratory-gating for lung cancer imaging and radiotherapy.« less

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

NASA Astrophysics Data System (ADS)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However, MODIS EVI phenology was "greened" up earlier than UAV-based deciduousness, perhaps reflecting the new late dry season leaf flush that increases EVI but not overall leaf cover. We discuss how the potential mechanisms that explain variation among species and between trees and lianas and the consequences for these variation for ecosystem processes and modeling.

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

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

Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivativesmore » of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.« less

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties

PubMed Central

Shi, Qi; Sun, Nanbo; Sun, Tao; Wang, Jing; Tan, Shan

2016-01-01

The exposure of normal tissues to high radiation during cone-beam CT (CBCT) imaging increases the risk of cancer and genetic defects. Statistical iterative algorithms with the total variation (TV) penalty have been widely used for low dose CBCT reconstruction, with state-of-the-art performance in suppressing noise and preserving edges. However, TV is a first-order penalty and sometimes leads to the so-called staircase effect, particularly over regions with smooth intensity transition in the reconstruction images. A second-order penalty known as the Hessian penalty was recently used to replace TV to suppress the staircase effect in CBCT reconstruction at the cost of slightly blurring object edges. In this study, we proposed a new penalty, the TV-H, which combines TV and Hessian penalties for CBCT reconstruction in a structure-adaptive way. The TV-H penalty automatically differentiates the edges, gradual transition and uniform local regions within an image using the voxel gradient, and adaptively weights TV and Hessian according to the local image structures in the reconstruction process. Our proposed penalty retains the benefits of TV, including noise suppression and edge preservation. It also maintains the structures in regions with gradual intensity transition more successfully. A majorization-minimization (MM) approach was designed to optimize the objective energy function constructed with the TV-H penalty. The MM approach employed a quadratic upper bound of the original objective function, and the original optimization problem was changed to a series of quadratic optimization problems, which could be efficiently solved using the Gauss-Seidel update strategy. We tested the reconstruction algorithm on two simulated digital phantoms and two physical phantoms. Our experiments indicated that the TV-H penalty visually and quantitatively outperformed both TV and Hessian penalties. PMID:27699100

Structure-adaptive CBCT reconstruction using weighted total variation and Hessian penalties.

PubMed

Shi, Qi; Sun, Nanbo; Sun, Tao; Wang, Jing; Tan, Shan

2016-09-01

The exposure of normal tissues to high radiation during cone-beam CT (CBCT) imaging increases the risk of cancer and genetic defects. Statistical iterative algorithms with the total variation (TV) penalty have been widely used for low dose CBCT reconstruction, with state-of-the-art performance in suppressing noise and preserving edges. However, TV is a first-order penalty and sometimes leads to the so-called staircase effect, particularly over regions with smooth intensity transition in the reconstruction images. A second-order penalty known as the Hessian penalty was recently used to replace TV to suppress the staircase effect in CBCT reconstruction at the cost of slightly blurring object edges. In this study, we proposed a new penalty, the TV-H, which combines TV and Hessian penalties for CBCT reconstruction in a structure-adaptive way. The TV-H penalty automatically differentiates the edges, gradual transition and uniform local regions within an image using the voxel gradient, and adaptively weights TV and Hessian according to the local image structures in the reconstruction process. Our proposed penalty retains the benefits of TV, including noise suppression and edge preservation. It also maintains the structures in regions with gradual intensity transition more successfully. A majorization-minimization (MM) approach was designed to optimize the objective energy function constructed with the TV-H penalty. The MM approach employed a quadratic upper bound of the original objective function, and the original optimization problem was changed to a series of quadratic optimization problems, which could be efficiently solved using the Gauss-Seidel update strategy. We tested the reconstruction algorithm on two simulated digital phantoms and two physical phantoms. Our experiments indicated that the TV-H penalty visually and quantitatively outperformed both TV and Hessian penalties.

GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation.

PubMed

Jia, Xun; Lou, Yifei; Li, Ruijiang; Song, William Y; Jiang, Steve B

2010-04-01

Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. The authors developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multigrid technique is also employed. It is found that 20-40 x-ray projections are sufficient to reconstruct images with satisfactory quality for IGRT. The reconstruction time ranges from 77 to 130 s on an NVIDIA Tesla C1060 (NVIDIA, Santa Clara, CA) GPU card, depending on the number of projections used, which is estimated about 100 times faster than similar iterative reconstruction approaches. Moreover, phantom studies indicate that the algorithm enables the CBCT to be reconstructed under a scanning protocol with as low as 0.1 mA s/projection. Comparing with currently widely used full-fan head and neck scanning protocol of approximately 360 projections with 0.4 mA s/projection, it is estimated that an overall 36-72 times dose reduction has been achieved in our fast CBCT reconstruction algorithm. This work indicates that the developed GPU-based CBCT reconstruction algorithm is capable of lowering imaging dose considerably. The high computation efficiency in this algorithm makes the iterative CBCT reconstruction approach applicable in real clinical environments.

The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry

NASA Astrophysics Data System (ADS)

Maynard, Matthew R.; Geyer, John W.; Aris, John P.; Shifrin, Roger Y.; Bolch, Wesley

2011-08-01

Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR™ and then imported to the 3D modeling software package Rhinoceros™ for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations in skeletal size, individual organ masses and total fetal masses. The resulting series of fetal hybrid computational phantoms is applicable to organ-level and bone-level internal and external radiation dosimetry for human fetuses of various ages and weight percentiles

Spatial and phylogenetic variation in plant defense in a tropical moist forest canopy community

NASA Astrophysics Data System (ADS)

McManus, K. M.; Asner, G. P.; Martin, R.

2013-12-01

Plants employ physical and chemical defenses to mitigate damage caused by herbivory. Spatial patterns of plant defense may provide insight into the role of plant-herbivore interactions in the assembly of plant communities. Within plant communities, the spatial overdispersion of anti-herbivore defenses by individuals may reflect a strategy to avoid host shifts from herbivore assemblages of neighboring plants. However, variation in plant defense may also result from trade-offs between foliar investment into defense and growth, mediated by variations in abiotic nutrient availability, or constrained by phylogeny. We measured four defensive traits (leaf toughness, total phenols, condensed tannins, and hydrolysable tannins) and three growth traits (LMA, C:N, total protein) of outer canopy foliage for 345 canopy trees representing 78 species, 65 genera, and 34 families in a moist tropical rainforest on Barro Colorado Island, Panama. The outer canopy provides an important, but rarely evaluated, cross-sectional image of the tropical forest ecosystem, and observations at this scale may provide an important link between field and remote sensing based studies. We used existing data on edaphic and geological properties to investigate the relationships of abiotic nutrient variation on variation in defense. Using regression and nested random-effects variance modeling, we found strong phylogenetic association with defensive traits at the family and species level, and little evidence for a trade-off between defensive traits. Greater understanding of phylogenetic structure in trait variation may yield improved characterizations of tropical biodiversity, from functional traits to risk assessments.

Imaging subtle microstructural variations in ceramics with precision ultrasonic velocity and attenuation measurements

NASA Technical Reports Server (NTRS)

Generazio, Edward R.; Roth, Don J.; Baaklini, George Y.

1987-01-01

Acoustic images of a silicon carbide ceramic disk were obtained using a precision scanning contact pulse echo technique. Phase and cross-correlation velocity, and attenuation maps were used to form color images of microstructural variations. These acoustic images reveal microstructural variations not observable with X-ray radiography.

Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.

PubMed

Kheradpisheh, Saeed R; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

2016-01-01

View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth) as well as their magnitude, which we call "variation level." We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group) on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier). This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

Vehicle Detection of Aerial Image Using TV-L1 Texture Decomposition

NASA Astrophysics Data System (ADS)

Wang, Y.; Wang, G.; Li, Y.; Huang, Y.

2016-06-01

Vehicle detection from high-resolution aerial image facilitates the study of the public traveling behavior on a large scale. In the context of road, a simple and effective algorithm is proposed to extract the texture-salient vehicle among the pavement surface. Texturally speaking, the majority of pavement surface changes a little except for the neighborhood of vehicles and edges. Within a certain distance away from the given vector of the road network, the aerial image is decomposed into a smoothly-varying cartoon part and an oscillatory details of textural part. The variational model of Total Variation regularization term and L1 fidelity term (TV-L1) is adopted to obtain the salient texture of vehicles and the cartoon surface of pavement. To eliminate the noise of texture decomposition, regions of pavement surface are refined by seed growing and morphological operation. Based on the shape saliency analysis of the central objects in those regions, vehicles are detected as the objects of rectangular shape saliency. The proposed algorithm is tested with a diverse set of aerial images that are acquired at various resolution and scenarios around China. Experimental results demonstrate that the proposed algorithm can detect vehicles at the rate of 71.5% and the false alarm rate of 21.5%, and that the speed is 39.13 seconds for a 4656 x 3496 aerial image. It is promising for large-scale transportation management and planning.

Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection

USGS Publications Warehouse

Davis, Philip A.

2013-01-01

The Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey (USGS) periodically collects airborne image data for the Colorado River corridor within Arizona (fig. 1) to allow scientists to study the impacts of Glen Canyon Dam water release on the corridor’s natural and cultural resources. These data are collected from just above Glen Canyon Dam (in Lake Powell) down to the entrance of Lake Mead, for a total distance of 450 kilometers (km) and within a 500-meter (m) swath centered on the river’s mainstem and its seven main tributaries (fig. 1). The most recent airborne data collection in 2009 acquired image data in four wavelength bands (blue, green, red, and near infrared) at a spatial resolution of 20 centimeters (cm). The image collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits. Davis (2012) reported on the performance of the SH52 sensor and on the processing steps required to produce the nearly flawless four-band image mosaic (sectioned into map tiles) for the river corridor. The final image mosaic has a total of only 3 km of surface defects in addition to some areas of cloud shadow because of persistent inclement weather during data collection. The 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River. Some analyses of these image mosaics do not require the full 12-bit dynamic range or all four bands of the calibrated image database, in which atmospheric scattering (or haze) had not been removed from the four bands. To provide scientists and the general public with image products that are more useful for visual interpretation, the 12-bit image data were converted to 8-bit natural-color and color-infrared images, which also removed atmospheric scattering within each wavelength-band image. The conversion required an evaluation of the histograms of each band’s digital-number population within each map tile throughout the corridor and the determination of the digital numbers corresponding to the lower and upper one percent of the picture-element population within each map tile. Visual examination of the image tiles that were given a 1-percent stretch (whereby the lower 1- percent 12-bit digital number is assigned an 8-bit value of zero and the upper 1-percent 12-bit digital number is assigned an 8-bit value of 255) indicated that this stretch sufficiently removed atmospheric scattering, which provided improved image clarity and true natural colors for all surface materials. The lower and upper 1-percent, 12-bit digital numbers for each wavelength-band image in the image tiles exhibit erratic variations along the river corridor; the variations exhibited similar trends in both the lower and upper 1-percent digital numbers for all four wavelength-band images (figs. 2–5). The erratic variations are attributed to (1) daily variations in atmospheric water-vapor content due to monsoonal storms, (2) variations in channel water color due to variable sediment input from tributaries, and (3) variations in the amount of topographic shadows within each image tile, in which reflectance is dominated by atmospheric scattering. To make the surface colors of the stretched, 8-bit images consistent among adjacent image tiles, it was necessary to average both the lower and upper 1-percent digital values for each wavelength-band image over 20 river miles to subdue the erratic variations. The average lower and upper 1-percent digital numbers for each image tile (figs. 2–5) were used to convert the 12-bit image values to 8-bit values and the resulting 8-bit four-band images were stored as natural-color (red, green, and blue wavelength bands) and color-infrared (near-infrared, red, and green wavelength bands) images in embedded geotiff format, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. All image data are projected in the State Plane (SP) map projection using the central Arizona zone (202) and the North American Datum of 1983 (NAD83). The map-tile scheme used to segment the corridor image mosaic followed the standard USGS quarter-quadrangle (QQ) map borders, but the high resolution (20 cm) of the images required further quarter segmentation (QQQ) of the standard QQ tiles, where the image mosaic covered a large fraction of a QQ map tile (segmentation shown in (figure 6), where QQ_1 to QQ_4 shows the number convention used to designate a quarter of a QQ tile). To minimize the size of each image tile, each image or map tile was subset to only include that part of the tile that had image data. In addition, some QQQ image tiles within a QQ tile were combined when adjacent QQQ map tiles were small. Thus, some image tiles consist of combinations of QQQ map tiles, some consist of an entire QQ map tile, and some consist of two adjoining QQ map tiles. The final image tiles number 143, which is a large number of files to list on the Internet for both the natural-color and color-infrared images. Thus, the image tiles were placed in seven file folders based on the one-half-degree geographic boundaries within the study area (fig. 7). The map tiles in each file folder were compressed to minimize folder size for more efficient downloading. The file folders are sequentially referred to as zone 1 through zone 7, proceeding down river (fig. 7). The QQ designations of the image tiles contained within each folder or zone are shown on the index map for each respective zone (figs. 8–14).

Characteristics of Rosai-Dorfman Disease Primarily Involved in the Central Nervous System: 3 Case Reports and Review of Literature.

PubMed

Luo, Zhengxiang; Zhang, Yansong; Zhao, Penglai; Lu, Hucheng; Yang, Kun; Zhang, Yuhai; Zeng, Yanjun

2017-01-01

This study aimed to summarize the clinical characteristics of Rosai-Dorfman disease primarily involving the central nervous system and to explore diagnosis and treatment. We analyzed the clinical, imaging, and pathologic characteristics; treatment; and prognosis in 3 cases of Rosai-Dorfman disease primarily involving the central nervous system. We also performed a literature review. The largest of multiple intracranial lesions was totally resected, and steroid administration and radiotherapy were performed in phases for the remaining lesions. During the 1-year follow-up period, the excised lesion did not recur, and no obvious variations were observed in the other lesions. Subtotal resection was performed of the largest of another group of multiple intracranial lesions, and the residual did not show any obvious variations during the 1-year follow-up period. The isolated lesion was totally resected and did not recur during a 2-year follow-up period. Rosai-Dorfman disease with multiple lesions primarily involving the central nervous system is rare. Imaging characteristics are similar to meningiomas, and the pathological features include lymphocytes and plasma cells reaching tissue cells with large volume and abundant cytoplasm. Surgery is the preferred treatment, as the effects of steroid administration and radiotherapy are not apparent. Copyright © 2016 Elsevier Inc. All rights reserved.

Annual and spatial variation in composition and activity of terrestrial mammals on two replicate plots in lowland forest of eastern Ecuador

PubMed Central

Loiselle, Bette A.

2018-01-01

Terrestrial mammals are important components of lowland forests in Amazonia (as seed dispersal agents, herbivores, predators) but there are relatively few detailed studies from areas that have not been affected by human activities (e.g., hunting, logging). Yet, such information is needed to evaluate effects of humans elsewhere. We used camera traps to sample medium to large-sized terrestrial mammals at a site in lowland forests of eastern Ecuador, one of the most biologically rich areas in the world. We deployed cameras on two study plots in terra firme forest at Tiputini Biodiversity Station. Sixteen cameras were arranged 200 m apart in a 4 × 4 grid on each plot. Cameras were operated for  60 days in January–March, 2014–2017, for a total of 3,707 and 3,482 trap-days on the two plots (Harpia, Puma). A total of 28 species were recorded; 26 on Harpia and 25 on Puma. Number of species recorded each year was slightly greater on Harpia whereas overall capture rates (images/100 trap-days) were higher on Puma. Although most species were recorded on each plot, differences in capture rates meant that yearly samples on a given plot were more similar to each other than to samples on the other plot. Images of most species showed a clumped distribution pattern on each plot; Panthera onca was the only species that did not show a clumped distribution on either plot. Images at a given camera location showed no evidence of autocorrelation with numbers of images at nearby camera locations, suggesting that species were responding to small-scale differences in habitat conditions. A redundancy analysis showed that environmental features within 50 or 100 m of camera locations (e.g., elevation, variation in elevation, slope, distance to streams) accounted for significant amounts of variation in distribution patterns of species. Composition and relative importance based on capture rates were very similar to results from cameras located along trails at the same site; similarities decreased at increasing spatial scales based on comparisons with results from other sites in Ecuador and Peru. PMID:29333349

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

The effect of individual variation on the structure and function of interaction networks in harvester ants

PubMed Central

Pinter-Wollman, Noa; Wollman, Roy; Guetz, Adam; Holmes, Susan; Gordon, Deborah M.

2011-01-01

Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant's interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow. PMID:21490001

Analysis on influence of installation error of off-axis three-mirror optical system on imaging line-of-sight

NASA Astrophysics Data System (ADS)

Gao, Lingyu; Li, Xinghua; Guo, Qianrui; Quan, Jing; Hu, Zhengyue; Su, Zhikun; Zhang, Dong; Liu, Peilu; Li, Haopeng

2018-01-01

The internal structure of off-axis three-mirror system is commonly complex. The mirror installation error in assembly always affects the imaging line-of-sight and further degrades the image quality. Due to the complexity of the optical path in off-axis three-mirror optical system, the straightforward theoretical analysis on the variations of imaging line-of-sight is extremely difficult. In order to simplify the theoretical analysis, an equivalent single-mirror system is proposed and presented in this paper. In addition, the mathematical model of single-mirror system is established and the accurate expressions of imaging coordinate are derived. Utilizing the simulation software ZEMAX, off-axis three-mirror model and single-mirror model are both established. By adjusting the position of mirror and simulating the line-of-sight rotation of optical system, the variations of imaging coordinates are clearly observed. The final simulation results include: in off-axis three-mirror system, the varying sensitivity of the imaging coordinate to the rotation of line-of-sight is approximately 30 um/″; in single-mirror system, the varying sensitivity of the imaging coordinate to the rotation of line-of-sight is 31.5 um/″. Compared to the simulation results of the off-axis three-mirror model, the 5% relative error of single-mirror model analysis highly satisfies the requirement of equivalent analysis and also verifies its validity. This paper presents a new method to analyze the installation error of the mirror in the off-axis three-mirror system influencing on the imaging line-of-sight. Moreover, the off-axis three-mirror model is totally equivalent to the single-mirror model in theoretical analysis.

Infrared and visible image fusion based on total variation and augmented Lagrangian.

PubMed

Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

2017-11-01

This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.

Low-illumination image denoising method for wide-area search of nighttime sea surface

NASA Astrophysics Data System (ADS)

Song, Ming-zhu; Qu, Hong-song; Zhang, Gui-xiang; Tao, Shu-ping; Jin, Guang

2018-05-01

In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface, a model based on total variation (TV) and split Bregman is proposed in this paper. A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types, and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image. The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform. The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images, and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.

Novel Application of Confocal Laser Scanning Microscopy and 3D Volume Rendering toward Improving the Resolution of the Fossil Record of Charcoal

PubMed Central

Belcher, Claire M.; Punyasena, Surangi W.; Sivaguru, Mayandi

2013-01-01

Variations in the abundance of fossil charcoals between rocks and sediments are assumed to reflect changes in fire activity in Earth’s past. These variations in fire activity are often considered to be in response to environmental, ecological or climatic changes. The role that fire plays in feedbacks to such changes is becoming increasingly important to understand and highlights the need to create robust estimates of variations in fossil charcoal abundance. The majority of charcoal based fire reconstructions quantify the abundance of charcoal particles and do not consider the changes in the morphology of the individual particles that may have occurred due to fragmentation as part of their transport history. We have developed a novel application of confocal laser scanning microscopy coupled to image processing that enables the 3-dimensional reconstruction of individual charcoal particles. This method is able to measure the volume of both microfossil and mesofossil charcoal particles and allows the abundance of charcoal in a sample to be expressed as total volume of charcoal. The method further measures particle surface area and shape allowing both relationships between different size and shape metrics to be analysed and full consideration of variations in particle size and size sorting between different samples to be studied. We believe application of this new imaging approach could allow significant improvement in our ability to estimate variations in past fire activity using fossil charcoals. PMID:23977267

Contrast adaptive total p-norm variation minimization approach to CT reconstruction for artifact reduction in reduced-view brain perfusion CT

NASA Astrophysics Data System (ADS)

Kim, Chang-Won; Kim, Jong-Hyo

2011-03-01

Perfusion CT (PCT) examinations are getting more frequently used for diagnosis of acute brain diseases such as hemorrhage and infarction, because the functional map images it produces such as regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), and mean transit time (MTT) may provide critical information in the emergency work-up of patient care. However, a typical PCT scans the same slices several tens of times after injection of contrast agent, which leads to much increased radiation dose and is inevitability of growing concern for radiation-induced cancer risk. Reducing the number of views in projection in combination of TV minimization reconstruction technique is being regarded as an option for radiation reduction. However, reconstruction artifacts due to insufficient number of X-ray projections become problematic especially when high contrast enhancement signals are present or patient's motion occurred. In this study, we present a novel reconstruction technique using contrast-adaptive TpV minimization that can reduce reconstruction artifacts effectively by using different p-norms in high contrast and low contrast objects. In the proposed method, high contrast components are first reconstructed using thresholded projection data and low p-norm total variation to reflect sparseness in both projection and reconstruction spaces. Next, projection data are modified to contain only low contrast objects by creating projection data of reconstructed high contrast components and subtracting them from original projection data. Then, the low contrast projection data are reconstructed by using relatively high p-norm TV minimization technique, and are combined with the reconstructed high contrast component images to produce final reconstructed images. The proposed algorithm was applied to numerical phantom and a clinical data set of brain PCT exam, and the resultant images were compared with those using filtered back projection (FBP) and conventional TV reconstruction algorithm. Our results show the potential of the proposed algorithm for image quality improvement, which in turn may lead to dose reduction.

Image restoration for civil engineering structure monitoring using imaging system embedded on UAV

NASA Astrophysics Data System (ADS)

Vozel, Benoit; Dumoulin, Jean; Chehdi, Kacem

2013-04-01

Nowadays, civil engineering structures are periodically surveyed by qualified technicians (i.e. alpinist) operating visual inspection using heavy mechanical pods. This method is far to be safe, not only for civil engineering structures monitoring staff, but also for users. Due to the unceasing traffic increase, making diversions or closing lanes on bridge becomes more and more difficult. New inspection methods have to be found. One of the most promising technique is to develop inspection method using images acquired by a dedicated monitoring system operating around the civil engineering structures, without disturbing the traffic. In that context, the use of images acquired with an UAV, which fly around the structures is of particular interest. The UAV can be equipped with different vision system (digital camera, infrared sensor, video, etc.). Nonetheless, detection of small distresses on images (like cracks of 1 mm or less) depends on image quality, which is sensitive to internal parameters of the UAV (vibration modes, video exposure times, etc.) and to external parameters (turbulence, bad illumination of the scene, etc.). Though progresses were made at UAV level and at sensor level (i.e. optics), image deterioration is still an open problem. These deteriorations are mainly represented by motion blur that can be coupled with out-of-focus blur and observation noise on acquired images. In practice, deteriorations are unknown if no a priori information is available or dedicated additional instrumentation is set-up at UAV level. Image restoration processing is therefore required. This is a difficult problem [1-3] which has been intensively studied over last decades [4-12]. Image restoration can be addressed by following a blind approach or a myopic one. In both cases, it includes two processing steps that can be implemented in sequential or alternate mode. The first step carries out the identification of the blur impulse response and the second one makes use of this estimated blur kernel for performing the deconvolution of the acquired image. In the present work, different regularization methods, mainly based on the pseudo norm aforementioned Total Variation, are studied and analysed. The key point of their respective implementation, their properties and limits are investigated in this particular applicative context. References [1] J. Hadamard. Lectures on Cauchy's problem in linear partial differential equations. Yale University Press, 1923. [2] A. N. Tihonov. On the resolution of incorrectly posed problems and regularisation method (in Russian). Doklady A. N.SSSR, 151(3), 1963. [3] C. R. Vogel. Computational Methods for inverse problems, SIAM, 2002. [4] A. K. Katsaggelos, J. Biemond, R.W. Schafer, and R. M. Mersereau, "A regularized iterative image restoration algorithm," IEEE Transactions on Signal Processing, vol.39, no. 4, pp. 914-929, 1991. [5] J. Biemond, R. L. Lagendijk, and R. M. Mersereau, "Iterative methods for image deblurring," Proceedings of the IEEE, vol. 78, no. 5, pp. 856-883, 1990. [6] D. Kundur and D. Hatzinakos, "Blind image deconvolution," IEEE Signal Processing Magazine, vol. 13, no. 3, pp. 43-64, 1996. [7] Y. L. You and M. Kaveh, "A regularization approach to joint blur identification and image restoration," IEEE Transactions on Image Processing, vol. 5, no. 3, pp. 416-428, 1996. [8] T. F. Chan and C. K. Wong, "Total variation blind deconvolution," IEEE Transactions on Image Processing, vol. 7, no. 3, pp. 370-375, 1998. [9] S. Chardon, B. Vozel, and K. Chehdi. Parametric Blur Estimation Using the GCV Criterion and a Smoothness Constraint on the Image. Multidimensional Systems and Signal Processing Journal, Kluwer Ed., 10:395-414, 1999 [10] B. Vozel, K. Chehdi, and J. Dumoulin. Myopic image restoration for civil structures inspection using UAV (in French). In GRETSI, 2005. [11] L. Bar, N. Sochen, and N. Kiryati. Semi-blind image restoration via Mumford-Shah regularization. IEEE Transactions on Image Processing, 15(2), 2006. [12] J. H. Money and S. H. Kang, "Total variation minimizing blind deconvolution with shock filter reference," Image and Vision Computing, vol. 26, no. 2, pp. 302-314, 2008.

White blood cell differential count of maturation stages in bone marrow smear using dual-stage convolutional neural networks.

PubMed

Choi, Jin Woo; Ku, Yunseo; Yoo, Byeong Wook; Kim, Jung-Ah; Lee, Dong Soon; Chai, Young Jun; Kong, Hyoun-Joong; Kim, Hee Chan

2017-01-01

The white blood cell differential count of the bone marrow provides information concerning the distribution of immature and mature cells within maturation stages. The results of such examinations are important for the diagnosis of various diseases and for follow-up care after chemotherapy. However, manual, labor-intensive methods to determine the differential count lead to inter- and intra-variations among the results obtained by hematologists. Therefore, an automated system to conduct the white blood cell differential count is highly desirable, but several difficulties hinder progress. There are variations in the white blood cells of each maturation stage, small inter-class differences within each stage, and variations in images because of the different acquisition and staining processes. Moreover, a large number of classes need to be classified for bone marrow smear analysis, and the high density of touching cells in bone marrow smears renders difficult the segmentation of single cells, which is crucial to traditional image processing and machine learning. Few studies have attempted to discriminate bone marrow cells, and even these have either discriminated only a few classes or yielded insufficient performance. In this study, we propose an automated white blood cell differential counting system from bone marrow smear images using a dual-stage convolutional neural network (CNN). A total of 2,174 patch images were collected for training and testing. The dual-stage CNN classified images into 10 classes of the myeloid and erythroid maturation series, and achieved an accuracy of 97.06%, a precision of 97.13%, a recall of 97.06%, and an F-1 score of 97.1%. The proposed method not only showed high classification performance, but also successfully classified raw images without single cell segmentation and manual feature extraction by implementing CNN. Moreover, it demonstrated rotation and location invariance. These results highlight the promise of the proposed method as an automated white blood cell differential count system.

White blood cell differential count of maturation stages in bone marrow smear using dual-stage convolutional neural networks

PubMed Central

Choi, Jin Woo; Ku, Yunseo; Yoo, Byeong Wook; Kim, Jung-Ah; Lee, Dong Soon; Chai, Young Jun; Kong, Hyoun-Joong

2017-01-01

The white blood cell differential count of the bone marrow provides information concerning the distribution of immature and mature cells within maturation stages. The results of such examinations are important for the diagnosis of various diseases and for follow-up care after chemotherapy. However, manual, labor-intensive methods to determine the differential count lead to inter- and intra-variations among the results obtained by hematologists. Therefore, an automated system to conduct the white blood cell differential count is highly desirable, but several difficulties hinder progress. There are variations in the white blood cells of each maturation stage, small inter-class differences within each stage, and variations in images because of the different acquisition and staining processes. Moreover, a large number of classes need to be classified for bone marrow smear analysis, and the high density of touching cells in bone marrow smears renders difficult the segmentation of single cells, which is crucial to traditional image processing and machine learning. Few studies have attempted to discriminate bone marrow cells, and even these have either discriminated only a few classes or yielded insufficient performance. In this study, we propose an automated white blood cell differential counting system from bone marrow smear images using a dual-stage convolutional neural network (CNN). A total of 2,174 patch images were collected for training and testing. The dual-stage CNN classified images into 10 classes of the myeloid and erythroid maturation series, and achieved an accuracy of 97.06%, a precision of 97.13%, a recall of 97.06%, and an F-1 score of 97.1%. The proposed method not only showed high classification performance, but also successfully classified raw images without single cell segmentation and manual feature extraction by implementing CNN. Moreover, it demonstrated rotation and location invariance. These results highlight the promise of the proposed method as an automated white blood cell differential count system. PMID:29228051

Scatter correction in cone-beam CT via a half beam blocker technique allowing simultaneous acquisition of scatter and image information

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

Lee, Ho; Xing Lei; Lee, Rena

2012-05-15

Purpose: X-ray scatter incurred to detectors degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, due to missing information resulting from the obstruction of the blocker, such methods require dual scanning or dynamically moving blocker to obtain a complete volumetric image. Here, we propose a half beam blocker-based approach, in conjunction with a total variation (TV) regularized Feldkamp-Davis-Kress (FDK) algorithm, to correct scatter-induced artifacts by simultaneously acquiring image and scatter information frommore » a single-rotation CBCT scan. Methods: A half beam blocker, comprising lead strips, is used to simultaneously acquire image data on one side of the projection data and scatter data on the other half side. One-dimensional cubic B-Spline interpolation/extrapolation is applied to derive patient specific scatter information by using the scatter distributions on strips. The estimated scatter is subtracted from the projection image acquired at the opposite view. With scatter-corrected projections where this subtraction is completed, the FDK algorithm based on a cosine weighting function is performed to reconstruct CBCT volume. To suppress the noise in the reconstructed CBCT images produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by a minimization using a steepest gradient descent optimization method. The experimental studies using Catphan504 and anthropomorphic phantoms were carried out to evaluate the performance of the proposed scheme. Results: The scatter-induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the nonuniformity value was reduced from 39.3% to 3.1%. The root mean square error relative to values inside the regions of interest selected from a benchmark scatter free image was reduced from 50 to 11.3. The TV regularization also led to a better contrast-to-noise ratio. Conclusions: An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.« less

Graph cuts for curvature based image denoising.

PubMed

Bae, Egil; Shi, Juan; Tai, Xue-Cheng

2011-05-01

Minimization of total variation (TV) is a well-known method for image denoising. Recently, the relationship between TV minimization problems and binary MRF models has been much explored. This has resulted in some very efficient combinatorial optimization algorithms for the TV minimization problem in the discrete setting via graph cuts. To overcome limitations, such as staircasing effects, of the relatively simple TV model, variational models based upon higher order derivatives have been proposed. The Euler's elastica model is one such higher order model of central importance, which minimizes the curvature of all level lines in the image. Traditional numerical methods for minimizing the energy in such higher order models are complicated and computationally complex. In this paper, we will present an efficient minimization algorithm based upon graph cuts for minimizing the energy in the Euler's elastica model, by simplifying the problem to that of solving a sequence of easy graph representable problems. This sequence has connections to the gradient flow of the energy function, and converges to a minimum point. The numerical experiments show that our new approach is more effective in maintaining smooth visual results while preserving sharp features better than TV models.

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

PubMed Central

Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

2016-01-01

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the “gas of near circles” active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

BOREAS RSS-10 TOMS Circumpolar One-Degree PAR Images

NASA Technical Reports Server (NTRS)

Dye, Dennis G.; Holben, Brent; Nickeson, Jaime (Editor); Hall, Forrest G. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-10 team investigated the magnitude of daily, seasonal, and yearly variations of Photosynthetically Active Radiation (PAR) from ground and satellite observations. This data set contains satellite estimates of surface-incident PAR (400-700 nm, MJ/sq m) at one-degree spatial resolution. The spatial coverage is circumpolar from latitudes of 41 to 66 degrees north. The temporal coverage is from May through September for years 1979 through 1989. Eleven-year statistics are also provided: (1) mean, (2) standard deviation, and (3) coefficient of variation for 1979-89. The PAR estimates were derived from the global gridded ultraviolet reflectivity data product (average of 360, 380 nm) from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS). Image mask data are provided for identifying the boreal forest zone, and ocean/land and snow/ice-covered areas. The data are available as binary image format data files. The PAR data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Fractional-order TV-L2 model for image denoising

NASA Astrophysics Data System (ADS)

Chen, Dali; Sun, Shenshen; Zhang, Congrong; Chen, YangQuan; Xue, Dingyu

2013-10-01

This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

Some Variations on Total Variation-Based Image Smoothing

DTIC Science & Technology

2009-03-01

isotropic BV seminorm. Given N > 1, we let h = 1/N and consider discrete functions fi, i = (i1, i2), 0 ≤ i1, i2 < N. A discrete Lh2 (I) norm of f is defined...p) given in (23), while the second is the Lh2 -projection of p onto the set K. We note at the end of the next section that this iteration is a special...I) ≤ λ(|f̃ n|BVh(I) − 〈∇hfn, pn〉) = (pn)2. So we can ensure that we’ve computed f̃ to within an error of , i.e., ‖f̃ − f̃n‖ Lh2 (I) ≤ , 5 if we

Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

NASA Astrophysics Data System (ADS)

Vishnukumar, S.; Wilscy, M.

2017-12-01

In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

PubMed Central

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

2012-01-01

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

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Bias correction for magnetic resonance images via joint entropy regularization.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Luo, Jianhua; Huang, Qiu; Feng, Dagan; Li, Yuanxiang

2014-01-01

Due to the imperfections of the radio frequency (RF) coil or object-dependent electrodynamic interactions, magnetic resonance (MR) images often suffer from a smooth and biologically meaningless bias field, which causes severe troubles for subsequent processing and quantitative analysis. To effectively restore the original signal, this paper simultaneously exploits the spatial and gradient features of the corrupted MR images for bias correction via the joint entropy regularization. With both isotropic and anisotropic total variation (TV) considered, two nonparametric bias correction algorithms have been proposed, namely IsoTVBiasC and AniTVBiasC. These two methods have been applied to simulated images under various noise levels and bias field corruption and also tested on real MR data. The test results show that the proposed two methods can effectively remove the bias field and also present comparable performance compared to the state-of-the-art methods.

A Laplacian based image filtering using switching noise detector.

PubMed

Ranjbaran, Ali; Hassan, Anwar Hasni Abu; Jafarpour, Mahboobe; Ranjbaran, Bahar

2015-01-01

This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction of the pixels value with their related Laplacian value weighted by local noise estimator. The only parameter which controls smoothness is the number of iterations. Noise reduction quality of the introduced method is evaluated and compared with some classic algorithms like Wiener and Total Variation based filters for Gaussian noise. And also the method compared with the state-of-the-art method BM3D for some images. The algorithm appears to be easy, fast and comparable with many classic denoising algorithms for Gaussian noise.

Reproducibility of MR-Based Attenuation Maps in PET/MRI and the Impact on PET Quantification in Lung Cancer.

PubMed

Olin, Anders; Ladefoged, Claes N; Langer, Natasha H; Keller, Sune H; Löfgren, Johan; Hansen, Adam E; Kjær, Andreas; Langer, Seppo W; Fischer, Barbara M; Andersen, Flemming L

2018-06-01

Quantitative PET/MRI is dependent on reliable and reproducible MR-based attenuation correction (MR-AC). In this study, we evaluated the quality of current vendor-provided thoracic MR-AC maps and further investigated the reproducibility of their impact on 18 F-FDG PET quantification in patients with non-small cell lung cancer. Methods: Eleven patients with inoperable non-small cell lung cancer underwent 2-5 thoracic PET/MRI scan-rescan examinations within 22 d. 18 F-FDG PET data were acquired along with 2 Dixon MR-AC maps for each examination. Two PET images (PET A and PET B ) were reconstructed using identical PET emission data but with MR-AC from these intrasubject repeated attenuation maps. In total, 90 MR-AC maps were evaluated visually for quality and the occurrence of categorized artifacts by 2 PET/MRI-experienced physicians. Each tumor was outlined by a volume of interest (40% isocontour of maximum) on PET A , which was then projected onto the corresponding PET B SUV mean and SUV max were assessed from the PET images. Within-examination coefficients of variation and Bland-Altman analyses were conducted for the assessment of SUV variations between PET A and PET B Results: Image artifacts were observed in 86% of the MR-AC maps, and 30% of the MR-AC maps were subjectively expected to affect the tumor SUV. SUV mean and SUV max resulted in coefficients of variation of 5.6% and 6.6%, respectively, and scan-rescan SUV variations were within ±20% in 95% of the cases. Substantial SUV variations were seen mainly for scan-rescan examinations affected by respiratory motion. Conclusion: Artifacts occur frequently in standard thoracic MR-AC maps, affecting the reproducibility of PET/MRI. These, in combination with other well-known sources of error associated with PET/MRI examinations, lead to inconsistent SUV measurements in serial studies, which may affect the reliability of therapy response assessment. A thorough visual inspection of the thoracic MR-AC map and Dixon images from which it is derived remains crucial for the detection of MR-AC artifacts that may influence the reliability of SUV. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Interobserver Variation in Response Evaluation Criteria in Solid Tumors 1.1.

PubMed

Karmakar, Arunabha; Kumtakar, Apeksha; Sehgal, Himanshu; Kumar, Savith; Kalyanpur, Arjun

2018-06-19

Response Evaluation Criteria in Solid Tumors (RECIST 1.1) is the gold standard for imaging response evaluation in cancer trials. We sought to evaluate consistency of applying RECIST 1.1 between 2 conventionally trained radiologists, designated as A and B; identify reasons for variation; and reconcile these differences for future studies. The study was approved as an institutional quality check exercise. Since no identifiable patient data was collected or used, a waiver of informed consent was granted. Imaging case report forms of a concluded multicentric breast cancer trial were retrospectively reviewed. Cohen's kappa was used to rate interobserver agreement in Response Evaluation Data (target response, nontarget response, new lesions, overall response). Significant variations were reassessed by a senior radiologist to extrapolate reasons for disagreement. Methods to improve agreement were similarly ascertained. Sixty one cases with total of 82 data-pairs were evaluated (35 data-pairs in visit 5, 47 in visit 9). Both radiologists showed moderate agreement in target response (n = 82; ĸ = 0.477; 95% confidence interval [CI]: 0.314-0.640-), nontarget response (n = 82; ĸ = 0.578; 95% CI: 0.213-0.944) and overall response evaluation in both visits (n = 82; ĸ = 0.510; 95% CI: 0.344-0.676). Further assessment demonstrated "Prevalence effect" of Kappa in some cases which led to underestimation of agreement. Percent agreement of overall response was 74.39% while percent variation was 25.6%. Differences in interpreting RECIST 1.1 and in radiological image interpretation were the primary sources of variation. The commonest overall response was "Partial Response" (Rad A:45/82; Rad B:63/82). Inspite of moderate interobserver agreement, qualitative interpretation differences in some cases increased interobserver variability. Protocols such as Adjudication, to reduce easily avoidable inconsistencies are or should be a part of the Standard Operating Procedure in imaging institutions. Based on our findings, a standard checklist has been developed to help reduce the interpretation error-margin for future studies. Such check-lists may improve interobserver agreement in the preadjudication phase thereby improving quality of results and reducing adjudication per case ratio. Improving data reliability when using RECIST 1.1 will reflect in better cancer clinical trial outcomes. A checklist can be of use to imaging centers to assess and improve their own processes. Copyright © 2018. Published by Elsevier Inc.

American Alcohol Photo Stimuli (AAPS): A standardized set of alcohol and matched non-alcohol images.

PubMed

Stauffer, Christopher S; Dobberteen, Lily; Woolley, Joshua D

2017-11-01

Photographic stimuli are commonly used to assess cue reactivity in the research and treatment of alcohol use disorder. The stimuli used are often non-standardized, not properly validated, and poorly controlled. There are no previously published, validated, American-relevant sets of alcohol images created in a standardized fashion. We aimed to: 1) make available a standardized, matched set of photographic alcohol and non-alcohol beverage stimuli, 2) establish face validity, the extent to which the stimuli are subjectively viewed as what they are purported to be, and 3) establish construct validity, the degree to which a test measures what it claims to be measuring. We produced a standardized set of 36 images consisting of American alcohol and non-alcohol beverages matched for basic color, form, and complexity. A total of 178 participants (95 male, 82 female, 1 genderqueer) rated each image for appetitiveness. An arrow-probe task, in which matched pairs were categorized after being presented for 200 ms, assessed face validity. Criteria for construct validity were met if variation in AUDIT scores were associated with variation in performance on tasks during alcohol image presentation. Overall, images were categorized with >90% accuracy. Participants' AUDIT scores correlated significantly with alcohol "want" and "like" ratings [r(176) = 0.27, p = <0.001; r(176) = 0.36, p = <0.001] and arrow-probe latency [r(176) = -0.22, p = 0.004], but not with non-alcohol outcomes. Furthermore, appetitive ratings and arrow-probe latency for alcohol, but not non-alcohol, differed significantly for heavy versus light drinkers. Our image set provides valid and reliable alcohol stimuli for both explicit and implicit tests of cue reactivity. The use of standardized, validated, reliable image sets may improve consistency across research and treatment paradigms.

Imaging the spotty surface of Betelgeuse in the H band

NASA Astrophysics Data System (ADS)

Haubois, X.; Perrin, G.; Lacour, S.; Verhoelst, T.; Meimon, S.; Mugnier, L.; Thiébaut, E.; Berger, J. P.; Ridgway, S. T.; Monnier, J. D.; Millan-Gabet, R.; Traub, W.

2009-12-01

Aims. This paper reports on H-band interferometric observations of Betelgeuse made at the three-telescope interferometer IOTA. We image Betelgeuse and its asymmetries to understand the spatial variation of the photosphere, including its diameter, limb darkening, effective temperature, surrounding brightness, and bright (or dark) star spots. Methods: We used different theoretical simulations of the photosphere and dusty environment to model the visibility data. We made images with parametric modeling and two image reconstruction algorithms: MIRA and WISARD. Results: We measure an average limb-darkened diameter of 44.28 ± 0.15 mas with linear and quadratic models and a Rosseland diameter of 45.03 ± 0.12 mas with a MARCS model. These measurements lead us to derive an updated effective temperature of 3600 ± 66 K. We detect a fully-resolved environment to which the silicate dust shell is likely to contribute. By using two imaging reconstruction algorithms, we unveiled two bright spots on the surface of Betelgeuse. One spot has a diameter of about 11 mas and accounts for about 8.5% of the total flux. The second one is unresolved (diameter < 9 mas) with 4.5% of the total flux. Conclusions: Resolved images of Betelgeuse in the H band are asymmetric at the level of a few percent. The MOLsphere is not detected in this wavelength range. The amount of measured limb-darkening is in good agreement with model predictions. The two spots imaged at the surface of the star are potential signatures of convective cells.

PHOTOMETRIC TRENDS IN THE VISIBLE SOLAR CONTINUUM AND THEIR SENSITIVITY TO THE CENTER-TO-LIMB PROFILE

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

Peck, C. L.; Rast, M. P.

2015-08-01

Solar irradiance variations over solar rotational timescales are largely determined by the passage of magnetic structures across the visible solar disk. Variations on solar cycle timescales are thought to be similarly due to changes in surface magnetism with activity. Understanding the contribution of magnetic structures to total solar irradiance and solar spectral irradiance requires assessing their contributions as a function of disk position. Since only relative photometry is possible from the ground, the contrasts of image pixels are measured with respect to a center-to-limb intensity profile. Using nine years of full-disk red and blue continuum images from the Precision Solarmore » Photometric Telescope at the Mauna Loa Solar Observatory, we examine the sensitivity of continuum contrast measurements to the center-to-limb profile definition. Profiles which differ only by the amount of magnetic activity allowed in the pixels used to determine them yield oppositely signed solar cycle length continuum contrast trends, either agreeing with previous results and showing negative correlation with solar cycle or disagreeing and showing positive correlation with solar cycle. Changes in the center-to-limb profile shape over the solar cycle are responsible for the contradictory contrast results, and we demonstrate that the lowest contrast structures, internetwork and network, are most sensitive to these. Thus the strengths of the full-disk, internetwork, and network photometric trends depend critically on the magnetic flux density used in the quiet-Sun definition. We conclude that the contributions of low contrast magnetic structures to variations in the solar continuum output, particularly to long-term variations, are difficult, if not impossible, to determine without the use of radiometric imaging.« less

Imaging spectrometer measurement of water vapor in the 400 to 2500 nm spectral region

NASA Technical Reports Server (NTRS)

Green, Robert O.; Roberts, Dar A.; Conel, James E.; Dozier, Jeff

1995-01-01

The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) measures the total upwelling spectral radiance from 400 to 2500 nm sampled at 10 nm intervals. The instrument acquires spectral data at an altitude of 20 km above sea level, as images of 11 by up to 100 km at 17x17 meter spatial sampling. We have developed a nonlinear spectral fitting algorithm coupled with a radiative transfer code to derive the total path water vapor from the spectrum, measured for each spatial element in an AVIRIS image. The algorithm compensates for variation in the surface spectral reflectance and atmospheric aerosols. It uses water vapor absorption bands centered at 940 nm, 1040 nm, and 1380 nm. We analyze data sets with water vapor abundances ranging from 1 to 40 perceptible millimeters. In one data set, the total path water vapor varies from 7 to 21 mm over a distance of less than 10 km. We have analyzed a time series of five images acquired at 12 minute intervals; these show spatially heterogeneous changes of advocated water vapor of 25 percent over 1 hour. The algorithm determines water vapor for images with a range of ground covers, including bare rock and soil, sparse to dense vegetation, snow and ice, open water, and clouds. The precision of the water vapor determination approaches one percent. However, the precision is sensitive to the absolute abundance and the absorption strength of the atmospheric water vapor band analyzed. We have evaluated the accuracy of the algorithm by comparing several surface-based determinations of water vapor at the time of the AVIRIS data acquisition. The agreement between the AVIRIS measured water vapor and the in situ surface radiometer and surface interferometer measured water vapor is 5 to 10 percent.

Rib Geometry Explains Variation in Dynamic Structural Response: Potential Implications for Frontal Impact Fracture Risk.

PubMed

Murach, Michelle M; Kang, Yun-Seok; Goldman, Samuel D; Schafman, Michelle A; Schlecht, Stephen H; Moorhouse, Kevin; Bolte, John H; Agnew, Amanda M

2017-09-01

The human thorax is commonly injured in motor vehicle crashes, and despite advancements in occupant safety rib fractures are highly prevalent. The objective of this study was to quantify the ability of gross and cross-sectional geometry, separately and in combination, to explain variation of human rib structural properties. One hundred and twenty-two whole mid-level ribs from 76 fresh post-mortem human subjects were tested in a dynamic frontal impact scenario. Structural properties (peak force and stiffness) were successfully predicted (p < 0.001) by rib cross-sectional geometry obtained via direct histological imaging (total area, cortical area, and section modulus) and were improved further when utilizing a combination of cross-sectional and gross geometry (robusticity, whole bone strength index). Additionally, preliminary application of a novel, adaptive thresholding technique, allowed for total area and robusticity to be measured on a subsample of standard clinical CT scans with varied success. These results can be used to understand variation in individual rib response to frontal loading as well as identify important geometric parameters, which could ultimately improve injury criteria as well as the biofidelity of anthropomorphic test devices (ATDs) and finite element (FE) models of the human thorax.

Rib Geometry Explains Variation in Dynamic Structural Response: Potential Implications for Frontal Impact Fracture Risk

PubMed Central

Murach, Michelle M.; Kang, Yun-Seok; Goldman, Samuel D.; Schafman, Michelle A.; Schlecht, Stephen H.; Moorhouse, Kevin; Bolte, John H.; Agnew, Amanda M.

2018-01-01

The human thorax is commonly injured in motor vehicle crashes, and despite advancements in occupant safety rib fractures are highly prevalent. The objective of this study was to quantify the ability of gross and cross-sectional geometry, separately and in combination, to explain variation of human rib structural properties. One hundred and twenty-two whole mid-level ribs from 76 fresh post-mortem human subjects were tested in a dynamic frontal impact scenario. Structural properties (peak force and stiffness) were successfully predicted (p<0.001) by rib cross-sectional geometry obtained via direct histological imaging (total area, cortical area, and section modulus) and were improved further when utilizing a combination of cross-sectional and gross geometry (robusticity, whole bone strength index). Additionally, preliminary application of a novel, adaptive thresholding technique, allowed for total area and robusticity to be measured on a subsample of standard clinical CT scans with varied success. These results can be used to understand variation in individual rib response to frontal loading as well as identify important geometric parameters, which could ultimately improve injury criteria as well as the biofidelity of anthropomorphic test devices (ATDs) and finite element (FE) models of the human thorax. PMID:28547660

A New Variational Method for Bias Correction and Its Applications to Rodent Brain Extraction.

PubMed

Chang, Huibin; Huang, Weimin; Wu, Chunlin; Huang, Su; Guan, Cuntai; Sekar, Sakthivel; Bhakoo, Kishore Kumar; Duan, Yuping

2017-03-01

Brain extraction is an important preprocessing step for further analysis of brain MR images. Significant intensity inhomogeneity can be observed in rodent brain images due to the high-field MRI technique. Unlike most existing brain extraction methods that require bias corrected MRI, we present a high-order and L 0 regularized variational model for bias correction and brain extraction. The model is composed of a data fitting term, a piecewise constant regularization and a smooth regularization, which is constructed on a 3-D formulation for medical images with anisotropic voxel sizes. We propose an efficient multi-resolution algorithm for fast computation. At each resolution layer, we solve an alternating direction scheme, all subproblems of which have the closed-form solutions. The method is tested on three T2 weighted acquisition configurations comprising a total of 50 rodent brain volumes, which are with the acquisition field strengths of 4.7 Tesla, 9.4 Tesla and 17.6 Tesla, respectively. On one hand, we compare the results of bias correction with N3 and N4 in terms of the coefficient of variations on 20 different tissues of rodent brain. On the other hand, the results of brain extraction are compared against manually segmented gold standards, BET, BSE and 3-D PCNN based on a number of metrics. With the high accuracy and efficiency, our proposed method can facilitate automatic processing of large-scale brain studies.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

PubMed

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

Spatiotemporal change of sky polarization during the total solar eclipse on 29 March 2006 in Turkey: polarization patterns of the eclipsed sky observed by full-sky imaging polarimetry.

PubMed

Sipocz, Brigitta; Hegedüs, Ramón; Kriska, György; Horváth, Gábor

2008-12-01

Using 180 degrees field-of-view (full-sky) imaging polarimetry, we measured the spatiotemporal change of the polarization of skylight during the total solar eclipse on 29 March 2006 in Turkey. We present our observations here on the temporal variation of the celestial patterns of the degree p and angle alpha of linear polarization of the eclipsed sky measured in the red (650 nm), green (550 nm), and blue (450 nm) parts of the spectrum. We also report on the temporal and spectral change of the positions of neutral (unpolarized, p = 0) points, and points with local minima or maxima of p of the eclipsed sky. Our results are compared with the observations performed by the same polarimetric technique during the total solar eclipse on 11 August 1999 in Hungary. Practically the same characteristics of celestial polarization were encountered during both eclipses. This shows that the observed polarization phenomena of the eclipsed sky may be general.

Radial Variations in the Io Plasma Torus during the Cassini Era

NASA Technical Reports Server (NTRS)

Delamere, P. A.; Bagenal, F.; Steffl, A.

2005-01-01

A radial scan through the midnight sector of the Io plasma torus was made by the Cassini Ultraviolet Imaging Spectrograph on 14 January 2001, shortly after closest approach to Jupiter. From these data, Steffl et al. (2004a) derived electron temperature, plasma composition (ion mixing ratios), and electron column density as a function of radius from L = 6 to 0 as well as the total luminosity. We have advanced our homogeneous model of torus physical chemistry (Delamere and Bagenal, 2003) to include latitudinal and radial variations in a manner similar to the two-dimensional model by Schreier et al. (1998). The model variables include: (1) neutral source rate, (2) radial transport coefficient, (3) the hot electron fraction, (4) hot electron temperature, and (5) the neutral O/S ratio. The radial variation of parameters 1-4 are described by simple power laws, making a total of nine parameters. We have explored the sensitivity of the model results to variations in these parameters and compared the best fit with previous Voyager era models (schreier et al., 1998), galileo data (Crary et al., 1998), and Cassini observations (steffl et al., 2004a). We find that radial variations during the Cassini era are consistent with a neutral source rate of 700-1200 kg/s, an integrated transport time from L = 6 to 9 of 100-200 days, and that the core electron temperature is largely determined by a spatially and temporally varying superthermal electron population.

Coherent seasonal, annual, and quasi-biennial variations in ionospheric tidal/SPW amplitudes

NASA Astrophysics Data System (ADS)

Chang, Loren C.; Sun, Yan-Yi; Yue, Jia; Wang, Jack Chieh; Chien, Shih-Han

2016-07-01

In this study, we examine the coherent spatial and temporal modes dominating the variation of selected ionospheric tidal and stationary planetary wave (SPW) signatures from 2007 to 2013 FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) total electron content observations using multidimensional ensemble empirical mode decomposition (MEEMD) from the Hilbert-Huang Transform. We examine the DW1, SW2, DE3, and SPW4 components, which are driven by a variety of in situ and vertical coupling sources. The intrinsic mode functions (IMFs) resolved by MEEMD analysis allows for the isolation of the dominant modes of variability for prominent ionospheric tidal/SPW signatures in a manner not previously used, allowing the effects of specific drivers to be examined individually. The time scales of the individual IMFs isolated for all tidal/SPW signatures correspond to a semiannual variation at equatorial ionization anomaly (EIA) latitudes maximizing at the equinoxes, as well as annual oscillations at the EIA crests and troughs. All tidal/SPW signatures show one IMF isolating an ionospheric quasi-biennial oscillation (QBO) in the equatorial latitudes maximizing around January of odd-numbered years. This total electron content QBO variation is in phase with a similar QBO variation isolated in both the Global Ultraviolet Imager (GUVI) zonal mean column O/N2 density ratio (ΣO/N2) and the F10.7 solar radio flux index around solar maximum, while showing temporal variation more similar to that of GUVI ΣO/N2 during the time around the 2008/2009 extended solar minimum. These results point to both quasi-biennial variations in solar irradiance and thermosphere/ionosphere composition as a generation mechanism for the ionospheric QBO.

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Point spread functions and deconvolution of ultrasonic images.

PubMed

Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten

2015-03-01

This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.

MO-FG-202-01: A Fast Yet Sensitive EPID-Based Real-Time Treatment Verification System

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

Ahmad, M; Nourzadeh, H; Neal, B

2016-06-15

Purpose: To create a real-time EPID-based treatment verification system which robustly detects treatment delivery and patient attenuation variations. Methods: Treatment plan DICOM files sent to the record-and-verify system are captured and utilized to predict EPID images for each planned control point using a modified GPU-based digitally reconstructed radiograph algorithm which accounts for the patient attenuation, source energy fluence, source size effects, and MLC attenuation. The DICOM and predicted images are utilized by our C++ treatment verification software which compares EPID acquired 1024×768 resolution frames acquired at ∼8.5hz from Varian Truebeam™ system. To maximize detection sensitivity, image comparisons determine (1) ifmore » radiation exists outside of the desired treatment field; (2) if radiation is lacking inside the treatment field; (3) if translations, rotations, and magnifications of the image are within tolerance. Acquisition was tested with known test fields and prior patient fields. Error detection was tested in real-time and utilizing images acquired during treatment with another system. Results: The computational time of the prediction algorithms, for a patient plan with 350 control points and 60×60×42cm^3 CT volume, is 2–3minutes on CPU and <27 seconds on GPU for 1024×768 images. The verification software requires a maximum of ∼9ms and ∼19ms for 512×384 and 1024×768 resolution images, respectively, to perform image analysis and dosimetric validations. Typical variations in geometric parameters between reference and the measured images are 0.32°for gantry rotation, 1.006 for scaling factor, and 0.67mm for translation. For excess out-of-field/missing in-field fluence, with masks extending 1mm (at isocenter) from the detected aperture edge, the average total in-field area missing EPID fluence was 1.5mm2 the out-of-field excess EPID fluence was 8mm^2, both below error tolerances. Conclusion: A real-time verification software, with EPID images prediction algorithm, was developed. The system is capable of performing verifications between frames acquisitions and identifying source(s) of any out-of-tolerance variations. This work was supported in part by Varian Medical Systems.« less

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

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

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu

2014-05-15

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical propertiesmore » of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less

MO-AB-BRA-08: Rapid Treatment Field Uniformity Optimization for Total Skin Electron Beam Therapy Using Cherenkov Imaging

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

Andreozzi, J; Zhang, R; Glaser, A

Purpose: To evaluate treatment field heterogeneity resulting from gantry angle choice in total skin electron beam therapy (TSEBT) following a modified Stanford dual-field technique, and determine a relationship between source to surface distance (SSD) and optimized gantry angle spread. Methods: Cherenkov imaging was used to image 62 treatment fields on a sheet of 1.2m x 2.2m x 1.2cm polyethylene following standard TSEBT setup at our institution (6 MeV, 888 MU/min, no spoiler, SSD=441cm), where gantry angles spanned from 239.5° to 300.5° at 1° increments. Average Cherenkov intensity and coefficient of variation in the region of interest were compared for themore » set of composite Cherenkov images created by summing all unique combinations of angle pairs to simulate dual-field treatment. The angle pair which produced the lowest coefficient of variation was further studied using an ionization chamber. The experiment was repeated at SSD=300cm, and SSD=370.5cm. Cherenkov imaging was also implemented during TSEBT of three patients. Results: The most uniform treatment region from a symmetric angle spread was achieved using gantry angles +/−17.5° about the horizontal axis at SSD=441cm, +/−18.5° at SSD=370.5cm, and +/−19.5° at SSD=300cm. Ionization chamber measurements comparing the original treatment spread (+/−14.5°) and the optimized angle pair (+/−17.5°) at SSD=441cm showed no significant deviation (r=0.999) in percent depth dose curves, and chamber measurements from nine locations within the field showed an improvement in dose uniformity from 24.41% to 9.75%. Ionization chamber measurements correlated strongly (r=0.981) with Cherenkov intensity measured concurrently on the flat Plastic Water phantom. Patient images and TLD results also showed modest uniformity improvements. Conclusion: A decreasing linear relationship between optimal angle spread and SSD was observed. Cherenkov imaging offers a new method of rapidly analyzing and optimizing TSEBT setup geometry by providing a 2D image of the treatment plane as a sum of the two fields. This study has been funded by NIH grants R21EB17559 and R01CA109558 as well as Norris Cotton Cancer Center Pilot funding.« less

MRI of articular cartilage at microscopic resolution

PubMed Central

Xia, Y.

2013-01-01

This review briefly summarises some of the definitive studies of articular cartilage by microscopic MRI (µMRI) that were conducted with the highest spatial resolutions. The article has four major sections. The first section introduces the cartilage tissue, MRI and µMRI, and the concept of image contrast in MRI. The second section describes the characteristic profiles of three relaxation times (T1, T2 and T1ρ) and self-diffusion in healthy articular cartilage. The third section discusses several factors that can influence the visualisation of articular cartilage and the detection of cartilage lesion by MRI and µMRI. These factors include image resolution, image analysis strategies, visualisation of the total tissue, topographical variations of the tissue properties, surface fibril ambiguity, deformation of the articular cartilage, and cartilage lesion. The final section justifies the values of multidisciplinary imaging that correlates MRI with other technical modalities, such as optical imaging. Rather than an exhaustive review to capture all activities in the literature, the studies cited in this review are merely illustrative. PMID:23610697

A model-based reconstruction for undersampled radial spin echo DTI with variational penalties on the diffusion tensor

PubMed Central

Knoll, Florian; Raya, José G; Halloran, Rafael O; Baete, Steven; Sigmund, Eric; Bammer, Roland; Block, Tobias; Otazo, Ricardo; Sodickson, Daniel K

2015-01-01

Radial spin echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled DTI. A model-based reconstruction implicitly exploits redundancies in the diffusion weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a Total Variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (3 and 2 volunteers, respectively). Evaluation of the new approach was conducted by comparing the results to reconstructions performed with gridding, combined parallel imaging and compressed sensing, and a recently proposed model-based approach. The experiments demonstrated improvement in terms of reduction of noise and streaking artifacts in the quantitative parameter maps as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin echo diffusion tensor imaging without degrading parameter quantification and/or SNR. PMID:25594167

Single Transducer Ultrasonic Imaging Method that Eliminates the Effect of Plate Thickness Variation in the Image

NASA Technical Reports Server (NTRS)

Roth, Don J.

1996-01-01

This article describes a single transducer ultrasonic imaging method that eliminates the effect of plate thickness variation in the image. The method thus isolates ultrasonic variations due to material microstructure. The use of this method can result in significant cost savings because the ultrasonic image can be interpreted correctly without the need for machining to achieve precise thickness uniformity during nondestructive evaluations of material development. The method is based on measurement of ultrasonic velocity. Images obtained using the thickness-independent methodology are compared with conventional velocity and c-scan echo peak amplitude images for monolithic ceramic (silicon nitride), metal matrix composite and polymer matrix composite materials. It was found that the thickness-independent ultrasonic images reveal and quantify correctly areas of global microstructural (pore and fiber volume fraction) variation due to the elimination of thickness effects. The thickness-independent ultrasonic imaging method described in this article is currently being commercialized under a cooperative agreement between NASA Lewis Research Center and Sonix, Inc.

Positioning accuracy and daily dose assessment for prostate cancer treatment using in-room CT image guidance at a proton therapy facility.

PubMed

Maeda, Yoshikazu; Sato, Yoshitaka; Minami, Hiroki; Yasukawa, Yutaka; Yamamoto, Kazutaka; Tamamura, Hiroyasu; Shibata, Satoshi; Bou, Sayuri; Sasaki, Makoto; Tameshige, Yuji; Kume, Kyo; Ooto, Hiroshi; Kasahara, Shigeru; Shimizu, Yasuhiro; Saga, Yusuke; Omoya, Akira; Saitou, Makoto

2018-05-01

To evaluate the effectiveness of CT image-guided proton radiotherapy for prostate cancer by analyzing the positioning uncertainty and assessing daily dose change due to anatomical variations. Patients with prostate cancer were treated by opposed lateral proton beams based on a passive scattering method using an in-room CT image-guided system. The system employs a single couch for both CT scanning and beam delivery. The patient was positioned by matching the boundary between the prostate and the rectum's anterior region identified in the CT images to the corresponding boundary in the simulator images after bone matching. We acquired orthogonal kV x-ray images after couch movement and confirmed the body position by referring to the bony structure prior to treatment. In offline analyses, we contoured the targeted anatomical structures on 375 sets of daily in-room CT images for 10 patients. The uncertainty of the image-matching procedure was evaluated using the prostate contours and actual couch corrections. We also performed dose calculations using the same set of CT images, and evaluated daily change of dose-volume histograms (DVHs) to compare the effectiveness of the treatment using prostate matching to the bone-matching procedure. The isocenter shifts by prostate matching after bone matching were 0.5 ± 1.8 and -0.8 ± 2.6 mm along the superior-inferior (SI) and anterior-posterior (AP) directions, respectively. The body movement errors (σ) after couch movement were 0.7, 0.5, and 0.3 mm along the lateral, SI and AP direction, respectively, for 30 patients. The estimated errors (σ) in the prostate matching were 1.0 and 1.3 mm, and, in conjunction with the movement errors, the total positioning uncertainty was estimated to be 1.0 and 1.4 mm along the SI and AP directions, respectively. Daily DVH analyses showed that in the prostate matching, 98.7% and 86.1% of the total 375 irradiations maintained a dose condition of V 95%  > 95% for the prostate and a dose constraint of V 77%  < 18% for the rectum, whereas 90.4% and 66.1% of the total irradiations did so when bone matching was used. The dose constraint of the rectum and dose coverage of the prostate were better maintained by prostate matching than bone matching (P < 0.001). The daily variation in the dose to the seminal vesicles (SVs) was large, and only 40% of the total irradiations maintained the initial planned values of V 95% for high-risk treatment. Nevertheless, the deviations from the original value were -4 ± 7% and -5 ± 11% in the prostate and bone matching, respectively, and a better dose coverage of the SV was achieved by the prostate matching. The correction of repositioning along the AP and SI direction from conventional bone matching in CT image-guided proton therapy was found to be effective to maintain the dose constraint of the rectum and the dose coverage of the prostate. This work indicated that prostate cancer treatment by prostate matching using CT image guidance may be effective to reduce the rectal complications and achieve better tumor control of the prostate. However, an adaptive approach is desirable to maintain better dose coverage of the SVs. © 2018 American Association of Physicists in Medicine.

Dosimetric impact of daily setup variations during treatment of canine nasal tumors using intensity-modulated radiation therapy.

PubMed

Deveau, Michael A; Gutiérrez, Alonso N; Mackie, Thomas R; Tomé, Wolfgang A; Forrest, Lisa J

2010-01-01

Intensity-modulated radiation therapy (IMRT) can be employed to yield precise dose distributions that tightly conform to targets and reduce high doses to normal structures by generating steep dose gradients. Because of these sharp gradients, daily setup variations may have an adverse effect on clinical outcome such that an adjacent normal structure may be overdosed and/or the target may be underdosed. This study provides a detailed analysis of the impact of daily setup variations on optimized IMRT canine nasal tumor treatment plans when variations are not accounted for due to the lack of image guidance. Setup histories of ten patients with nasal tumors previously treated using helical tomotherapy were replanned retrospectively to study the impact of daily setup variations on IMRT dose distributions. Daily setup shifts were applied to IMRT plans on a fraction-by-fraction basis. Using mattress immobilization and laser alignment, mean setup error magnitude in any single dimension was at least 2.5 mm (0-10.0 mm). With inclusions of all three translational coordinates, mean composite offset vector was 5.9 +/- 3.3 mm. Due to variations, a loss of equivalent uniform dose for target volumes of up to 5.6% was noted which corresponded to a potential loss in tumor control probability of 39.5%. Overdosing of eyes and brain was noted by increases in mean normalized total dose and highest normalized dose given to 2% of the volume. Findings suggest that successful implementation of canine nasal IMRT requires daily image guidance to ensure accurate delivery of precise IMRT distributions when non-rigid immobilization techniques are utilized. Unrecognized geographical misses may result in tumor recurrence and/or radiation toxicities to the eyes and brain.

DOSIMETRIC IMPACT OF DAILY SETUP VARIATIONS DURING TREATMENT OF CANINE NASAL TUMORS USING INTENSITY-MODULATED RADIATION THERAPY

PubMed Central

Deveau, Michael A.; Gutiérrez, Alonso N.; Mackie, Thomas R.; Tomé, Wolfgang A.; Forrest, Lisa J.

2009-01-01

Intensity-modulated radiation therapy (IMRT) can be employed to yield precise dose distributions that tightly conform to targets and reduce high doses to normal structures by generating steep dose gradients. Because of these sharp gradients, daily setup variations may have an adverse effect on clinical outcome such that an adjacent normal structure may be overdosed and/or the target may be underdosed. This study provides a detailed analysis of the impact of daily setup variations on optimized IMRT canine nasal tumor treatment plans when variations are not accounted for due to the lack of image guidance. Setup histories of ten patients with nasal tumors previously treated using helical tomotherapy were replanned retrospectively to study the impact of daily setup variations on IMRT dose distributions. Daily setup shifts were applied to IMRT plans on a fraction-by-fraction basis. Using mattress immobilization and laser alignment, mean setup error magnitude in any single dimension was at least 2.5mm (0-10.0mm). With inclusions of all three translational coordinates, mean composite offset vector was 5.9±3.3mm. Due to variations, a loss of equivalent uniform dose (EUD) for target volumes of up to 5.6% was noted which corresponded to a potential loss in TCP of 39.5%. Overdosing of eyes and brain was noted by increases in mean normalized total dose (NTDmean) and highest normalized dose given to 2% of the volume (NTD2%). Findings suggest that successful implementation of canine nasal IMRT requires daily image guidance to ensure accurate delivery of precise IMRT distributions when non-rigid immobilization techniques are utilized. Unrecognized geographical misses may result in tumor recurrence and/or radiation toxicities to the eyes and brain. PMID:20166402

Geographic variation in cancer-related imaging: Veterans Affairs health care system versus Medicare.

PubMed

McWilliams, J Michael; Dalton, Jesse B; Landrum, Mary Beth; Frakt, Austin B; Pizer, Steven D; Keating, Nancy L

2014-12-02

Geographic variations in use of medical services have been interpreted as indirect evidence of wasteful care. Less overuse of services, however, may not be reliably associated with less geographic variation. To compare average use and geographic variation in use of cancer-related imaging between fee-for-service Medicare and the Department of Veterans Affairs (VA) health care system. Observational analysis of cancer-related imaging from 2003 to 2005 using Medicare and VA utilization data linked to cancer registry data. Multilevel models, adjusted for sociodemographic and tumor characteristics, were used to estimate mean differences in annual imaging use between cohorts of Medicare and VA patients within geographic areas and variation in use across areas for each cohort. 40 hospital referral regions. Older men with lung, colorectal, or prostate cancer, including 34,475 traditional Medicare beneficiaries (Medicare cohort) and 6835 VA patients (VA cohort). Per-patient count of imaging studies for which lung, colorectal, or prostate cancer was the primary diagnosis (each study weighted by a standardized price), and a direct measure of overuse-advanced imaging for prostate cancer at low risk for metastasis. Adjusted annual use of cancer-related imaging was lower in the VA cohort than in the Medicare cohort (price-weighted count, $197 vs. $379 per patient; P < 0.001), as was annual use of advanced imaging for prostate cancer at low risk for metastasis ($41 vs. $117 per patient; P < 0.001). Geographic variation in cancer-related imaging use was similar in magnitude in the VA and Medicare cohorts. Observational study design. Use of cancer-related imaging was lower in the VA health care system than in fee-for-service Medicare, but lower use was not associated with less geographic variation. Geographic variation in service use may not be a reliable indicator of the extent of overuse. Doris Duke Charitable Foundation and Department of Veterans Affairs Office of Policy and Planning.

InP-based Geiger-mode avalanche photodiode arrays for three-dimensional imaging at 1.06 μm

NASA Astrophysics Data System (ADS)

Itzler, Mark A.; Entwistle, Mark; Owens, Mark; Jiang, Xudong; Patel, Ketan; Slomkowski, Krystyna; Koch, Tim; Rangwala, Sabbir; Zalud, Peter F.; Yu, Young; Tower, John; Ferraro, Joseph

2009-05-01

We report on the development of 32 x 32 focal plane arrays (FPAs) based on InGaAsP/InP Geiger-mode avalanche photodiodes (GmAPDs) designed for use in three-dimensional (3-D) laser radar imaging systems at 1064 nm. To our knowledge, this is the first realization of FPAs for 3-D imaging that employ a planar-passivated buried-junction InP-based GmAPD device platform. This development also included the design and fabrication of custom readout integrate circuits (ROICs) to perform avalanche detection and time-of-flight measurements on a per-pixel basis. We demonstrate photodiode arrays (PDAs) with a very narrow breakdown voltage distribution width of 0.34 V, corresponding to a breakdown voltage total variation of less than +/- 0.2%. At an excess bias voltage of 3.3 V, which provides 40% pixel-level single photon detection efficiency, we achieve average dark count rates of 2 kHz at an operating temperature of 248 K. We present the characterization of optical crosstalk induced by hot carrier luminescence during avalanche events, where we show that the worst-case crosstalk probability per pixel, which occurs for nearest neighbors, has a value of less than 1.6% and exhibits anisotropy due to isolation trench etch geometry. To demonstrate the FPA response to optical density variations, we show a simple image of a broadened optical beam.

HST UV Images of Saturn's Aurora Coordinated with Cassini Solar Wind Measurements

NASA Astrophysics Data System (ADS)

Clarke, John

2003-07-01

A key measurement goal of the Cassini mission to Saturn is to obtain simultaneous solar wind and auroral imaging measurements in a campaign scheduled for Jan. 2004. Cassini will measure the solar wind approaching Saturn continuously from 9 Jan. - 6 Feb., but not closer to Saturn due to competing spacecraft orientation constraints. The only system capable of imaging Saturn's aurora in early 2004 will be HST. In this community DD proposal we request the minimum HST time needed to support the Cassini mission during the solar wind campaign with UV images of Saturn's aurora. Saturn's magnetosphere is intermediate between the "closed" Jovian case with large internal sources of plasma and the Earth's magnetosphere which is open to solar wind interactions. Saturn's aurora has been shown to exhibit large temporal variations in brightness and morphology from Voyager and HST observations. Changes of auroral emitted power exceeding one order of magnitude, dawn brightenings, and latitudinal motions of the main oval have all been observed. Lacking knowledge of solar wind conditions near Saturn, it has not been possible to determine its role in Saturn's auroral processes, nor the mechanisms controlling the auroral precipitation. During Cassini's upcoming approach to Saturn there will be a unique opportunity to answer these questions. We propose to image one complete rotation of Saturn to determine the corotational and longitudinal dependences of the auroral activity. We will then image the active sector of Saturn once every two days for a total coverage of 26 days during the Cassini campaign to measure the upstream solar wind parameters. This is the minimum coverage needed to ensure observations of the aurora under solar wind pressure variations of more than a factor of two, based on the solar wind pressure variations measured by Voyager 2 near Saturn on the declining phase of solar activity. The team of proposers has carried out a similar coordinated observing campaign of Jupiter during the Cassini flyby, resulting in a set of papers and HST images on the cover of Nature on 28 February 2002.

Diurnal Variation of Tropical Ice Cloud Microphysics inferred from Global Precipitation Measurement Microwave Imager (GPM-GMI)'s Polarimetric Measurement

NASA Astrophysics Data System (ADS)

Gong, J.; Zeng, X.; Wu, D. L.; Li, X.

2017-12-01

Diurnal variation of tropical ice cloud has been well observed and examined in terms of the area of coverage, occurring frequency, and total mass, but rarely on ice microphysical parameters (habit, size, orientation, etc.) because of lack of direct measurements of ice microphysics on a high temporal and spatial resolutions. This accounts for a great portion of the uncertainty in evaluating ice cloud's role on global radiation and hydrological budgets. The design of Global Precipitation Measurement (GPM) mission's procession orbit gives us an unprecedented opportunity to study the diurnal variation of ice microphysics on the global scale for the first time. Dominated by cloud ice scattering, high-frequency microwave polarimetric difference (PD, namely the brightness temperature difference between vertically- and horizontally-polarized paired channel measurements) from the GPM Microwave Imager (GMI) has been proven by our previous study to be very valuable to infer cloud ice microphysical properties. Using one year of PD measurements at 166 GHz, we found that cloud PD exhibits a strong diurnal cycle in the tropics (25S-25N). The peak PD amplitude varies as much as 35% over land, compared to only 6% over ocean. The diurnal cycle of the peak PD value is strongly anti-correlated with local ice cloud occurring frequency and the total ice mass with a leading period of 3 hours for the maximum correlation. The observed PD diurnal cycle can be explained by the change of ice crystal axial ratio. Using a radiative transfer model, we can simulate the observed 166 GHz PD-brightness temperature curve as well as its diurnal variation using different axial ratio values, which can be caused by the diurnal variation of ice microphysical properties including particle size, percentage of horizontally-aligned non-spherical particles, and ice habit. The leading of the change of PD ahead of ice cloud mass and occurring frequency implies the important role microphysics play in the formation and dissipation processes of ice clouds and frozen precipitations.

The ``False Colour'' Problem

NASA Astrophysics Data System (ADS)

Serra, Jean

The emergence of new data in multidimensional function lattices is studied. A typical example is the apparition of false colours when (R,G,B) images are processed. Two lattice models are specially analysed. Firstly, one considers a mixture of total and marginal orderings where the variations of some components are governed by other ones. This constraint yields the “pilot lattices”. The second model is a cylindrical polar representation in n dimensions. In this model, data that are distributed on the unit sphere of n - 1 dimensions need to be ordered. The proposed orders, and lattices are specific to each image. They are obtained from Voronoi tesselation of the unit sphere The case of four dimensions is treated in detail and illustrated.

TU-CD-BRA-12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

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

Li, L; Tan, S; Lu, W

Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was usedmore » on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant No.61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

The Total Variation Regularized L1 Model for Multiscale Decomposition

DTIC Science & Technology

2006-01-01

L1 fidelity term, and presented impressive and successful applications of the TV-L1 model to impulsive noise removal and outlier identification. She...used to filter 1D signal [3], to remove impulsive (salt-n- pepper) noise [35], to extract textures from natural images [45], to remove varying...34, 35, 36] discovery of the usefulness of this model for removing impul- sive noise , Chan and Esedoglu’s [17] further analysis of this model, and a

Inter-Vendor Reproducibility of Pseudo-Continuous Arterial Spin Labeling at 3 Tesla

PubMed Central

Mutsaerts, Henri J. M. M.; Steketee, Rebecca M. E.; Heijtel, Dennis F. R.; Kuijer, Joost P. A.; van Osch, Matthias J. P.; Majoie, Charles B. L. M.; Smits, Marion; Nederveen, Aart J.

2014-01-01

Purpose Prior to the implementation of arterial spin labeling (ASL) in clinical multi-center studies, it is important to establish its status quo inter-vendor reproducibility. This study evaluates and compares the intra- and inter-vendor reproducibility of pseudo-continuous ASL (pCASL) as clinically implemented by GE and Philips. Material and Methods 22 healthy volunteers were scanned twice on both a 3T GE and a 3T Philips scanner. The main difference in implementation between the vendors was the readout module: spiral 3D fast spin echo vs. 2D gradient-echo echo-planar imaging respectively. Mean and variation of cerebral blood flow (CBF) were compared for the total gray matter (GM) and white matter (WM), and on a voxel-level. Results Whereas the mean GM CBF of both vendors was almost equal (p = 1.0), the mean WM CBF was significantly different (p<0.01). The inter-vendor GM variation did not differ from the intra-vendor GM variation (p = 0.3 and p = 0.5 for GE and Philips respectively). Spatial inter-vendor CBF and variation differences were observed in several GM regions and in the WM. Conclusion These results show that total GM CBF-values can be exchanged between vendors. For the inter-vendor comparison of GM regions or WM, these results encourage further standardization of ASL implementation among vendors. PMID:25090654

Inter-vendor reproducibility of pseudo-continuous arterial spin labeling at 3 Tesla.

PubMed

Mutsaerts, Henri J M M; Steketee, Rebecca M E; Heijtel, Dennis F R; Kuijer, Joost P A; van Osch, Matthias J P; Majoie, Charles B L M; Smits, Marion; Nederveen, Aart J

2014-01-01

Prior to the implementation of arterial spin labeling (ASL) in clinical multi-center studies, it is important to establish its status quo inter-vendor reproducibility. This study evaluates and compares the intra- and inter-vendor reproducibility of pseudo-continuous ASL (pCASL) as clinically implemented by GE and Philips. 22 healthy volunteers were scanned twice on both a 3T GE and a 3T Philips scanner. The main difference in implementation between the vendors was the readout module: spiral 3D fast spin echo vs. 2D gradient-echo echo-planar imaging respectively. Mean and variation of cerebral blood flow (CBF) were compared for the total gray matter (GM) and white matter (WM), and on a voxel-level. Whereas the mean GM CBF of both vendors was almost equal (p = 1.0), the mean WM CBF was significantly different (p<0.01). The inter-vendor GM variation did not differ from the intra-vendor GM variation (p = 0.3 and p = 0.5 for GE and Philips respectively). Spatial inter-vendor CBF and variation differences were observed in several GM regions and in the WM. These results show that total GM CBF-values can be exchanged between vendors. For the inter-vendor comparison of GM regions or WM, these results encourage further standardization of ASL implementation among vendors.

Cerebellum volume in high-risk offspring from multiplex alcohol dependence families: Association with allelic variation in GABRA2 and BDNF

PubMed Central

Hill, Shirley Y.; Wang, Shuhui; Carter, Howard; Tessner, Kevin; Holmes, Brian; McDermott, Michael; Zezza, Nicholas; Stiffler, Scott

2012-01-01

Offspring from families with multiple cases of alcohol dependence have a greater likelihood of developing alcohol dependence (AD) and related substance use disorders. Greater susceptibility for developing these disorders may be related to structural differences in brain circuits that influence the salience of rewards or modify the efficiency of information processing and AD susceptibility. We examined the cerebellum of 71 adolescent/young adult high-risk (HR) offspring from families with multiple cases of alcohol dependence (multiplex families), and 60 low-risk (LR) controls with no family history of alcohol or drug dependence who were matched for age, gender, socioeconomic status and IQ, with attention given to possible effects of personal use of substances and maternal use during pregnancy. Magnetic resonance images were acquired on a General Electric 1.5-Tesla scanner and manually traced (BRAINS2) blind to clinical information. GABRA2 and BDNF variation were tested for their association with cerebellar volumes. High-risk offspring from multiplex AD families showed greater total volume of the cerebellum and total gray matter (GM), in comparison with LR controls. An interaction between allelic variation in GABRA2 and BDNF genes was associated with GM volumes, suggesting that inherited variation in these genes may promote early developmental differences in neuronal proliferation of the cerebellum. PMID:22047728

An estimate of the suspended particulate matter (SPM) transport in the southern North Sea using SeaWiFS images, in situ measurements and numerical model results

NASA Astrophysics Data System (ADS)

Fettweis, Michael; Nechad, Bouchra; Van den Eynde, Dries

2007-06-01

A study is presented where satellite images (SeaWiFS), in situ measurements (tidal cycle and snapshot) and a 2D hydrodynamic numerical model have been combined to calculate the long term SPM (Suspended Particulate Matter) transport through the Dover Strait and in the southern North Sea. The total amount of SPM supplied to the North Sea through the Dover Strait is estimated to be 31.74×10 6 t. The satellite images provide synoptic views of SPM concentration distribution but do not take away the uncertainty of SPM transport calculation. This is due to the fact that SPM concentration varies as a function of tide, wind, spring-neap tidal cycles and seasons. The short term variations (tidal, spring-neap tidal cycle) have not been found in the satellite images, however seasonal variations are clearly visible. Furthermore the SPM concentration in the satellite images is generally lower than in the in situ measurements. The representativness of SPM concentration maps derived from satellites for calculating long term transports has therefore been investigated by comparing the SPM concentration variability from the in situ measurements with those of the remote sensing data. The most important constraints of satellite images are related to the fact that satellite data is evidence of clear sky conditions, whereas in situ measurements from a vessel can be carried out also during rougher meteorological conditions and that due to the too low time resolution of the satellite images the SPM concentration peaks are often missed. It is underlined that SPM concentration measurements should be carried out during at least one tidal cycle in high turbidity areas to obtain representative values of SPM concentration.

Reconstruction of total solar irradiance 1974-2009

NASA Astrophysics Data System (ADS)

Ball, W. T.; Unruh, Y. C.; Krivova, N. A.; Solanki, S.; Wenzler, T.; Mortlock, D. J.; Jaffe, A. H.

2012-05-01

Context. The study of variations in total solar irradiance (TSI) is important for understanding how the Sun affects the Earth's climate. Aims: Full-disk continuum images and magnetograms are now available for three full solar cycles. We investigate how modelled TSI compares with direct observations by building a consistent modelled TSI dataset. The model, based only on changes in the photospheric magnetic flux can then be tested on rotational, cyclical and secular timescales. Methods: We use Kitt Peak and SoHO/MDI continuum images and magnetograms in the SATIRE-S model to reconstruct TSI over cycles 21-23. To maximise independence from TSI composites, SORCE/TIM TSI data are used to fix the one free parameter of the model. We compare and combine the separate data sources for the model to estimate an uncertainty on the reconstruction and prevent any additional free parameters entering the model. Results: The reconstruction supports the PMOD composite as being the best historical record of TSI observations, although on timescales of the solar rotation the IRMB composite provides somewhat better agreement. Further to this, the model is able to account for 92% of TSI variations from 1978 to 2009 in the PMOD composite and over 96% during cycle 23. The reconstruction also displays an inter-cycle, secular decline of 0.20+0.12-0.09 W m-2 between cycle 23 minima, in agreement with the PMOD composite. Conclusions: SATIRE-S is able to recreate TSI observations on all timescales of a day and longer over 31 years from 1978. This is strong evidence that changes in photospheric magnetic flux alone are responsible for almost all solar irradiance variations over the last three solar cycles.

Segmentation of knee MRI using structure enhanced local phase filtering

NASA Astrophysics Data System (ADS)

Lim, Mikhiel; Hacihaliloglu, Ilker

2016-03-01

The segmentation of bone surfaces from magnetic resonance imaging (MRI) data has applications in the quanti- tative measurement of knee osteoarthritis, surgery planning for patient specific total knee arthroplasty and its subsequent fabrication of artificial implants. However, due to the problems associated with MRI imaging such as low contrast between bone and surrounding tissues, noise, bias fields, and the partial volume effect, segmentation of bone surfaces continues to be a challenging operation. In this paper, a new framework is presented for the enhancement of knee MRI scans prior to segmentation in order to obtain high contrast bone images. During the first stage, a new contrast enhanced relative total variation (RTV) regularization method is used in order to remove textural noise from the bone structures and surrounding soft tissue interface. This salient bone edge information is further enhanced using a sparse gradient counting method based on L0 gradient minimization, which globally controls how many non-zero gradients are resulted in order to approximate prominent bone structures in a structure-sparsity-management manner. The last stage of the framework involves incorporation of local phase bone boundary information in order to provide an intensity invariant enhancement of contrast between the bone and surrounding soft tissue. The enhanced images are segmented using a fast random walker algorithm. Validation against expert segmentation was performed on 10 clinical knee MRI images, and achieved a mean dice similarity coefficient (DSC) of 0.975.

A digital image-based method for determining of total acidity in red wines using acid-base titration without indicator.

PubMed

Tôrres, Adamastor Rodrigues; Lyra, Wellington da Silva; de Andrade, Stéfani Iury Evangelista; Andrade, Renato Allan Navarro; da Silva, Edvan Cirino; Araújo, Mário César Ugulino; Gaião, Edvaldo da Nóbrega

2011-05-15

This work proposes the use of digital image-based method for determination of total acidity in red wines by means of acid-base titration without using an external indicator or any pre-treatment of the sample. Digital images present the colour of the emergent radiation which is complementary to the radiation absorbed by anthocyanines present in wines. Anthocyanines change colour depending on the pH of the medium, and from the variation of colour in the images obtained during titration, the end point can be localized with accuracy and precision. RGB-based values were employed to build titration curves, and end points were localized by second derivative curves. The official method recommends potentiometric titration with a NaOH standard solution, and sample dilution until the pH reaches 8.2-8.4. In order to illustrate the feasibility of the proposed method, titrations of ten red wines were carried out. Results were compared with the reference method, and no statistically significant difference was observed between the results by applying the paired t-test at the 95% confidence level. The proposed method yielded more precise results than the official method. This is due to the trivariate nature of the measurements (RGB), associated with digital images. Copyright © 2011 Elsevier B.V. All rights reserved.

Variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction

NASA Astrophysics Data System (ADS)

Li, Shuo; Wang, Hui; Wang, Liyong; Yu, Xiangzhou; Yang, Le

2018-01-01

The uneven illumination phenomenon reduces the quality of remote sensing image and causes interference in the subsequent processing and applications. A variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction is proposed. The L1 norm and the L2 norm are adopted to constrain the textures and details of reflectance image and the smoothness of the illumination image, respectively. The problem of separating the illumination image from the reflectance image is transformed into the optimal solution of the variational model. In order to accelerate the solution, the split Bregman method is used to decompose the variational model into three subproblems, which are calculated by alternate iteration. Two groups of experiments are implemented on two synthetic images and three real remote sensing images. Compared with the variational Retinex method with single-norm constraint and the Mask method, the proposed method performs better in both visual evaluation and quantitative measurements. The proposed method can effectively eliminate the uneven illumination while maintaining the textures and details of the remote sensing image. Moreover, the proposed method using split Bregman method is more than 10 times faster than the method with the steepest descent method.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

NASA Astrophysics Data System (ADS)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

Conductivity map from scanning tunneling potentiometry.

PubMed

Zhang, Hao; Li, Xianqi; Chen, Yunmei; Durand, Corentin; Li, An-Ping; Zhang, X-G

2016-08-01

We present a novel method for extracting two-dimensional (2D) conductivity profiles from large electrochemical potential datasets acquired by scanning tunneling potentiometry of a 2D conductor. The method consists of a data preprocessing procedure to reduce/eliminate noise and a numerical conductivity reconstruction. The preprocessing procedure employs an inverse consistent image registration method to align the forward and backward scans of the same line for each image line followed by a total variation (TV) based image restoration method to obtain a (nearly) noise-free potential from the aligned scans. The preprocessed potential is then used for numerical conductivity reconstruction, based on a TV model solved by accelerated alternating direction method of multiplier. The method is demonstrated on a measurement of the grain boundary of a monolayer graphene, yielding a nearly 10:1 ratio for the grain boundary resistivity over bulk resistivity.

Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

PubMed

Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

2015-05-01

It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analyzing structural variations along strike in a deep-water thrust belt

NASA Astrophysics Data System (ADS)

Totake, Yukitsugu; Butler, Robert W. H.; Bond, Clare E.; Aziz, Aznan

2018-03-01

We characterize a deep-water fold-thrust arrays imaged by a high-resolution 3D seismic dataset in the offshore NW Borneo, Malaysia, to understand the kinematics behind spatial arrangement of structural variations throughout the fold-thrust system. The seismic volume used covers two sub-parallel fold trains associated with a series of fore-thrusts and back-thrusts. We measured fault heave, shortening value, fold geometries (forelimb dip, interlimb angle and crest depth) along strike in individual fold trains. Heave plot on strike projection allows to identify individual thrust segments showing semi-elliptical to triangular to bimodal patterns, and linkages of these segments. The linkage sites are marked by local minima in cumulative heave. These local heave minima are compensated by additional structures, such as small imbricate thrusts and tight folds indicated by large forelimb dip and small interlimb angle. Complementary profiles of the shortening amount for the two fold trains result in smoother gradient of total shortening across the structures. We interpret this reflects kinematic interaction between two fold-thrust trains. This type of along-strike variation analysis provides comprehensive understanding of a fold-thrust system and may provide an interpretative strategy for inferring the presence of complex multiple faults in less well-imaged parts of seismic volumes.

A stepwedge-based method for measuring breast density: observer variability and comparison with human reading

NASA Astrophysics Data System (ADS)

Diffey, Jenny; Berks, Michael; Hufton, Alan; Chung, Camilla; Verow, Rosanne; Morrison, Joanna; Wilson, Mary; Boggis, Caroline; Morris, Julie; Maxwell, Anthony; Astley, Susan

2010-04-01

Breast density is positively linked to the risk of developing breast cancer. We have developed a semi-automated, stepwedge-based method that has been applied to the mammograms of 1,289 women in the UK breast screening programme to measure breast density by volume and area. 116 images were analysed by three independent operators to assess inter-observer variability; 24 of these were analysed on 10 separate occasions by the same operator to determine intra-observer variability. 168 separate images were analysed using the stepwedge method and by two radiologists who independently estimated percentage breast density by area. There was little intra-observer variability in the stepwedge method (average coefficients of variation 3.49% - 5.73%). There were significant differences in the volumes of glandular tissue obtained by the three operators. This was attributed to variations in the operators' definition of the breast edge. For fatty and dense breasts, there was good correlation between breast density assessed by the stepwedge method and the radiologists. This was also observed between radiologists, despite significant inter-observer variation. Based on analysis of thresholds used in the stepwedge method, radiologists' definition of a dense pixel is one in which the percentage of glandular tissue is between 10 and 20% of the total thickness of tissue.

Reducing Variability in Orthogonal Reformatted Image Quality Associated With Axial Long-z-Axis CT Angiography.

PubMed

Stein, Erica B; Liu, Peter S; Kazerooni, Ella A; Barber, Karen; Davenport, Matthew S

2016-12-01

The objective of our study was to reduce variation in image quality of orthogonal reformatted images generated from long-z-axis CT angiography (CTA) studies of the upper and lower extremities. Upper and lower extremity CTA studies were targeted at a single health care system. A correctly performed CTA examination was defined as one that met the following three criteria: Sagittal and coronal reformats were obtained, a high-resolution matrix greater than 512 × 512 was used, and reformatted images were available in a distance-measurable format. Baseline data were collected from February 1, 2014, through September 30, 2014. Corrective actions were implemented during three consecutive plan-do-check-act (PDCA) cycles from October 1, 2014, through July 31, 2015, that addressed human, technical, and systematic variations. A 3-month maintenance period followed in which no intervention was performed. Longitudinal data were analyzed monthly using a statistical process control chart (p-chart). The total number of long-z-axis extremity CTA studies analyzed was as follows: 351 CTA studies were analyzed at baseline, 94 at the first PDCA cycle, 92 at the second PDCA cycle, 114 at the third PDCA cycle, and 138 during the maintenance period. The monthly rate of correctly performed studies ranged from 7% to 51% (mean, 38% ± 13% [SD]) during the baseline period, 32-59% (mean, 46% ± 14%) during the first PDCA cycle, 40-81% (mean, 61% ± 21%) during the second PDCA cycle, and 80-82% (mean, 81% ± 0.9%) during the third PDCA cycle. The monthly rate improved to 90-91% (mean, 91% ± 0.5%) during the maintenance period. The upper and lower control limits of the p-chart were upshifted after the second and third PDCA cycles. Correcting systematic and technical variations led to the greatest improvements in reformat accuracy. Obtaining consistently and correctly reformatted images from long-z-axis CTA studies is achievable using iterative PDCA cycles.

Effects of diurnal, lighting, and angle-of-incidence variation on anterior segment optical coherence tomography (AS-OCT) angle metrics.

PubMed

Akil, Handan; Dastiridou, Anna; Marion, Kenneth; Francis, Brian A; Chopra, Vikas

2017-03-23

First reported study to assess the effect of diurnal variation on anterior chamber angle measurements, as well as, to re-test the effects of lighting and angle-of-incidence variation on anterior chamber angle (ACA) measurements acquired by time-domain anterior segment optical coherence tomography (AS-OCT). A total of 30 eyes from 15 healthy, normal subjects underwent anterior chamber imaging using a Visante time-domain AS-OCT according to an IRB-approved protocol. For each eye, the inferior angle was imaged twice in the morning (8 am - 10 am) and then again in the afternoon (3 pm - 5 pm), under light meter-controlled conditions with ambient room lighting 'ON' and lights 'OFF', and at 5° angle of incidence increments. The ACA metrics measured for each eye were: angle opening distance (AOD, measured 500 and 750 μm anterior from scleral spur), the trabecular-iris-space area (TISA, measured 500 and 750 μm anterior from scleral spur), and scleral spur angle. Measurements were performed by masked, certified Reading Center graders using the Visante's Internal Measurement Tool. Differences in measurements between morning and afternoon, lighting variations, and angle of incidence were compared. Mean age of the participants was 31.2 years (range 23-58). Anterior chamber angle metrics did not differ significantly from morning to afternoon imaging, or when the angle of incidence was offset by 5° in either direction away from the inferior angle 6 o'clock position. (p-value 0.13-0.93). Angle metrics at the inferior corneal limbus, 6 o'clock position (IC270), with room lighting 'OFF', showed a significant decrease (p < 0.05) compared to room lighting 'ON'. There does not appear to be significant diurnal variation in AS-OCT parameters in normal individuals, but lighting conditions need to be strictly controlled since variation in lighting led to significant variability in AS-OCT parameters. No changes in ACA parameters were noted by varying the angle-of-incidence, which gives confidence in being able to perform longitudinal studies in approximately the same area (plus/minus 5° of original scan location).

Investigation of cone-beam CT image quality trade-off for image-guided radiation therapy

NASA Astrophysics Data System (ADS)

Bian, Junguo; Sharp, Gregory C.; Park, Yang-Kyun; Ouyang, Jinsong; Bortfeld, Thomas; El Fakhri, Georges

2016-05-01

It is well-known that projections acquired over an angular range slightly over 180° (so-called short scan) are sufficient for fan-beam reconstruction. However, due to practical imaging conditions (projection data and reconstruction image discretization, physical factors, and data noise), the short-scan reconstructions may have different appearances and properties from the full-scan (scans over 360°) reconstructions. Nevertheless, short-scan configurations have been used in applications such as cone-beam CT (CBCT) for head-neck-cancer image-guided radiation therapy (IGRT) that only requires a small field of view due to the potential reduced imaging time and dose. In this work, we studied the image quality trade-off for full, short, and full/short scan configurations with both conventional filtered-backprojection (FBP) reconstruction and iterative reconstruction algorithms based on total-variation (TV) minimization for head-neck-cancer IGRT. Anthropomorphic and Catphan phantoms were scanned at different exposure levels with a clinical scanner used in IGRT. Both visualization- and numerical-metric-based evaluation studies were performed. The results indicate that the optimal exposure level and number of views are in the middle range for both FBP and TV-based iterative algorithms and the optimization is object-dependent and task-dependent. The optimal view numbers decrease with the total exposure levels for both FBP and TV-based algorithms. The results also indicate there are slight differences between FBP and TV-based iterative algorithms for the image quality trade-off: FBP seems to be more in favor of larger number of views while the TV-based algorithm is more robust to different data conditions (number of views and exposure levels) than the FBP algorithm. The studies can provide a general guideline for image-quality optimization for CBCT used in IGRT and other applications.

GPU-accelerated compressed-sensing (CS) image reconstruction in chest digital tomosynthesis (CDT) using CUDA programming

NASA Astrophysics Data System (ADS)

Choi, Sunghoon; Lee, Haenghwa; Lee, Donghoon; Choi, Seungyeon; Shin, Jungwook; Jang, Woojin; Seo, Chang-Woo; Kim, Hee-Joung

2017-03-01

A compressed-sensing (CS) technique has been rapidly applied in medical imaging field for retrieving volumetric data from highly under-sampled projections. Among many variant forms, CS technique based on a total-variation (TV) regularization strategy shows fairly reasonable results in cone-beam geometry. In this study, we implemented the TV-based CS image reconstruction strategy in our prototype chest digital tomosynthesis (CDT) R/F system. Due to the iterative nature of time consuming processes in solving a cost function, we took advantage of parallel computing using graphics processing units (GPU) by the compute unified device architecture (CUDA) programming to accelerate our algorithm. In order to compare the algorithmic performance of our proposed CS algorithm, conventional filtered back-projection (FBP) and simultaneous algebraic reconstruction technique (SART) reconstruction schemes were also studied. The results indicated that the CS produced better contrast-to-noise ratios (CNRs) in the physical phantom images (Teflon region-of-interest) by factors of 3.91 and 1.93 than FBP and SART images, respectively. The resulted human chest phantom images including lung nodules with different diameters also showed better visual appearance in the CS images. Our proposed GPU-accelerated CS reconstruction scheme could produce volumetric data up to 80 times than CPU programming. Total elapsed time for producing 50 coronal planes with 1024×1024 image matrix using 41 projection views were 216.74 seconds for proposed CS algorithms on our GPU programming, which could match the clinically feasible time ( 3 min). Consequently, our results demonstrated that the proposed CS method showed a potential of additional dose reduction in digital tomosynthesis with reasonable image quality in a fast time.

Investigation of cone-beam CT image quality trade-off for image-guided radiation therapy.

PubMed

Bian, Junguo; Sharp, Gregory C; Park, Yang-Kyun; Ouyang, Jinsong; Bortfeld, Thomas; El Fakhri, Georges

2016-05-07

It is well-known that projections acquired over an angular range slightly over 180° (so-called short scan) are sufficient for fan-beam reconstruction. However, due to practical imaging conditions (projection data and reconstruction image discretization, physical factors, and data noise), the short-scan reconstructions may have different appearances and properties from the full-scan (scans over 360°) reconstructions. Nevertheless, short-scan configurations have been used in applications such as cone-beam CT (CBCT) for head-neck-cancer image-guided radiation therapy (IGRT) that only requires a small field of view due to the potential reduced imaging time and dose. In this work, we studied the image quality trade-off for full, short, and full/short scan configurations with both conventional filtered-backprojection (FBP) reconstruction and iterative reconstruction algorithms based on total-variation (TV) minimization for head-neck-cancer IGRT. Anthropomorphic and Catphan phantoms were scanned at different exposure levels with a clinical scanner used in IGRT. Both visualization- and numerical-metric-based evaluation studies were performed. The results indicate that the optimal exposure level and number of views are in the middle range for both FBP and TV-based iterative algorithms and the optimization is object-dependent and task-dependent. The optimal view numbers decrease with the total exposure levels for both FBP and TV-based algorithms. The results also indicate there are slight differences between FBP and TV-based iterative algorithms for the image quality trade-off: FBP seems to be more in favor of larger number of views while the TV-based algorithm is more robust to different data conditions (number of views and exposure levels) than the FBP algorithm. The studies can provide a general guideline for image-quality optimization for CBCT used in IGRT and other applications.

Positive and negative variations in capacitive images for given defects under varying experimental conditions

NASA Astrophysics Data System (ADS)

Li, Chen; Yin, Xiaokang; Li, Zhen; Li, Wei; Chen, Guoming

2018-04-01

Capacitive imaging (CI) technique is a novel electromagnetic NDE technique. The Quasi-static electromagnetic field from the carefully designed electrode pair will vary when the electrical properties of the sample change, leading to the possibility of imaging. It is observed that for a given specimen, the targeted features appear as different variations in capacitive images under different experimental conditions. In some cases, even opposite variations occur, which brings confusion to indication interpretation. It is thus thought interesting to embark on investigations into the cause and effects of the negative variation phenomenon. In this work, the positive and negative variations were first explained from the measurement sensitivity distribution perspective. This was then followed by a detailed analysis using finite element models in COMSOL. A parametric experimental study on a glass fiber composite plate with artificial defects was then carried out to investigate how the experimental conditions affect the variation.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Digital preservation of anatomical variation: 3D-modeling of embalmed and plastinated cadaveric specimens using uCT and MRI.

PubMed

Moore, Colin W; Wilson, Timothy D; Rice, Charles L

2017-01-01

Anatomy educators have an opportunity to teach anatomical variations as a part of medical and allied health curricula using both cadaveric and three-dimensional (3D) digital models of these specimens. Beyond published cadaveric case reports, anatomical variations identified during routine gross anatomy dissection can be powerful teaching tools and a medium to discuss several anatomical sub-disciplines from embryology to medical imaging. The purpose of this study is to document how cadaveric anatomical variation identified during routine dissection can be scanned using medical imaging techniques to create two-dimensional axial images and interactive 3D models for teaching and learning of anatomical variations. Three cadaveric specimens (2 formalin embalmed, 1 plastinated) depicting anatomical variations and an embryological malformation were scanned using magnetic resonance imaging (MRI) and micro-computed tomography (μCT) for visualization in cross-section and for creation of 3D volumetric models. Results provide educational options to enable visualization and facilitate learning of anatomical variations from cross-sectional scans. Furthermore, the variations can be highlighted, digitized, modeled and manipulated using 3D imaging software and viewed in the anatomy laboratory in conjunction with traditional anatomical dissection. This study provides an example for anatomy educators to teach and describe anatomical variations in the undergraduate medical curriculum. Copyright © 2016 Elsevier GmbH. All rights reserved.

Image correction during large and rapid B(0) variations in an open MRI system with permanent magnets using navigator echoes and phase compensation.

PubMed

Li, Jianqi; Wang, Yi; Jiang, Yu; Xie, Haibin; Li, Gengying

2009-09-01

An open permanent magnet system with vertical B(0) field and without self-shielding can be quite susceptible to perturbations from external magnetic sources. B(0) variation in such a system located close to a subway station was measured to be greater than 0.7 microT by both MRI and a fluxgate magnetometer. This B(0) variation caused image artifacts. A navigator echo approach that monitored and compensated the view-to-view variation in magnetic resonance signal phase was developed to correct for image artifacts. Human brain imaging experiments using a multislice gradient-echo sequence demonstrated that the ghosting and blurring artifacts associated with B(0) variations were effectively removed using the navigator method.

THE CELESTIAL REFERENCE FRAME AT 24 AND 43 GHz. II. IMAGING

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

Charlot, P.; Boboltz, D. A.; Fey, A. L.

2010-05-15

We have measured the submilliarcsecond structure of 274 extragalactic sources at 24 and 43 GHz in order to assess their astrometric suitability for use in a high-frequency celestial reference frame (CRF). Ten sessions of observations with the Very Long Baseline Array have been conducted over the course of {approx}5 years, with a total of 1339 images produced for the 274 sources. There are several quantities that can be used to characterize the impact of intrinsic source structure on astrometric observations including the source flux density, the flux density variability, the source structure index, the source compactness, and the compactness variability.more » A detailed analysis of these imaging quantities shows that (1) our selection of compact sources from 8.4 GHz catalogs yielded sources with flux densities, averaged over the sessions in which each source was observed, of about 1 Jy at both 24 and 43 GHz, (2) on average the source flux densities at 24 GHz varied by 20%-25% relative to their mean values, with variations in the session-to-session flux density scale being less than 10%, (3) sources were found to be more compact with less intrinsic structure at higher frequencies, and (4) variations of the core radio emission relative to the total flux density of the source are less than 8% on average at 24 GHz. We conclude that the reduction in the effects due to source structure gained by observing at higher frequencies will result in an improved CRF and a pool of high-quality fiducial reference points for use in spacecraft navigation over the next decade.« less

Surface tension and modeling of cellular intercalation during zebrafish gastrulation.

PubMed

Calmelet, Colette; Sepich, Diane

2010-04-01

In this paper we discuss a model of zebrafish embryo notochord development based on the effect of surface tension of cells at the boundaries. We study the process of interaction of mesodermal cells at the boundaries due to adhesion and cortical tension, resulting in cellular intercalation. From in vivo experiments, we obtain cell outlines of time-lapse images of cell movements during zebrafish embryo development. Using Cellular Potts Model, we calculate the total surface energy of the system of cells at different time intervals at cell contacts. We analyze the variations of total energy depending on nature of cell contacts. We demonstrate that our model can be viable by calculating the total surface energy value for experimentally observed configurations of cells and showing that in our model these configurations correspond to a decrease in total energy values in both two and three dimensions.

Vacuum ultraviolet imagery of the Virgo cluster region

NASA Astrophysics Data System (ADS)

Onaka, T.; Tanaka, W.; Watanabe, T.; Watanabe, J.; Yamaguchi, A.; Nakagiri, M.; Kodaira, K.; Nakano, M.; Sasaki, M.; Tsujimura, T.; Yamashita, K.

1989-07-01

The results are reported of an experiment using the UV imager aboard an attitude-controlled S520 type sounding rocket. The total UV fluxes of galaxies in the Virgo Cluster as well as the flux level of the diffuse UV background around the cluster were measured. The data on NGC 4486 and NGC 4472 confirm the variation in the degree of the 'turnup' below 200 nm in the energy spectrum of the total light of elliptical galaxies. At two-color diagram of galaxies of visual/near-UV/vacuum UV indicates that colors of spiral galaxies are distributed within a strip and well-correlated with the morphological type, while elliptical galaxies are located differently from spiral galaxies.

A second order derivative scheme based on Bregman algorithm class

NASA Astrophysics Data System (ADS)

Campagna, Rosanna; Crisci, Serena; Cuomo, Salvatore; Galletti, Ardelio; Marcellino, Livia

2016-10-01

The algorithms based on the Bregman iterative regularization are known for efficiently solving convex constraint optimization problems. In this paper, we introduce a second order derivative scheme for the class of Bregman algorithms. Its properties of convergence and stability are investigated by means of numerical evidences. Moreover, we apply the proposed scheme to an isotropic Total Variation (TV) problem arising out of the Magnetic Resonance Image (MRI) denoising. Experimental results confirm that our algorithm has good performance in terms of denoising quality, effectiveness and robustness.

Effect of the Solar UV/EUV Heating on the Intensity and Spatial Distribution of Jupiter's Synchrotron Radiation

NASA Astrophysics Data System (ADS)

Kita, Hajime; Misawa, H.; Tsuchiya, F.; Tao, C.; Morioka, A.

2012-10-01

Jupiter's synchrotron radiation (JSR) is the emission from relativistic electrons, and it is the most effective probe for remote sensing of Jupiter's radiation belt from the Earth. Recent observations reveal short term variations of JSR with the time scale of days to weeks. Brice and McDonough (1973) proposed that the solar UV/EUV heating for Jupiter's upper atmosphere causes enhancement of total flux density. If such a process occurs at Jupiter, it is also expected that diurnal wind system produces dawn-dusk asymmetry of the JSR brightness distribution. Preceding studies confirmed that the short term variations in total flux density correspond to the solar UV/EUV. However, the effect of solar UV/EUV heating on the brightness distribution has not been confirmed. Hence, the purpose of this study is to confirm the solar UV/EUV heating effect on total flux density and brightness distribution. We made radio imaging analysis using the National Radio Astronomy Observatory (NRAO) archived data of the Very Large Array (VLA) obtained in 2000, and following results were shown. 1, Total flux density varied corresponding to the solar UV/EUV. 2, Dawn side emission was brighter than dusk side emission almost every day. 3, Variations of the dawn-dusk asymmetry did not correspond to the solar UV/EUV. In order to explain the second result, we estimate the diurnal wind velocity from the observed dawn-dusk ratio by using the model brightness distribution of JSR. Estimated neutral wind velocity is 46+/-11 m/s, which reasonably corresponds to the numerical simulation of Jupiter's upper atmosphere. In order to explain the third result, we examined the effect of the global convection electric field driven by tailward outflow of plasma in Jupiter's magnetosphere. As the result, it is suggested that typical fluctuation of the convection electric field strength was enough to cause the observed variations of the dawn-dusk asymmetry.

Thermal-to-visible transducer (TVT) for thermal-IR imaging

NASA Astrophysics Data System (ADS)

Flusberg, Allen; Swartz, Stephen; Huff, Michael; Gross, Steven

2008-04-01

We have been developing a novel thermal-to-visible transducer (TVT), an uncooled thermal-IR imager that is based on a Fabry-Perot Interferometer (FPI). The FPI-based IR imager can convert a thermal-IR image to a video electronic image. IR radiation that is emitted by an object in the scene is imaged onto an IR-absorbing material that is located within an FPI. Temperature variations generated by the spatial variations in the IR image intensity cause variations in optical thickness, modulating the reflectivity seen by a probe laser beam. The reflected probe is imaged onto a visible array, producing a visible image of the IR scene. This technology can provide low-cost IR cameras with excellent sensitivity, low power consumption, and the potential for self-registered fusion of thermal-IR and visible images. We will describe characteristics of requisite pixelated arrays that we have fabricated.

Differential contributions of cortical thickness and surface area to trait impulsivity in healthy young adults.

PubMed

Kubera, Katharina M; Schmitgen, Mike M; Maier-Hein, Klaus H; Thomann, Philipp A; Hirjak, Dusan; Wolf, Robert C

2018-05-08

Impulsivity is an essential human personality trait and highly relevant for the development of several mental disorders. There is evidence that impulsivity is heritable, yet little is known about neural correlates reflecting early brain development. Here, we address the question whether motor, attentional and non-planning components, as reflected by the Barratt Impulsiveness Scale (BIS-11), are distinctly associated with cortical thickness and surface area variations in young healthy individuals. We investigated cortical thickness and surface area in 54 healthy volunteers (m/f = 30%/70%; age mean/SD = 24.9/4.02) using structural magnetic resonance imaging at 3 T together with surface-based analysis techniques. Impulsivity was examined on the Barratt impulsiveness scale (BIS-11) and related to the two distinct cortical measurements. Higher BIS-11 total scores were negatively associated with cortical thickness variations in the left lingual gyrus, left superior temporal gyrus, right cuneus, and right superior parietal gyrus (p<0.05 cluster-wise probability [CWP] corrected). Higher BIS-11 nonplanning scores were negatively associated with cortical thickness variations in bilateral pericalcarine gyrus (p<0.05 CWP corr.). In the orbitofrontal cortex motor impulsivity associated cortical thickness differs significantly between male and female. These data suggest distinct neurodevelopmental trajectories underlying impulsivity in healthy subjects. Impulsivity total scores appear to be specifically related to cortical thickness variations, in contrast to variations of cortical surface area. Furthermore, our findings underscores the importance of better characterizing gender-specific structural correlates of impulsivity. Copyright © 2018. Published by Elsevier B.V.

Photometric Properties of Network and Faculae Derived from HMI Data Compensated for Scattered Light

NASA Astrophysics Data System (ADS)

Criscuoli, Serena; Norton, Aimee; Whitney, Taylor

2017-10-01

We report on the photometric properties of faculae and network, as observed in full-disk, scattered-light-corrected images from the Helioseismic Magnetic Imager. We use a Lucy-Richardson deconvolution routine that corrects an image in less than one second. Faculae are distinguished from network through proximity to active regions. This is the first report that full-disk observations, including center-to-limb variations, reproduce the photometric properties of faculae and network observed previously only in sub-arcsecond-resolution; small field-of-view studies, I.e. that network, as defined by distance from active regions, exhibit higher photometric contrasts. Specifically, for magnetic flux values larger than approximately 300 G, the network is brighter than faculae and the contrast differences increase toward the limb, where the network contrast is about twice the facular one. For lower magnetic flux values, network appear darker than faculae. Contrary to reports from previous full-disk observations, we also found that network exhibits a higher center-to-limb variation. Our results are in agreement with reports from simulations that indicate magnetic flux alone is a poor proxy of the photometric properties of magnetic features. We estimate that the contribution of faculae and network to Total Solar Irradiance variability of the current Cycle 24 is overestimated by at least 11%, due to the photometric properties of network and faculae not being recognized as different. This estimate is specific to the method employed in this study to reconstruct irradiance variations, so caution should be paid when extending it to other techniques.

Digital Rock Physics Aplications: Visualisation Complex Pore and Porosity-Permeability Estimations of the Porous Sandstone Reservoir

NASA Astrophysics Data System (ADS)

Handoyo; Fatkhan; Del, Fourier

2018-03-01

Reservoir rock containing oil and gas generally has high porosity and permeability. High porosity is expected to accommodate hydrocarbon fluid in large quantities and high permeability is associated with the rock’s ability to let hydrocarbon fluid flow optimally. Porosity and permeability measurement of a rock sample is usually performed in the laboratory. We estimate the porosity and permeability of sandstones digitally by using digital images from μCT-Scan. Advantages of the method are non-destructive and can be applied for small rock pieces also easily to construct the model. The porosity values are calculated by comparing the digital image of the pore volume to the total volume of the sandstones; while the permeability values are calculated using the Lattice Boltzmann calculations utilizing the nature of the law of conservation of mass and conservation of momentum of a particle. To determine variations of the porosity and permeability, the main sandstone samples with a dimension of 300 × 300 × 300 pixels are made into eight sub-cubes with a size of 150 × 150 × 150 pixels. Results of digital image modeling fluid flow velocity are visualized as normal velocity (streamline). Variations in value sandstone porosity vary between 0.30 to 0.38 and permeability variations in the range of 4000 mD to 6200 mD. The results of calculations show that the sandstone sample in this research is highly porous and permeable. The method combined with rock physics can be powerful tools for determining rock properties from small rock fragments.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis

PubMed Central

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3–10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception. PMID:28052103

Photometric Properties of Network and Faculae Derived from HMI Data Compensated for Scattered Light

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

Criscuoli, Serena; Whitney, Taylor; Norton, Aimee

We report on the photometric properties of faculae and network, as observed in full-disk, scattered-light-corrected images from the Helioseismic Magnetic Imager. We use a Lucy–Richardson deconvolution routine that corrects an image in less than one second. Faculae are distinguished from network through proximity to active regions. This is the first report that full-disk observations, including center-to-limb variations, reproduce the photometric properties of faculae and network observed previously only in sub-arcsecond-resolution; small field-of-view studies, i.e. that network, as defined by distance from active regions, exhibit higher photometric contrasts. Specifically, for magnetic flux values larger than approximately 300 G, the network ismore » brighter than faculae and the contrast differences increase toward the limb, where the network contrast is about twice the facular one. For lower magnetic flux values, network appear darker than faculae. Contrary to reports from previous full-disk observations, we also found that network exhibits a higher center-to-limb variation. Our results are in agreement with reports from simulations that indicate magnetic flux alone is a poor proxy of the photometric properties of magnetic features. We estimate that the contribution of faculae and network to Total Solar Irradiance variability of the current Cycle 24 is overestimated by at least 11%, due to the photometric properties of network and faculae not being recognized as different. This estimate is specific to the method employed in this study to reconstruct irradiance variations, so caution should be paid when extending it to other techniques.« less

Cancer-related Imaging in the Veterans Affairs Health Care System versus Medicare: Does a System with Lower Use Exhibit Less Geographic Variation?

PubMed Central

McWilliams, J. Michael; Dalton, Jesse B.; Landrum, Mary Beth; Frakt, Austin B.; Pizer, Steven D.; Keating, Nancy L.

2014-01-01

Background Geographic variations in use of medical services have been interpreted as indirect evidence of wasteful care. Less overuse of services, however, may not be reliably associated with less geographic variation. Objective To compare average use and geographic variation in use of cancer-related imaging between fee-for-service Medicare and the Department of Veterans Affairs (VA) health care system. Design Observational analysis of cancer-related imaging from 2003–2005, using Medicare and VA utilization data linked to cancer registry data. We used multilevel models to estimate mean differences in annual imaging use between cohorts of Medicare and VA patients within geographic areas and variation in use across areas for each cohort, adjusting for sociodemographic and tumor characteristics. Setting 40 hospital referral regions. Patients Older men with lung, colorectal, or prostate cancer, including 34,475 traditional Medicare beneficiaries (Medicare cohort) and 6,835 VA patients (VA cohort). Measurements 1)Per-patient count of imaging studies for which lung, colorectal, or prostate cancer was the primary diagnosis (each study weighted by a standardized price); 2)a direct measure of overuse—advanced imaging for prostate cancer at low risk of metastasis. Results Adjusted annual use of cancer-related imaging was lower in the VA cohort than the Medicare cohort (price-weighted count, $197 vs. $379/patient; P<0.001), as was annual use of advanced imaging for prostate cancer at low risk of metastasis ($41 vs. $117/patient; P<0.001). Geographic variation in cancer-related imaging use was similar in magnitude in the VA and Medicare cohorts. Limitations Observational study design. Conclusions Use of cancer-related imaging was lower in the VA health care system than in fee-for-service Medicare, but lower use was not associated with less geographic variation. Geographic variation in service use may not be a reliable indicator of the extent of overuse. Primary Funding Source Doris Duke Charitable Foundation and Department of Veterans Affairs Office of Policy and Planning. PMID:25437407

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

PubMed

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

2018-07-01

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

The complexity of body image following bariatric surgery: a systematic review of the literature.

PubMed

Ivezaj, V; Grilo, C M

2018-06-13

Poor body image is common among individuals seeking bariatric surgery and is associated with adverse psychosocial sequelae. Following massive weight loss secondary to bariatric surgery, many individuals experience excess skin and associated concerns, leading to subsequent body contouring procedures. Little is known, however, about body image changes and associated features from pre-to post-bariatric surgery and subsequent body contouring. The objective of the present study was to conduct a comprehensive literature review of body image following bariatric surgery to help inform future clinical research and care. The articles for the current review were identified by searching PubMed and SCOPUS and references from relevant articles. A total of 60 articles examining body image post-bariatric surgery were identified, and 45 did not include body contouring surgery. Overall, there was great variation in standards of reporting sample characteristics and body image terms. When examining broad levels of body image dissatisfaction, the literature suggests general improvements in certain aspects of body image following bariatric surgery; however, few studies have systematically examined various body image domains from pre-to post-bariatric surgery and subsequent body contouring surgery. In conclusion, there is a paucity of research that examines the multidimensional elements of body image following bariatric surgery. © 2018 World Obesity Federation.

Convex blind image deconvolution with inverse filtering

NASA Astrophysics Data System (ADS)

Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong

2018-03-01

Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.

WE-G-18C-05: Characterization of Cross-Vendor, Cross-Field Strength MR Image Intensity Variations

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

Paulson, E; Prah, D

2014-06-15

Purpose: Variations in MR image intensity and image intensity nonuniformity (IINU) can challenge the accuracy of intensity-based image segmentation and registration algorithms commonly applied in radiotherapy. The goal of this work was to characterize MR image intensity variations across scanner vendors and field strengths commonly used in radiotherapy. Methods: ACR-MRI phantom images were acquired at 1.5T and 3.0T on GE (450w and 750, 23.1), Siemens (Espree and Verio, VB17B), and Philips (Ingenia, 4.1.3) scanners using commercial spin-echo sequences with matched parameters (TE/TR: 20/500 ms, rBW: 62.5 kHz, TH/skip: 5/5mm). Two radiofrequency (RF) coil combinations were used for each scanner: bodymore » coil alone, and combined body and phased-array head coils. Vendorspecific B1- corrections (PURE/Pre-Scan Normalize/CLEAR) were applied in all head coil cases. Images were transferred offline, corrected for IINU using the MNI N3 algorithm, and normalized. Coefficients of variation (CV=σ/μ) and peak image uniformity (PIU = 1−(Smax−Smin)/(Smax+Smin)) estimates were calculated for one homogeneous phantom slice. Kruskal-Wallis and Wilcoxon matched-pairs tests compared mean MR signal intensities and differences between original and N3 image CV and PIU. Results: Wide variations in both MR image intensity and IINU were observed across scanner vendors, field strengths, and RF coil configurations. Applying the MNI N3 correction for IINU resulted in significant improvements in both CV and PIU (p=0.0115, p=0.0235). However, wide variations in overall image intensity persisted, requiring image normalization to improve consistency across vendors, field strengths, and RF coils. These results indicate that B1- correction routines alone may be insufficient in compensating for IINU and image scaling, warranting additional corrections prior to use of MR images in radiotherapy. Conclusions: MR image intensities and IINU vary as a function of scanner vendor, field strength, and RF coil configuration. A two-step strategy consisting of MNI N3 correction followed by normalization was required to improve MR image consistency. Funding provided by Advancing a Healthier Wisconsin.« less

HARDI DATA DENOISING USING VECTORIAL TOTAL VARIATION AND LOGARITHMIC BARRIER

PubMed Central

Kim, Yunho; Thompson, Paul M.; Vese, Luminita A.

2010-01-01

In this work, we wish to denoise HARDI (High Angular Resolution Diffusion Imaging) data arising in medical brain imaging. Diffusion imaging is a relatively new and powerful method to measure the three-dimensional profile of water diffusion at each point in the brain. These images can be used to reconstruct fiber directions and pathways in the living brain, providing detailed maps of fiber integrity and connectivity. HARDI data is a powerful new extension of diffusion imaging, which goes beyond the diffusion tensor imaging (DTI) model: mathematically, intensity data is given at every voxel and at any direction on the sphere. Unfortunately, HARDI data is usually highly contaminated with noise, depending on the b-value which is a tuning parameter pre-selected to collect the data. Larger b-values help to collect more accurate information in terms of measuring diffusivity, but more noise is generated by many factors as well. So large b-values are preferred, if we can satisfactorily reduce the noise without losing the data structure. Here we propose two variational methods to denoise HARDI data. The first one directly denoises the collected data S, while the second one denoises the so-called sADC (spherical Apparent Diffusion Coefficient), a field of radial functions derived from the data. These two quantities are related by an equation of the form S = SSexp (−b · sADC) (in the noise-free case). By applying these two different models, we will be able to determine which quantity will most accurately preserve data structure after denoising. The theoretical analysis of the proposed models is presented, together with experimental results and comparisons for denoising synthetic and real HARDI data. PMID:20802839

Latitudinal Variations In Vertical Cloud Structure Of Jupiter As Determined By Ground- based Observation With Multispectral Imaging

NASA Astrophysics Data System (ADS)

Sato, T.; Kasaba, Y.; Takahashi, Y.; Murata, I.; Uno, T.; Tokimasa, N.; Sakamoto, M.

2008-12-01

We conducted ground-based observation of Jupiter with the liquid crystal tunable filter (LCTF) and EM-CCD camera in two methane absorption bands (700-757nm, 872-950nm at 3 nm step: total of 47 wavelengths) to derive detailed Jupiter's vertical cloud structure. The 2-meter reflector telescope at Nishi-Harima astronomical observatory in Japan was used for our observation on 26-30 May, 2008. After a series of image processing (composition of high quality images in each wavelength and geometry calibration), we converted observed intensity to absolute reflectivity at each pixel using standard star. As a result, we acquired Jupiter's data cubes with high-spatial resolution (about 1") and narrow band imaging (typically 7nm) in each methane absorption band by superimposing 30 Jupiter's images obtained in short exposure time (50 ms per one image). These data sets enable us to probe different altitudes of Jupiter from 100 mbar down to 1bar level with higher vertical resolution than using convectional interference filters. To interpret observed center-limb profiles, we developed radiative transfer code based on layer adding doubling algorithm to treat multiple scattering of solar light theoretically and extracted information on aerosol altitudes and optical properties using two-cloud model. First, we fit 5 different profiles simultaneously in continuum data (745-757 nm) to retrieve information on optical thickness of haze and single scattering albedo of cloud. Second, we fit 15 different profiles around 727nm methane absorption band and 13 different profiles around 890 nm methane absorption band to retrieve information on the aerosol altitude location and optical thickness of cloud. In this presentation, we present the results of these modeling simulations and discuss the latitudinal variations of Jupiter's vertical cloud structure.

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials

PubMed Central

Liang, Zhikai; Pandey, Piyush; Stoerger, Vincent; Xu, Yuhang; Qiu, Yumou; Ge, Yufeng

2018-01-01

Abstract Background Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision–based tools. Findings A set of maize inbreds—primarily recently off patent lines—were phenotyped using a high-throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high-density genotyping and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2 years by the Genomes 2 Fields Consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence, and thermal infrared photos has been released. Conclusions Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors that influence yield plasticity. PMID:29186425

FIVE YEARS OF SYNTHESIS OF SOLAR SPECTRAL IRRADIANCE FROM SDID/SISA AND SDO /AIA IMAGES

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

Fontenla, J. M.; Codrescu, M.; Fedrizzi, M.

In this paper we describe the synthetic solar spectral irradiance (SSI) calculated from 2010 to 2015 using data from the Atmospheric Imaging Assembly (AIA) instrument, on board the Solar Dynamics Observatory spacecraft. We used the algorithms for solar disk image decomposition (SDID) and the spectral irradiance synthesis algorithm (SISA) that we had developed over several years. The SDID algorithm decomposes the images of the solar disk into areas occupied by nine types of chromospheric and 5 types of coronal physical structures. With this decomposition and a set of pre-computed angle-dependent spectra for each of the features, the SISA algorithm ismore » used to calculate the SSI. We discuss the application of the basic SDID/SISA algorithm to a subset of the AIA images and the observed variation occurring in the 2010–2015 period of the relative areas of the solar disk covered by the various solar surface features. Our results consist of the SSI and total solar irradiance variations over the 2010–2015 period. The SSI results include soft X-ray, ultraviolet, visible, infrared, and far-infrared observations and can be used for studies of the solar radiative forcing of the Earth’s atmosphere. These SSI estimates were used to drive a thermosphere–ionosphere physical simulation model. Predictions of neutral mass density at low Earth orbit altitudes in the thermosphere and peak plasma densities at mid-latitudes are in reasonable agreement with the observations. The correlation between the simulation results and the observations was consistently better when fluxes computed by SDID/SISA procedures were used.« less

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials.

PubMed

Liang, Zhikai; Pandey, Piyush; Stoerger, Vincent; Xu, Yuhang; Qiu, Yumou; Ge, Yufeng; Schnable, James C

2018-02-01

Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision-based tools. A set of maize inbreds-primarily recently off patent lines-were phenotyped using a high-throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high-density genotyping and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2 years by the Genomes 2 Fields Consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence, and thermal infrared photos has been released. Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors that influence yield plasticity. © The Authors 2017. Published by Oxford University Press.

Quantitative Mapping of Pore Fraction Variations in Silicon Nitride Using an Ultrasonic Contact Scan Technique

NASA Technical Reports Server (NTRS)

Roth, Don J.; Kiser, James D.; Swickard, Suzanne M.; Szatmary, Steven A.; Kerwin, David P.

1993-01-01

An ultrasonic scan procedure using the pulse-echo contact configuration was employed to obtain maps of pore fraction variations in sintered silicon nitride samples in terms of ultrasonic material properties. Ultrasonic velocity, attenuation coefficient, and reflection coefficient images were obtained simultaneously over a broad band of frequencies (e.g., 30 to 110 MHz) by using spectroscopic analysis. Liquid and membrane (dry) coupling techniques and longitudinal and shear-wave energies were used. The major results include the following: Ultrasonic velocity (longitudinal and shear wave) images revealed and correlated with the extent of average through-thickness pore fraction variations in the silicon nitride disks. Attenuation coefficient images revealed pore fraction nonuniformity due to the scattering that occurred at boundaries between regions of high and low pore fraction. Velocity and attenuation coefficient images were each nearly identical for machined and polished disks, making the method readily applicable to machined materials. Velocity images were similar for wet and membrane coupling. Maps of apparent Poisson's ratio constructed from longitudinal and shear-wave velocities quantified Poisson's ratio variations across a silicon nitride disk. Thermal wave images of a disk indicated transient thermal behavior variations that correlated with observed variations in pore fraction and velocity and attenuation coefficients.

3D and 4D magnetic susceptibility tomography based on complex MR images

DOEpatents

Chen, Zikuan; Calhoun, Vince D

2014-11-11

Magnetic susceptibility is the physical property for T2*-weighted magnetic resonance imaging (T2*MRI). The invention relates to methods for reconstructing an internal distribution (3D map) of magnetic susceptibility values, .chi. (x,y,z), of an object, from 3D T2*MRI phase images, by using Computed Inverse Magnetic Resonance Imaging (CIMRI) tomography. The CIMRI technique solves the inverse problem of the 3D convolution by executing a 3D Total Variation (TV) regularized iterative convolution scheme, using a split Bregman iteration algorithm. The reconstruction of .chi. (x,y,z) can be designed for low-pass, band-pass, and high-pass features by using a convolution kernel that is modified from the standard dipole kernel. Multiple reconstructions can be implemented in parallel, and averaging the reconstructions can suppress noise. 4D dynamic magnetic susceptibility tomography can be implemented by reconstructing a 3D susceptibility volume from a 3D phase volume by performing 3D CIMRI magnetic susceptibility tomography at each snapshot time.

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

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

Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

2013-05-06

Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry withmore » alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.« less

A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2015-07-01

In digital histopathology, tasks of segmentation and disease diagnosis are achieved by quantitative analysis of image content. However, color variation in image samples makes it challenging to produce reliable results. This paper introduces a complete normalization scheme to address the problem of color variation in histopathology images jointly caused by inconsistent biopsy staining and nonstandard imaging condition. Method : Different from existing normalization methods that either address partial cause of color variation or lump them together, our method identifies causes of color variation based on a microscopic imaging model and addresses inconsistency in biopsy imaging and staining by an illuminant normalization module and a spectral normalization module, respectively. In evaluation, we use two public datasets that are representative of histopathology images commonly received in clinics to examine the proposed method from the aspects of robustness to system settings, performance consistency against achromatic pixels, and normalization effectiveness in terms of histological information preservation. As the saturation-weighted statistics proposed in this study generates stable and reliable color cues for stain normalization, our scheme is robust to system parameters and insensitive to image content and achromatic colors. Extensive experimentation suggests that our approach outperforms state-of-the-art normalization methods as the proposed method is the only approach that succeeds to preserve histological information after normalization. The proposed color normalization solution would be useful to mitigate effects of color variation in pathology images on subsequent quantitative analysis.

Electric field imaging of single atoms

PubMed Central

Shibata, Naoya; Seki, Takehito; Sánchez-Santolino, Gabriel; Findlay, Scott D.; Kohno, Yuji; Matsumoto, Takao; Ishikawa, Ryo; Ikuhara, Yuichi

2017-01-01

In scanning transmission electron microscopy (STEM), single atoms can be imaged by detecting electrons scattered through high angles using post-specimen, annular-type detectors. Recently, it has been shown that the atomic-scale electric field of both the positive atomic nuclei and the surrounding negative electrons within crystalline materials can be probed by atomic-resolution differential phase contrast STEM. Here we demonstrate the real-space imaging of the (projected) atomic electric field distribution inside single Au atoms, using sub-Å spatial resolution STEM combined with a high-speed segmented detector. We directly visualize that the electric field distribution (blurred by the sub-Å size electron probe) drastically changes within the single Au atom in a shape that relates to the spatial variation of total charge density within the atom. Atomic-resolution electric field mapping with single-atom sensitivity enables us to examine their detailed internal and boundary structures. PMID:28555629

Nighttime Medium-Scale Traveling Ionospheric Disturbances From Airglow Imager and Global Navigation Satellite Systems Observations

NASA Astrophysics Data System (ADS)

Huang, Fuqing; Lei, Jiuhou; Dou, Xiankang; Luan, Xiaoli; Zhong, Jiahao

2018-01-01

In this study, coordinated airglow imager, GPS total electron content (TEC), and Beidou geostationary orbit (GEO) TEC observations for the first time are used to investigate the characteristics of nighttime medium-scale traveling ionospheric disturbances (MSTIDs) over central China. The results indicated that the features of nighttime MSTIDs from three types of observations are generally consistent, whereas the nighttime MSTID features from the Beidou GEO TEC are in better agreement with those from airglow images as compared with the GPS TEC, given that the nighttime MSTID characteristics from GPS TEC are significantly affected by Doppler effect due to satellite movement. It is also found that there are three peaks in the seasonal variations of the occurrence rate of nighttime MSTIDs in 2016. Our study revealed that the Beidou GEO satellites provided fidelity TEC observations to study the ionospheric variability.

A limited-angle CT reconstruction method based on anisotropic TV minimization.

PubMed

Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge

2013-04-07

This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.

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

Chen, Yu; Gao, Kai; Huang, Lianjie

Accurate imaging and characterization of fracture zones is crucial for geothermal energy exploration. Aligned fractures within fracture zones behave as anisotropic media for seismic-wave propagation. The anisotropic properties in fracture zones introduce extra difficulties for seismic imaging and waveform inversion. We have recently developed a new anisotropic elastic-waveform inversion method using a modified total-variation regularization scheme and a wave-energy-base preconditioning technique. Our new inversion method uses the parameterization of elasticity constants to describe anisotropic media, and hence it can properly handle arbitrary anisotropy. We apply our new inversion method to a seismic velocity model along a 2D-line seismic data acquiredmore » at Eleven-Mile Canyon located at the Southern Dixie Valley in Nevada for geothermal energy exploration. Our inversion results show that anisotropic elastic-waveform inversion has potential to reconstruct subsurface anisotropic elastic parameters for imaging and characterization of fracture zones.« less

Using active shape modeling based on MRI to study morphologic and pitch-related functional changes affecting vocal structures and the airway.

PubMed

Miller, Nicola A; Gregory, Jennifer S; Aspden, Richard M; Stollery, Peter J; Gilbert, Fiona J

2014-09-01

The shape of the vocal tract and associated structures (eg, tongue and velum) is complicated and varies according to development and function. This variability challenges interpretation of voice experiments. Quantifying differences between shapes and understanding how vocal structures move in relation to each other is difficult using traditional linear and angle measurements. With statistical shape models, shape can be characterized in terms of independent modes of variation. Here, we build an active shape model (ASM) to assess morphologic and pitch-related functional changes affecting vocal structures and the airway. Using a cross-sectional study design, we obtained six midsagittal magnetic resonance images from 10 healthy adults (five men and five women) at rest, while breathing out, and while listening to, and humming low and high notes. Eighty landmark points were chosen to define the shape of interest and an ASM was built using these (60) images. Principal component analysis was used to identify independent modes of variation, and statistical analysis was performed using one-way repeated-measures analysis of variance. Twenty modes of variation were identified with modes 1 and 2 accounting for half the total variance. Modes 1 and 9 were significantly associated with humming low and high notes (P < 0.001) and showed coordinated changes affecting the cervical spine, vocal structures, and airway. Mode 2 highlighted wide structural variations between subjects. This study highlights the potential of active shape modeling to advance understanding of factors underlying morphologic and pitch-related functional variations affecting vocal structures and the airway in health and disease. Copyright © 2014 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Time-evolution of uniform momentum zones in a turbulent boundary layer

NASA Astrophysics Data System (ADS)

Laskari, Angeliki; Hearst, R. Jason; de Kat, Roeland; Ganapathisubramani, Bharathram

2016-11-01

Time-resolved planar particle image velocimetry (PIV) is used to analyse the organisation and evolution of uniform momentum zones (UMZs) in a turbulent boundary layer. Experiments were performed in a recirculating water tunnel on a streamwise-wall-normal plane extending approximately 0 . 5 δ × 1 . 8 δ , in x and y, respectively. In total 400,000 images were captured and for each of the resulting velocity fields, local peaks in the probability density distribution of the streamwise velocity were detected, indicating the instantaneous presence of UMZs throughout the boundary layer. The main characteristics of these zones are outlined and more specifically their velocity range and wall-normal extent. The variation of these characteristics with wall normal distance and total number of zones are also discussed. Exploiting the time information available, time-scales of zones that have a substantial coherence in time are analysed and results show that the zones' lifetime is dependent on both their momentum deficit level and the total number of zones present. Conditional averaging of the flow statistics seems to further indicate that a large number of zones is the result of a wall-dominant mechanism, while the opposite implies an outer-layer dominance.

Optimizing a 18F-NaF and 18F-FDG cocktail for PET assessment of metastatic castration-resistant prostate cancer

PubMed Central

Simoncic, Urban; Perlman, Scott; Liu, Glenn; Jeraj, Robert

2015-01-01

Background The 18F-NaF/18F-FDG cocktail PET/CT imaging has been proposed for patients with osseous metastases. This work aimed to optimize the cocktail composition for patients with metastatic castrate-resistant prostate cancer (mCRPC). Materials and methods Study was done on 6 patients with mCRPC that had analyzed a total of 26 lesions. Patients had 18F-NaF and 18F-FDG injections separated in time. Dynamic PET/CT imaging recorded uptake time course for both tracers into osseous metastases. 18F-NaF and 18F-FDG uptakes were decoupled by kinetic analysis, which enabled calculation of 18F-NaF and 18F-FDG Standardized Uptake Value (SUV) images. Peak, mean and total SUVs were evaluated for both tracers and all visible lesions. The 18F-NaF/18F-FDG cocktail was optimized under the assumption that contribution of both tracers to the image formation should be equal. SUV images for combined 18F-NaF/18F-FDG cocktail PET/CT imaging were generated for cocktail compositions with 18F-NaF:18F-FDG ratio varying from 1:8 to 1:2. Results The 18F-NaF peak and mean SUVs were on average 4-5 times higher than the 18F-FDG peak and mean SUVs, with inter-lesion coefficient-of-variations (COV) of 20%. 18F-NaF total SUV was on average 7 times higher than the 18F-FDG total SUV. When the 18F-NaF:18F-FDG ratio changed from 1:8 to 1:2, typical SUV on generated PET images increased by 50%, while change in uptake visual pattern was hardly noticeable. Conclusion The 18F-NaF/18F-FDG cocktail has equal contributions of both tracers to the image formation when the 18F-NaF:18F-FDG ratio is 1:5. Therefore we propose this ratio as the optimal cocktail composition for mCRPC patients. We also urge to strictly control the 18F-NaF/18F-FDG cocktail composition in any 18F-NaF/18F-FDG cocktail PET/CT exams. PMID:26378490

Segmentation of photospheric magnetic elements corresponding to coronal features to understand the EUV and UV irradiance variability

NASA Astrophysics Data System (ADS)

Zender, J. J.; Kariyappa, R.; Giono, G.; Bergmann, M.; Delouille, V.; Damé, L.; Hochedez, J.-F.; Kumara, S. T.

2017-09-01

Context. The magnetic field plays a dominant role in the solar irradiance variability. Determining the contribution of various magnetic features to this variability is important in the context of heliospheric studies and Sun-Earth connection. Aims: We studied the solar irradiance variability and its association with the underlying magnetic field for a period of five years (January 2011-January 2016). We used observations from the Large Yield Radiometer (LYRA), the Sun Watcher with Active Pixel System detector and Image Processing (SWAP) on board PROBA2, the Atmospheric Imaging Assembly (AIA), and the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Methods: The Spatial Possibilistic Clustering Algorithm (SPoCA) is applied to the extreme ultraviolet (EUV) observations obtained from the AIA to segregate coronal features by creating segmentation maps of active regions (ARs), coronal holes (CHs) and the quiet sun (QS). Further, these maps are applied to the full-disk SWAP intensity images and the full-disk (FD) HMI line-of-sight (LOS) magnetograms to isolate the SWAP coronal features and photospheric magnetic counterparts, respectively. We then computed full-disk and feature-wise averages of EUV intensity and line of sight (LOS) magnetic flux density over ARs/CHs/QS/FD. The variability in these quantities is compared with that of LYRA irradiance values. Results: Variations in the quantities resulting from the segmentation, namely the integrated intensity and the total magnetic flux density of ARs/CHs/QS/FD regions, are compared with the LYRA irradiance variations. We find that the EUV intensity over ARs/CHs/QS/FD is well correlated with the underlying magnetic field. In addition, variations in the full-disk integrated intensity and magnetic flux density values are correlated with the LYRA irradiance variations. Conclusions: Using the segmented coronal features observed in the EUV wavelengths as proxies to isolate the underlying magnetic structures is demonstrated in this study. Sophisticated feature identification and segmentation tools are important in providing more insights into the role of various magnetic features in both the short- and long-term changes in the solar irradiance. The movie associated to Fig. 2 is available at http://www.aanda.org

Mapping large extensions of flat dentin through digital microscopy: introduction to the method and possible applications.

PubMed

Reis, Claudia; De-Deus, Gustavo; Marins, Juliana; Fidel, Sandra; Fidel, Rivail; Paciornik, Sidnei

2012-08-01

To introduce a mapping method to characterize large dentin surfaces using digital microscopy and to discuss the advantages and possible applications of the method. Twenty unerupted third molars were sectioned transversally exposing coronal dentin surfaces. The microscopic mosaic method was used to generate a large field image with the resolution necessary to measure characteristics of dentin tubules. The AxioVision 4.7 software was used to control a motorized optical microscope and the process of acquiring approximately 400 small images to generate each dentin mosaic. An image analysis routine measured the number of tubules (NT) and the ratio between the total area of tubules and the area of the mosaic - the area fraction (AF) - of each mosaic. An automatic procedure transformed the mosaic image into a color map, providing a direct visual representation of tubule density through colors. The dentin maps were used for a comparative qualitative analysis of tubule density distribution of each sample. The results for NT (92450 to 196029 tubules/sample) and AF (4.12% to 11.10%) demonstrated a wide variation among dentin samples. The maps confirmed the microstructure variety, also revealing strong local variations in tubule density within each sample. The mapping method was able to perform dentin morphology characterization and is a valuable tool for producing a baseline for dentin adhesion studies. The method could be also useful in determining the real contribution of dentin structures to the final adhesion quality.

Functional validation and comparison framework for EIT lung imaging.

PubMed

Grychtol, Bartłomiej; Elke, Gunnar; Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.

Multimodal registration of three-dimensional maxillodental cone beam CT and photogrammetry data over time.

PubMed

Bolandzadeh, N; Bischof, W; Flores-Mir, C; Boulanger, P

2013-01-01

In recent years, one of the foci of orthodontics has been on systems for the evaluation of treatment results and the tracking of tissue variations over time. This can be accomplished through analysing three-dimensional orthodontic images obtained before and after the treatments. Since complementary information is achieved by integrating multiple imaging modalities, cone beam CT (CBCT) and stereophotogrammetry technologies are used in this study to develop a method for tracking bone, teeth and facial soft-tissue variations over time. We propose a two-phase procedure of multimodal (Phase 1) and multitemporal (Phase 2) registration which aligns images taken from the same patient by different imaging modalities and at different times. Extrinsic (for Phase 1) and intrinsic (for Phase 2) landmark-based registration methods are employed as an initiation for a robust iterative closest points algorithm. Since the mandible moves independently of the upper skull, the registration procedure is applied separately on the mandible and the upper skull. The results show that the signed error distributions of both mandible and skull registrations follow a mixture of two Gaussian distributions, corresponding to alignment errors (due to our method) and temporal change over time. We suggest that the large values among the total registration errors correspond to the temporal change resulting from (1) the effect of treatment (i.e. the orthodontic changes of teeth positions); (2) the biological changes such as teeth growth over time, especially for teenagers; and (3) the segmentation procedure and CBCT precision change over time.

An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

PubMed

Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values.

An Object-Oriented Simulator for 3D Digital Breast Tomosynthesis Imaging System

PubMed Central

Cengiz, Kubra

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

Compressed sensing with cyclic-S Hadamard matrix for terahertz imaging applications

NASA Astrophysics Data System (ADS)

Ermeydan, Esra Şengün; ćankaya, Ilyas

2018-01-01

Compressed Sensing (CS) with Cyclic-S Hadamard matrix is proposed for single pixel imaging applications in this study. In single pixel imaging scheme, N = r . c samples should be taken for r×c pixel image where . denotes multiplication. CS is a popular technique claiming that the sparse signals can be reconstructed with samples under Nyquist rate. Therefore to solve the slow data acquisition problem in Terahertz (THz) single pixel imaging, CS is a good candidate. However, changing mask for each measurement is a challenging problem since there is no commercial Spatial Light Modulators (SLM) for THz band yet, therefore circular masks are suggested so that for each measurement one or two column shifting will be enough to change the mask. The CS masks are designed using cyclic-S matrices based on Hadamard transform for 9 × 7 and 15 × 17 pixel images within the framework of this study. The %50 compressed images are reconstructed using total variation based TVAL3 algorithm. Matlab simulations demonstrates that cyclic-S matrices can be used for single pixel imaging based on CS. The circular masks have the advantage to reduce the mechanical SLMs to a single sliding strip, whereas the CS helps to reduce acquisition time and energy since it allows to reconstruct the image from fewer samples.

Fractional Diffusion, Low Exponent Lévy Stable Laws, and 'Slow Motion' Denoising of Helium Ion Microscope Nanoscale Imagery.

PubMed

Carasso, Alfred S; Vladár, András E

2012-01-01

Helium ion microscopes (HIM) are capable of acquiring images with better than 1 nm resolution, and HIM images are particularly rich in morphological surface details. However, such images are generally quite noisy. A major challenge is to denoise these images while preserving delicate surface information. This paper presents a powerful slow motion denoising technique, based on solving linear fractional diffusion equations forward in time. The method is easily implemented computationally, using fast Fourier transform (FFT) algorithms. When applied to actual HIM images, the method is found to reproduce the essential surface morphology of the sample with high fidelity. In contrast, such highly sophisticated methodologies as Curvelet Transform denoising, and Total Variation denoising using split Bregman iterations, are found to eliminate vital fine scale information, along with the noise. Image Lipschitz exponents are a useful image metrology tool for quantifying the fine structure content in an image. In this paper, this tool is applied to rank order the above three distinct denoising approaches, in terms of their texture preserving properties. In several denoising experiments on actual HIM images, it was found that fractional diffusion smoothing performed noticeably better than split Bregman TV, which in turn, performed slightly better than Curvelet denoising.

Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion

PubMed Central

Weaver, Cole A.; Miller, Steven F.; da Fontoura, Clarissa S. G.; Wehby, George L.; Amendt, Brad A.; Holton, Nathan E.; Allareddy, Veeratrishul; Southard, Thomas E.; Moreno Uribe, Lina M.

2017-01-01

Introduction Genetic studies of malocclusion etiology have identified 4 deleterious mutations in genes, DUSP6, ARHGAP21, FGF23, and ADAMTS1 in familial Class III cases. Although these variants may have large impacts on Class III phenotypic expression, their low frequency (<1%) makes them unlikely to explain most malocclusions. Thus, much of the genetic variation underlying the dentofacial phenotypic variation associated with malocclusion remains unknown. In this study, we evaluated associations between common genetic variations in craniofacial candidate genes and 3-dimensional dentoalveolar phenotypes in patients with malocclusion. Methods Pretreatment dental casts or cone-beam computed tomographic images from 300 healthy subjects were digitized with 48 landmarks. The 3-dimensional coordinate data were submitted to a geometric morphometric approach along with principal component analysis to generate continuous phenotypes including symmetric and asymmetric components of dentoalveolar shape variation, fluctuating asymmetry, and size. The subjects were genotyped for 222 single-nucleotide polymorphisms in 82 genes/loci, and phenotpye-genotype associations were tested via multivariate linear regression. Results Principal component analysis of symmetric variation identified 4 components that explained 68% of the total variance and depicted anteroposterior, vertical, and transverse dentoalveolar discrepancies. Suggestive associations (P < 0.05) were identified with PITX2, SNAI3, 11q22.2-q22.3, 4p16.1, ISL1, and FGF8. Principal component analysis for asymmetric variations identified 4 components that explained 51% of the total variations and captured left-to-right discrepancies resulting in midline deviations, unilateral crossbites, and ectopic eruptions. Suggestive associations were found with TBX1 AJUBA, SNAI3 SATB2, TP63, and 1p22.1. Fluctuating asymmetry was associated with BMP3 and LATS1. Associations for SATB2 and BMP3 with asymmetric variations remained significant after the Bonferroni correction (P <0.00022). Suggestive associations were found for centroid size, a proxy for dentoalveolar size variation with 4p16.1 and SNAI1. Conclusions Specific genetic pathways associated with 3-dimensional dentoalveolar phenotypic variation in malocclusions were identified. PMID:28257739

Community patterns of tropical tree phenology derived from Unmanned Aerial Vehicle images: intra- and interspecific variation, association with species plant traits, and response to interannual climate variation

NASA Astrophysics Data System (ADS)

Bohlman, Stephanie; Rifai, Sami; Park, John; Dandois, Jonathan; Muller-Landau, Helene

2017-04-01

Phenology is a key life history trait of plant species and critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical forest phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns, which makes it difficult to collect sufficient ground-based field data to characterize individual tropical tree species phenologies. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. The objective of this study is to quantify inter- and intra-specific responses of tropical tree leaf phenology to environmental variation over large spatial scales and identify key environmental variables and physiological mechanisms underpinning phenological variation. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. UAV imagery was corrected for exposure, orthorectified, and then processed to extract spectral, texture, and image information for individual tree crowns, which was then used as inputs for a machine learning algorithm that successfully predicted the percentages of leaf, branch, and flower cover for each tree crown (r2=0.76 between observed and predicted percent branch cover for individual tree crowns). We then quantified cumulative annual deciduousness for each crown by fitting a non-parametric curve of flexible shape to its predicted percent branch time series and calculated the area under the curve. We obtained the species identities of 2000 crowns in the images by linking the crowns to stem tags in the field, thus producing a time series of cumulative annual deciduousness for 65 species. Deciduousness showed continuous variation among species rather than distinct phenological categories (ie evergreen and deciduous) that are commonly used in physiological, ecosystem and modeling studies. Some species labelled as evergreen by expert-based classification had annual deciduousness higher than those labelled as deciduous. We found significant, positive relationships between species mean deciduousness and species' leaf phosphorous, photosynthetic capacity and adult relative growth rate, suggesting that higher deciduousness is associated with greater resource acquisition. Comparing May 2015 (during an El Nino drought) and May 2014 (an non El Nino year with normal rainfall), mean deciduousness values for nearly all species was greater in 2015 but with differing levels of intraspecific variation. We discuss how the variation in deciduousness among species, its relationship with plant traits and response to the drought might be incorporated into terrestrial biosphere models of tropical forests to more accurately represent phenology and understand the consequences of community-level variation in phenology for ecosystem processes.

Identifying water mass depletion in Northern Iraq observed by GRACE

NASA Astrophysics Data System (ADS)

Mulder, G.; Olsthoorn, T. N.; Al-Manmi, D. A. M. A.; Schrama, E. J. O.; Smidt, E. H.

2014-10-01

Observations acquired by Gravity Recovery And Climate Experiment (GRACE) mission indicate a mass loss of 31 ± 3 km3 or 130 ± 14 mm in Northern Iraq between 2007 and 2009. This data is used as an independent validation of a hydrologic model of the region including lake mass variations. We developed a rainfall-runoff model for five tributaries of the Tigris River, based on local geology and climate conditions. Model inputs are precipitation from Tropical Rainfall Measurement Mission (TRMM) observations, and potential evaporation from GLDAS model parameters. Our model includes a representation of the karstified aquifers that cause large natural groundwater variations in this region. Observed river discharges were used to calibrate our model. In order to get the total mass variations, we corrected for lake mass variations derived from Moderate Resolution Imaging Spectroradiometer (MODIS) in combination with satellite altimetry and some in-situ data. Our rainfall-runoff model confirms that Northern Iraq suffered a drought between 2007 and 2009 and is consistent with the mass loss observed by GRACE over that period. Also, GRACE observed the annual cycle predicted by the rainfall-runoff model. The total mass depletion seen by GRACE between 2007 and 2009 is mainly explained by a lake mass depletion of 74 ± 4 mm and a natural groundwater depletion of 37 ± 6 mm. Our findings indicate that man-made groundwater extraction has a minor influence in this region while depletion of lake mass and geology play a key role.

Photoacoustic image reconstruction via deep learning

NASA Astrophysics Data System (ADS)

Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes

2018-02-01

Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.

Variation of River Islands around a Large City along the Yangtze River from Satellite Remote Sensing Images

PubMed Central

Shi, Haiyun; Gao, Chao; Dong, Changming; Xia, Changshui; Xu, Guanglai

2017-01-01

River islands are sandbars formed by scouring and silting. Their evolution is affected by several factors, among which are runoff and sediment discharge. The spatial-temporal evolution of seven river islands in the Nanjing Section of the Yangtze River of China was examined using TM (Thematic Mapper) and ETM (Enhanced Thematic Mapper)+ images from 1985 to 2015 at five year intervals. The following approaches were applied in this study: the threshold value method, binarization model, image registration, image cropping, convolution and cluster analysis. Annual runoff and sediment discharge data as measured at the Datong hydrological station upstream of Nanjing section were also used to determine the roles and impacts of various factors. The results indicated that: (1) TM/ETM+ images met the criteria of information extraction of river islands; (2) generally, the total area of these islands in this section and their changing rate decreased over time; (3) sediment and river discharge were the most significant factors in island evolution. They directly affect river islands through silting or erosion. Additionally, anthropocentric influences could play increasingly important roles. PMID:28953218

Feedforward object-vision models only tolerate small image variations compared to human

PubMed Central

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

2014-01-01

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

Regional Ventilation Changes in the Lung: Treatment Response Mapping by Using Hyperpolarized Gas MR Imaging as a Quantitative Biomarker.

PubMed

Horn, Felix C; Marshall, Helen; Collier, Guilhem J; Kay, Richard; Siddiqui, Salman; Brightling, Christopher E; Parra-Robles, Juan; Wild, Jim M

2017-09-01

Purpose To assess the magnitude of regional response to respiratory therapeutic agents in the lungs by using treatment response mapping (TRM) with hyperpolarized gas magnetic resonance (MR) imaging. TRM was used to quantify regional physiologic response in adults with asthma who underwent a bronchodilator challenge. Materials and Methods This study was approved by the national research ethics committee and was performed with informed consent. Imaging was performed in 20 adult patients with asthma by using hyperpolarized helium 3 ( 3 He) ventilation MR imaging. Two sets of baseline images were acquired before inhalation of a bronchodilating agent (salbutamol 400 μg), and one set was acquired after. All images were registered for voxelwise comparison. Regional treatment response, ΔR(r), was calculated as the difference in regional gas distribution (R[r] = ratio of inhaled gas to total volume of a voxel when normalized for lung inflation volume) before and after intervention. A voxelwise activation threshold from the variability of the baseline images was applied to ΔR(r) maps. The summed global treatment response map (ΔR net ) was then used as a global lung index for comparison with metrics of bronchodilator response measured by using spirometry and the global imaging metric percentage ventilated volume (%VV). Results ΔR net showed significant correlation (P < .01) with changes in forced expiratory volume in 1 second (r = 0.70), forced vital capacity (r = 0.84), and %VV (r = 0.56). A significant (P < .01) positive treatment effect was detected with all metrics; however, ΔR net showed a lower intersubject coefficient of variation (64%) than all of the other tests (coefficient of variation, ≥99%). Conclusion TRM provides regional quantitative information on changes in inhaled gas ventilation in response to therapy. This method could be used as a sensitive regional outcome metric for novel respiratory interventions. © RSNA, 2017 Online supplemental material is available for this article.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

PubMed Central

Li, Laquan; Wang, Jian; Lu, Wei; Tan, Shan

2016-01-01

Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L2 regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L2 regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin’s lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial direction. PMID:28603407

High Resolution Ecosystem Structure, Biomass and Blue Carbon stocks in Mangrove Ecosystems- Methods and Applications of Lidar, radar Interferometry and High Resolution imagery

NASA Astrophysics Data System (ADS)

Lagomasino, D.; Fatoyinbo, T. E.; Lee, S. K.; Feliciano, E. A.; Simard, M.; Trettin, C.

2016-12-01

Earth's climate is determined by the exchange of radiant energy between the Sun, Earth and space. The absorbed solar radiation (ASR) fuels the climate system, providing the energy required for atmospheric and oceanic motions, while the system cools by emitting outgoing longwave (LW) radiation to space. A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget along with the associated atmospheric and surface properties that influence it. CERES data products utilize a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, polar orbiting and geostationary spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. Here we use simple diagnostic model of Earth's albedo and CERES Energy Balanced and Filled (EBAF) Ed4.0 data for March 2000-February 2016 to quantify interannual variations in SW TOA flux associated with surface albedo and atmospheric reflectance and transmittance variations. Surface albedo variations account for <0.5% of the total SW TOA flux variance over the tropics and 4% globally. Variations in atmospheric reflectance and transmittance account for virtually all of the total SW TOA flux variance over the tropics and only 81% globally. The remaining 15% of the global SW TOA flux variance is explained by the co-variance of surface albedo and atmospheric reflectance/transmittance. Equatorward of 60-degree latitude, the atmospheric contribution exceeds that of the surface by at least an order-of-magnitude. In contrast, the surface and atmospheric variations contribute equally poleward of 60S and surface variations account for twice as much as the atmosphere poleward of 60N. However, as much as 40% of the total SW TOA flux variance poleward of 60N is explained by the covariance of surface albedo and atmospheric reflectance/transmittance, highlighting the tight coupling between sea-ice concentration and cloud properties over the Arctic Ocean.

Decomposing Shortwave Top-of-Atmosphere Radiative Flux Variability in Terms of Surface and Atmospheric Contributions Using CERES Observations

NASA Astrophysics Data System (ADS)

Loeb, N. G.; Wong, T.; Wang, H.

2017-12-01

Earth's climate is determined by the exchange of radiant energy between the Sun, Earth and space. The absorbed solar radiation (ASR) fuels the climate system, providing the energy required for atmospheric and oceanic motions, while the system cools by emitting outgoing longwave (LW) radiation to space. A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget along with the associated atmospheric and surface properties that influence it. CERES data products utilize a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, polar orbiting and geostationary spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. Here we use simple diagnostic model of Earth's albedo and CERES Energy Balanced and Filled (EBAF) Ed4.0 data for March 2000-February 2016 to quantify interannual variations in SW TOA flux associated with surface albedo and atmospheric reflectance and transmittance variations. Surface albedo variations account for <0.5% of the total SW TOA flux variance over the tropics and 4% globally. Variations in atmospheric reflectance and transmittance account for virtually all of the total SW TOA flux variance over the tropics and only 81% globally. The remaining 15% of the global SW TOA flux variance is explained by the co-variance of surface albedo and atmospheric reflectance/transmittance. Equatorward of 60-degree latitude, the atmospheric contribution exceeds that of the surface by at least an order-of-magnitude. In contrast, the surface and atmospheric variations contribute equally poleward of 60S and surface variations account for twice as much as the atmosphere poleward of 60N. However, as much as 40% of the total SW TOA flux variance poleward of 60N is explained by the covariance of surface albedo and atmospheric reflectance/transmittance, highlighting the tight coupling between sea-ice concentration and cloud properties over the Arctic Ocean.

Solving ill-posed inverse problems using iterative deep neural networks

NASA Astrophysics Data System (ADS)

Adler, Jonas; Öktem, Ozan

2017-12-01

We propose a partially learned approach for the solution of ill-posed inverse problems with not necessarily linear forward operators. The method builds on ideas from classical regularisation theory and recent advances in deep learning to perform learning while making use of prior information about the inverse problem encoded in the forward operator, noise model and a regularising functional. The method results in a gradient-like iterative scheme, where the ‘gradient’ component is learned using a convolutional network that includes the gradients of the data discrepancy and regulariser as input in each iteration. We present results of such a partially learned gradient scheme on a non-linear tomographic inversion problem with simulated data from both the Sheep-Logan phantom as well as a head CT. The outcome is compared against filtered backprojection and total variation reconstruction and the proposed method provides a 5.4 dB PSNR improvement over the total variation reconstruction while being significantly faster, giving reconstructions of 512 × 512 pixel images in about 0.4 s using a single graphics processing unit (GPU).

Multiband optical variability of the blazar OJ 287 during its outbursts in 2015-2016

NASA Astrophysics Data System (ADS)

Gupta, Alok C.; Agarwal, Aditi; Mishra, Alka; Gaur, H.; Wiita, P. J.; Gu, M. F.; Kurtanidze, O. M.; Damljanovic, G.; Uemura, M.; Semkov, E.; Strigachev, A.; Bachev, R.; Vince, O.; Zhang, Z.; Villarroel, B.; Kushwaha, P.; Pandey, A.; Abe, T.; Chanishvili, R.; Chigladze, R. A.; Fan, J. H.; Hirochi, J.; Itoh, R.; Kanda, Y.; Kawabata, M.; Kimeridze, G. N.; Kurtanidze, S. O.; Latev, G.; Dimitrova, R. V. Muñoz; Nakaoka, T.; Nikolashvili, M. G.; Shiki, K.; Sigua, L. A.; Spassov, B.

2017-03-01

We present recent optical photometric observations of the blazar OJ 287 taken during 2015 September-2016 May. Our intense observations of the blazar started in 2015 November and continued until 2016 May and included detection of the large optical outburst in 2015 December that was predicted using the binary black hole model for OJ 287. For our observing campaign, we used a total of nine ground-based optical telescopes of which one is in Japan, one is in India, three are in Bulgaria, one is in Serbia, one is in Georgia, and two are in the USA. These observations were carried out in 102 nights with a total of ∼1000 image frames in BVRI bands, though the majority were in the R band. We detected a second comparably strong flare in 2016 March. In addition, we investigated multiband flux variations, colour variations, and spectral changes in the blazar on diverse time-scales as they are useful in understanding the emission mechanisms. We briefly discuss the possible physical mechanisms most likely responsible for the observed flux, colour, and spectral variability.

Preliminary Results on Irradiance Measurements from Lyra and Swap

NASA Astrophysics Data System (ADS)

Kumara, S. T.; Kariyappa, R.; Dominique, M.; Berghmans, D.; Damé, L.; Hochedez, J. F.; Doddamani, V. H.; Chitta, Lakshmi Pradeep

The first and preliminary results of the photometry of Large Yield Radiometer (LYRA) and Sun Watcher using Active Pixel system detector and Image Processing (SWAP) onboard PROBA2 are presented in this paper. To study the day-to-day variations of LYRA irradiance, we have compared the LYRA irradiance values (observed Sun as a star) measured in Aluminum filter channel (171Å-500Å) with spatially resolved full-disk integrated intensity values measured with SWAP (174Å) and Ca II K 1 Å index values (ground-based observations from NSO/Sac Peak) for the period from 01 April 2010 to 15 Mar 2011. We found that there is a good correlation between these parameters. This indicates that the spatial resolution of SWAP complements the high temporal resolution of LYRA. Hence SWAP can be considered as an additional radiometric channel. Also the K emission index is the integrated intensity (or flux) over a 1 Å band centered on the K line and is proportional to the total emission from the chromosphere; this comparison clearly explains that the LYRA irradiance variations are due to the various magnetic features, which are contributing significantly. In addition to this we have made an attempt to segregate coronal features from full-disk SWAP images. This will help to understand and determine the actual contribution of the individual coronal feature to LYRA irradiance variations.

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.

Resolution enhancement of tri-stereo remote sensing images by super resolution methods

NASA Astrophysics Data System (ADS)

Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

2016-10-01

Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

Optimization-Based Image Reconstruction with Artifact Reduction in C-Arm CBCT

PubMed Central

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

2016-01-01

We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g., data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility. PMID:27694700

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Improved wrist pannus volume measurement from contrast-enhanced MRI in rheumatoid arthritis using shuffle transform.

PubMed

Xanthopoulos, Emily; Hutchinson, Charles E; Adams, Judith E; Bruce, Ian N; Nash, Anthony F P; Holmes, Andrew P; Taylor, Christopher J; Waterton, John C

2007-01-01

Contrast-enhanced MRI is of value in assessing rheumatoid pannus in the hand, but the images are not always easy to quantitate. To develop and evaluate an improved measurement of volume of enhancing pannus (VEP) in the hand in human rheumatoid arthritis (RA). MR images of the hand and wrist were obtained for 14 patients with RA at 0, 1 and 13 weeks. Volume of enhancing pannus was measured on images created by subtracting precontrast T1-weighted images from contrast-enhanced T1-weighted images using a shuffle transformation technique. Maximum intensity projection (MIP) and 3D volume rendering of the images were used as a guide to identify the pannus and any contrast-enhanced veins. Visualisation of pannus was much improved following the shuffle transform. Between 0 weeks and 1 week, the mean value of the within-subject coefficient of variation (CoV) was 0.13 and the estimated total CoV was 0.15. There was no evidence of significant increased variability within the 13-week interval for the complete sample of patients. Volume of enhancing pannus can be measured reproducibly in the rheumatoid hand using 3D contrast-enhanced MRI and shuffle transform.

Determining the coating thickness of tablets by chiseling and image analysis.

PubMed

Sasić, Slobodan

2010-09-15

Several tablets are chiseled and imaged in order to determine the variation in the coating thickness with the addition of the coating material (weight-gain). Chiseling is carried out with an ultrasonic chisel. The chiseled tablets are imaged in full and these images are exported into programming language Matlab in order to numerically analyze all the pixels along one side of the tablet. The coating thickness is statistically assessed at four cutting depths for three tablets obtained from four weight-gain experiments, a total of 48 images. The coating layer is clearly visible and determinable in the 'white-light' images even for the smallest weight gain of 1% but with sizeable errors due to the diffused boundaries between the coating and the core on one, and the coating and the background on the other side. Addition of the coating material clearly increases the coating thickness which is found to be somewhat higher at the top of the tablets than at the edges. Two approaches for assessment of the coating thickness are tested and are found to be in a very good agreement except for the thinnest coating layer. Copyright 2010 Elsevier B.V. All rights reserved.

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

PubMed Central

Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.

2014-01-01

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949

A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

PubMed

Guo, Lu; Shen, Shuming; Harris, Eleanor; Wang, Zheng; Jiang, Wei; Guo, Yu; Feng, Yuanming

2014-01-01

To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors. A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV) delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT) and tri-modality (MRI/CT/PET) image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV), the average distance between surface and centroid (ADSC), and the local standard deviation (SDlocal). Analysis of COV was also performed to evaluate intra-observer volume variation. The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09) and 0.07(± 0.01) for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05) with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm) and patient 3 (from 0.42 cm to 0.36 cm) with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00) with the tri-modality method as compared with using the dual-modality method. With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.

Accuracy of the Heidelberg Spectralis in the alignment between near-infrared image and tomographic scan in a model eye: a multicenter study.

PubMed

Barteselli, Giulio; Bartsch, Dirk-Uwe; Viola, Francesco; Mojana, Francesca; Pellegrini, Marco; Hartmann, Kathrin I; Benatti, Eleonora; Leicht, Simon; Ratiglia, Roberto; Staurenghi, Giovanni; Weinreb, Robert N; Freeman, William R

2013-09-01

To evaluate temporal changes and predictors of accuracy in the alignment between simultaneous near-infrared image and optical coherence tomography (OCT) scan on the Heidelberg Spectralis using a model eye. Laboratory investigation. After calibrating the device, 6 sites performed weekly testing of the alignment for 12 weeks using a model eye. The maximum error was compared with multiple variables to evaluate predictors of inaccurate alignment. Variables included the number of weekly scanned patients, total number of OCT scans and B-scans performed, room temperature and its variation, and working time of the scanning laser. A 4-week extension study was subsequently performed to analyze short-term changes in the alignment. The average maximum error in the alignment was 15 ± 6 μm; the greatest error was 35 μm. The error increased significantly at week 1 (P = .01), specifically after the second imaging study (P < .05); reached a maximum after the eighth patient (P < .001); and then varied randomly over time. Predictors for inaccurate alignment were temperature variation and scans per patient (P < .001). For each 1 unit of increase in temperature variation, the estimated increase in maximum error was 1.26 μm. For the average number of scans per patient, each increase of 1 unit increased the error by 0.34 μm. Overall, the accuracy of the Heidelberg Spectralis was excellent. The greatest error happened in the first week after calibration, and specifically after the second imaging study. To improve the accuracy, room temperature should be kept stable and unnecessary scans should be avoided. The alignment of the device does not need to be checked on a regular basis in the clinical setting, but it should be checked after every other patient for more precise research purposes. Published by Elsevier Inc.

On non-invasive 2D and 3D Chromatic White Light image sensors for age determination of latent fingerprints.

PubMed

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. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Visualization of the aneurysm wall: a 7.0-tesla magnetic resonance imaging study.

PubMed

Kleinloog, Rachel; Korkmaz, Emine; Zwanenburg, Jaco J M; Kuijf, Hugo J; Visser, Fredy; Blankena, Roos; Post, Jan A; Ruigrok, Ynte M; Luijten, Peter R; Regli, Luca; Rinkel, Gabriel J E; Verweij, Bon H

2014-12-01

Risk prediction of rupture of intracranial aneurysms is poor and is based mainly on lumen characteristics. However, characteristics of the aneurysm wall may be more informative predictors. The limited resolution of currently available imaging techniques and the thin aneurysm wall make imaging of wall thickness challenging. To introduce a novel protocol for imaging wall thickness variation using ultra--high-resolution 7.0-Tesla (7.0-T) magnetic resonance imaging (MRI). We studied 33 unruptured intracranial aneurysms in 24 patients with a T1-weighted 3-dimensional magnetization-prepared inversion-recovery turbo-spin-echo whole-brain sequence with a resolution of 0.8 × 0.8 × 0.8 mm. We performed a validation study with a wedge phantom and with 2 aneurysm wall biopsies obtained during aneurysm treatment using ex vivo MRI and histological examination and correlating variations in MRI signal intensity with variations in actual thickness of the aneurysm wall. In vivo, the aneurysm wall was visible in 28 of the 33 aneurysms. Variation in signal intensity was observed in all visible aneurysm walls. Ex vivo MRI showed variation in signal intensity across the wall of the biopsies, similar to that observed on the in vivo images. Signal intensity and actual thickness in both biopsies had a linear correlation, with Pearson correlation coefficients of 0.85 and 0.86. Unruptured intracranial aneurysm wall and its variation in thickness can be visualized with 7.0-T MRI. Aneurysm wall thickness variation can now be further studied as a risk factor for rupture in prospective studies.

Study on the relationship between the lake area variations of Qinghai-Tibetan Plateau and the corresponding climate change in their basins

NASA Astrophysics Data System (ADS)

Guozhuang, Shen; Jingjuan, Liao; Huadong, Guo; Yingkui, Li

2014-03-01

Qinghai-Tibetan Plateau is the largest lake area in China, with a total area of existing lakes of 36,900km2, accounting for 52% of the total lake area of China. Lakes on the Tibetan Plateau play critical roles in the water cycle and ecological and environment systems of the Plateau. The global trend of warming up is increasing obviously, which has led to major changes in the climate conditions in China, even in the world. Whereas, when they analyse the relationship they just use the weather station's recording data, without any spatial analysis of the climate data. Here, we will do some researches on the relationship between the 10 selected lakes' area variation and the corresponding climate change in their drainage basin and discuss how the lakes changes in recent 40 years using the climate data processed using the spatial kriging. Thus, the drainage area can be taken into account and a real relationship can be pointed out. In order to study the relationship, Landsat MSS data, Landsat TM, Landsat ETM images, the topographic map have been collected to extract the variation of lake area. The 131 weather stations climate data, including precipitation, temperature, sun shine duration, evaporation are chosen to study the relationship. After extraction of the area of the lakes, a multivariate statistical analysis method was used to test the relationship between the area of the lakes and the global climate change, including the change of the temperature, the precipitation, and other factors. The variation of lakes in Qinghai-Tibetan Plateau is related to the mean temperature, the precipitation and saturation vapour pressure. But the frozen soil may affect the lake area variation to some extent.

Unilateral congenital elongation of the cervical part of the internal carotid artery with kinking and looping: two case reports and review of the literature

PubMed Central

Ovchinnikov, Nikolai A; Rao, Ramesh T; Rao, Suresh R

2007-01-01

Unilateral and bilateral variation in the course and elongation of the cervical (extracranial) part of the internal carotid artery (ICA) leading to its tortuosity, kinking and coiling or looping is not a rare condition, which could be caused by both embryological and acquired factors. Patients with such variations may be asymptomatic in some cases; in others, they can develop cerebrovascular symptoms due to carotid stenosis affecting cerebral circulation. The risk of transient ischemic attacks in patients with carotid stenosis is high and its surgical correction is indicated for the prevention of ischemic stroke. Detection of developmental variations of the ICA and evaluation of its stenotic areas is very important for surgical interventions and involves specific diagnostic imaging techniques for vascular lesions including contrast arteriography, duplex ultrasonography and magnetic resonance angiography. Examination of obtained images in cases of unusual and complicated variations of vascular pattern of the ICA may lead to confusion in interpretation of data. Awareness about details and topographic anatomy of variations of the ICA may serve as a useful guide for both radiologists and vascular surgeons. It may help to prevent diagnostic errors, influence surgical tactics and interventional procedures and avoid complications during the head and neck surgery. Our present study was conducted with a purpose of updating data about developmental variations of the ICA. Dissections of the main neurovascular bundle of the head and neck were performed on a total 14 human adult cadavers (10 – Africans: 7 males & 3 females and 4 – East Indians: all males). Two cases of unilateral congenital elongation of the cervical part of the ICA with kinking and looping and carotid stenoses were found only in African males. Here we present their detailed case reports with review of the literature. PMID:17650347

Annual and Seasonal Global Variation in Total Ozone and Layer-Mean Ozone, 1958-1987 (1991)

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

Angell, J. K.; Korshover, J.; Planet, W. G.

For 1958 through 1987, this data base presents total ozone variations and layer mean ozone variations expressed as percent deviations from the 1958 to 1977 mean. The total ozone variations were derived from mean monthly ozone values published in Ozone Data for the World by the Atmospheric Environment Service in cooperation with the World Meteorological Organization. The layer mean ozone variations are derived from ozonesonde and Umkehr observations. The data records include year, seasonal and annual total ozone variations, and seasonal and annual layer mean ozone variations. The total ozone data are for four regions (Soviet Union, Europe, North America,more » and Asia); five climatic zones (north and south polar, north and south temperate, and tropical); both hemispheres; and the world. Layer mean ozone data are for four climatic zones (north and south temperate and north and south polar) and for the stratosphere, troposphere, and tropopause layers. The data are in two files [seasonal and year-average total ozone (13.4 kB) and layer mean ozone variations (24.2 kB)].« less

Cone Beam CT Imaging Analysis of Interfractional Variations in Bladder Volume and Position During Radiotherapy for Bladder Cancer

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

Yee, Don, E-mail: dony@ualberta.c; Parliament, Matthew; Rathee, Satyapal

2010-03-15

Purpose: To quantify daily bladder size and position variations during bladder cancer radiotherapy. Methods and Materials: Ten bladder cancer patients underwent daily cone beam CT (CBCT) imaging of the bladder during radiotherapy. Bladder and planning target volumes (bladder/PTV) from CBCT and planning CT scans were compared with respect to bladder center-of-mass shifts in the x (lateral), y (anterior-posterior), and z (superior-inferior) coordinates, bladder/PTV size, bladder/PTV margin positions, overlapping areas, and mutually exclusive regions. Results: A total of 262 CBCT images were obtained from 10 bladder cancer patients. Bladder center of mass shifted most in the y coordinate (mean, -0.32 cm).more » The anterior bladder wall shifted the most (mean, -0.58 cm). Mean ratios of CBCT-derived bladder and PTV volumes to planning CT-derived counterparts were 0.83 and 0.88. The mean CBCT-derived bladder volume (+- standard deviation [SD]) outside the planning CT counterpart was 29.24 cm{sup 3} (SD, 29.71 cm{sup 3}). The mean planning CT-derived bladder volume outside the CBCT counterpart was 47.74 cm{sup 3} (SD, 21.64 cm{sup 3}). The mean CBCT PTV outside the planning CT-derived PTV was 47.35 cm{sup 3} (SD, 36.51 cm{sup 3}). The mean planning CT-derived PTV outside the CBCT-derived PTV was 93.16 cm{sup 3} (SD, 50.21). The mean CBCT-derived bladder volume outside the planning PTV was 2.41 cm{sup 3} (SD, 3.97 cm{sup 3}). CBCT bladder/ PTV volumes significantly differed from planning CT counterparts (p = 0.047). Conclusions: Significant variations in bladder and PTV volume and position occurred in patients in this trial.« less

Bayesian Quantification of Contrast-Enhanced Ultrasound Images With Adaptive Inclusion of an Irreversible Component.

PubMed

Rizzo, Gaia; Tonietto, Matteo; Castellaro, Marco; Raffeiner, Bernd; Coran, Alessandro; Fiocco, Ugo; Stramare, Roberto; Grisan, Enrico

2017-04-01

Contrast Enhanced Ultrasound (CEUS) is a sensitive imaging technique to assess tissue vascularity and it can be particularly useful in early detection and grading of arthritis. In a recent study we have shown that a Gamma-variate can accurately quantify synovial perfusion and it is flexible enough to describe many heterogeneous patterns. However, in some cases the heterogeneity of the kinetics can be such that even the Gamma model does not properly describe the curve, with a high number of outliers. In this work we apply to CEUS data the single compartment recirculation model (SCR) which takes explicitly into account the trapping of the microbubbles contrast agent by adding to the single Gamma-variate model its integral. The SCR model, originally proposed for dynamic-susceptibility magnetic resonance imaging, is solved here at pixel level within a Bayesian framework using Variational Bayes (VB). We also include the automatic relevant determination (ARD) algorithm to automatically infer the model complexity (SCR vs. Gamma model) from the data. We demonstrate that the inclusion of trapping best describes the CEUS patterns in 50% of the pixels, with the other 50% best fitted by a single Gamma. Such results highlight the necessity of the use ARD, to automatically exclude the irreversible component where not supported by the data. VB with ARD returns precise estimates in the majority of the kinetics (88% of total percentage of pixels) in a limited computational time (on average, 3.6 min per subject). Moreover, the impact of the additional trapping component has been evaluated for the differentiation of rheumatoid and non-rheumatoid patients, by means of a support vector machine classifier with backward feature selection. The results show that the trapping parameter is always present in the selected feature set, and improves the classification.

Prediction of foal carcass composition and wholesale cut yields by using video image analysis.

PubMed

Lorenzo, J M; Guedes, C M; Agregán, R; Sarriés, M V; Franco, D; Silva, S R

2018-01-01

This work represents the first contribution for the application of the video image analysis (VIA) technology in predicting lean meat and fat composition in the equine species. Images of left sides of the carcass (n=42) were captured from the dorsal, lateral and medial views using a high-resolution digital camera. A total of 41 measurements (angles, lengths, widths and areas) were obtained by VIA. The variation of percentage of lean meat obtained from the forequarter (FQ) and hindquarter (HQ) carcass ranged between 5.86% and 7.83%. However, the percentage of fat (FAT) obtained from the FQ and HQ carcass presented a higher variation (CV between 41.34% and 44.58%). By combining different measurements and using prediction models with cold carcass weight (CCW) and VIA measurement the coefficient of determination (k-fold-R 2) were 0.458 and 0.532 for FQ and HQ, respectively. On the other hand, employing the most comprehensive model (CCW plus all VIA measurements), the k-fold-R 2 increased from 0.494 to 0.887 and 0.513 to 0.878 with respect to the simplest model (only with CCW), while precision increased with the reduction in the root mean square error (2.958 to 0.947 and 1.841 to 0.787) for the hindquarter fat and lean percentage, respectively. With CCW plus VIA measurements is possible to explain the wholesale value cuts yield variation (k-fold-R 2 between 0.533 and 0.889). Overall, the VIA technology performed in the present study could be considered as an accurate method to assess the horse carcass composition which could have a role in breeding programmes and research studies to assist in the development of a value-based marketing system for horse carcass.

An Estimate of Changes in the Sun's Total Irradiance Caused by UV Irradiance Variations from 1874 to 1988

NASA Technical Reports Server (NTRS)

Lean, J.

1990-01-01

Enhanced emission from bright solar faculae is a source of significant variation in the sun's total irradiance. Relative to the emission from the quiet sun, facular emission is known to be considerably greater at UV wavelengths than at visible wavelengths. Determining the spectral dependence of facular emission is of interest for the physical insight this may provide to the origin of the sun's irradiance variations. It is also of interest because solar radiation at lambda less than 300 nm is almost totally absorbed in the Earth's atmosphere. Depending on the magnitude of the UV irradiance variations, changes in the sun's irradiance that penetrates to the Earth's surface may not be equivalent to total irradiance variations measured above the Earth's atmosphere. Using an empirical model of total irradiance variations which accounts separately for changes caused by bright faculae from those associated with dark sunspots, the contribution of UV irradiance variations to changes in the sun's total irradiance is estimated during solar cycles 12 to 21.

Scanning in situ Spectroscopy platform for imaging surgical breast tissue specimens

PubMed Central

Krishnaswamy, Venkataramanan; Laughney, Ashley M.; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.

2013-01-01

A non-contact localized spectroscopic imaging platform has been developed and optimized to scan 1x1cm2 square regions of surgically resected breast tissue specimens with ~150-micron resolution. A color corrected, image-space telecentric scanning design maintained a consistent sampling geometry and uniform spot size across the entire imaging field. Theoretical modeling in ZEMAX allowed estimation of the spot size, which is equal at both the center and extreme positions of the field with ~5% variation across the designed waveband, indicating excellent color correction. The spot sizes at the center and an extreme field position were also measured experimentally using the standard knife-edge technique and were found to be within ~8% of the theoretical predictions. Highly localized sampling offered inherent insensitivity to variations in background absorption allowing direct imaging of local scattering parameters, which was validated using a matrix of varying concentrations of Intralipid and blood in phantoms. Four representative, pathologically distinct lumpectomy tissue specimens were imaged, capturing natural variations in tissue scattering response within a given pathology. Variations as high as 60% were observed in the average reflectance and relative scattering power images, which must be taken into account for robust classification performance. Despite this variation, the preliminary data indicates discernible scatter power contrast between the benign vs malignant groups, but reliable discrimination of pathologies within these groups would require investigation into additional contrast mechanisms. PMID:23389199

In-Situ Lithospheric Rheology Measurement Using Isostatic Response and Geophysical State

NASA Astrophysics Data System (ADS)

Lowry, A. R.; Becker, T. W.; Buehler, J. S.; ma, X.; Miller, M. S.; Perez-Gussinye, M.; Ravat, D.; Schutt, D.

2013-12-01

Measurements of effective elastic thickness, Te, from flexural isostatic modeling are sensitive to flow rheology of the lithosphere. Nevertheless, Te has not been widely used to estimate in-situ rheology. Past methodological controversies regarding Te measurement are partly to blame for under-utilization of isostatic response in rheology studies, but these controversies are now largely resolved. The remaining hurdles include uncertainties in properties of geophysical state such as temperature, lithology, and water content. These are ambiguous in their relative contributions to total strength, and the unknown state-of-stress adds to ambiguity in the rheology. Dense seismic and other geophysical arrays such as EarthScope's USArray are providing a wealth of new information about physical state of the lithosphere, however, and these data promise new insights into rheology and deformation processes. For example, new estimates of subsurface mass distributions derived from seismic data enable us to examine controversial assumptions about the nature of lithospheric loads. Variations in crustal lithology evident in bulk crustal velocity ratio, vP/vS, contribute a surprisingly large fraction of total loading. Perhaps the most interesting new information on physical state derives from imaging of uppermost mantle velocities using refracted mantle phases, Pn and Sn, and depths to negative velocity gradients imaged as converted phases in receiver functions (so-called seismic lithosphere-asthenosphere boundary, 'LAB', and mid-lithosphere discontinuity, 'MLD'). Imaging of the ~580°C isotherm associated with the phase transition from alpha- to beta-quartz affords another exciting new avenue for investigation, in part because the transition closely matches the Curie temperature thought to control magnetic bottom in some continental crust. Reconciling seismic estimates of temperature variations with measurements of Te and upper-mantle negative velocity gradients in the US requires that we invoke variations in lithology, water concentrations, and/or membrane stress. In deforming lithosphere, Te and Pn are best-reconciled using a wet quartz crustal lithology, wet olivine mantle lithology, and large membrane stress. More stable lithosphere to the east is best-modeled with a dry feldspar or pyroxene crustal lithology and dry olivine in the mantle. Greater crustal quartz abundance in deforming lithosphere (and in ancient orogens further east) is observed independently in measurements of bulk-crustal vP/vS. Independent evidence also supports the inference of variable water concentrations. Taken together, these lines of evidence suggest that lithology and water abundance are at least as important as temperature variation in determining rheological behavior of the lithosphere.

Imaging metallic samples using electrical capacitance tomography: forward modelling and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Hosani, E. Al; Zhang, M.; Abascal, J. F. P. J.; Soleimani, M.

2016-11-01

Electrical capacitance tomography (ECT) is an imaging technology used to reconstruct the permittivity distribution within the sensing region. So far, ECT has been primarily used to image non-conductive media only, since if the conductivity of the imaged object is high, the capacitance measuring circuit will be almost shortened by the conductivity path and a clear image cannot be produced using the standard image reconstruction approaches. This paper tackles the problem of imaging metallic samples using conventional ECT systems by investigating the two main aspects of image reconstruction algorithms, namely the forward problem and the inverse problem. For the forward problem, two different methods to model the region of high conductivity in ECT is presented. On the other hand, for the inverse problem, three different algorithms to reconstruct the high contrast images are examined. The first two methods are the linear single step Tikhonov method and the iterative total variation regularization method, and use two sets of ECT data to reconstruct the image in time difference mode. The third method, namely the level set method, uses absolute ECT measurements and was developed using a metallic forward model. The results indicate that the applications of conventional ECT systems can be extended to metal samples using the suggested algorithms and forward model, especially using a level set algorithm to find the boundary of the metal.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

Remote sensing of forest canopy and leaf biochemical contents

NASA Technical Reports Server (NTRS)

Peterson, David L.; Matson, Pamela A.; Card, Don H.; Aber, John D.; Wessman, Carol; Swanberg, Nancy; Spanner, Michael

1988-01-01

Recent research on the remote sensing of forest leaf and canopy biochemical contents suggests that the shortwave IR region contains this information; laboratory analyses of dry ground leaves have yielded reliable predictive relationships between both leaf nitrogen and lignin with near-IR spectra. Attention is given to the application of these laboratory techniques to a limited set of spectra from fresh, whole leaves of conifer species. The analysis of Airborne Imaging Spectrometer data reveals that total water content variations in deciduous forest canopies appear as overall shifts in the brightness of raw spectra.

PR01 - The Effects of Total Sleep Deprivation and Recovery Sleep on Cognitive Performance and Brain Function

DTIC Science & Technology

2006-08-01

characterizing brain areas using fMRI activation during parametric variations of attentional load.Neuron, 2001, 32: 737–745. Doran, S . M., Van Dongen...four nouns. Three images collected at the begin- ning of each run were omitted form the analysis. The entire task lasted 300 s . Data Analysis fMRI data...The views, opinions and/or findings contained in this report are those of the author( s ) and should not be construed as an official Department of the

Light-driven liquid microlenses

NASA Astrophysics Data System (ADS)

Angelini, A.; Pirani, F.; Frascella, F.; Ricciardi, S.; Descrovi, E.

2017-02-01

We propose a liquid polymeric compound based on photo-responsive azo-polymers to be used as light-activated optical element with tunable and reversible functionalities. The interaction of a laser beam locally modifies the liquid density thus producing a refractive index gradient. The laser induced refractive index profiles are observed along the optical axis of the microscope to evaluate the total phase shift induced and along the orthogonal direction to provide the axial distribution of the refractive index variation. The focusing and imaging properties of the liquid lenses as functions of the light intensity are illustrated.

An l1-TV algorithm for deconvolution with salt and pepper noise

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

Wohlberg, Brendt; Rodriguez, Paul

2008-01-01

There has recently been considerable interest in applying Total Variation with an {ell}{sup 1} data fidelity term to the denoising of images subject to salt and pepper noise, but the extension of this formulation to more general problems, such as deconvolution, has received little attention, most probably because most efficient algorithms for {ell}{sup 1}-TV denoising can not handle more general inverse problems. We apply the Iteratively Reweighted Norm algorithm to this problem, and compare performance with an alternative algorithm based on the Mumford-Shah functional.

Space-variant restoration of images degraded by camera motion blur.

PubMed

Sorel, Michal; Flusser, Jan

2008-02-01

We examine the problem of restoration from multiple images degraded by camera motion blur. We consider scenes with significant depth variations resulting in space-variant blur. The proposed algorithm can be applied if the camera moves along an arbitrary curve parallel to the image plane, without any rotations. The knowledge of camera trajectory and camera parameters is not necessary. At the input, the user selects a region where depth variations are negligible. The algorithm belongs to the group of variational methods that estimate simultaneously a sharp image and a depth map, based on the minimization of a cost functional. To initialize the minimization, it uses an auxiliary window-based depth estimation algorithm. Feasibility of the algorithm is demonstrated by three experiments with real images.

Body size and allometric variation in facial shape in children.

PubMed

Larson, Jacinda R; Manyama, Mange F; Cole, Joanne B; Gonzalez, Paula N; Percival, Christopher J; Liberton, Denise K; Ferrara, Tracey M; Riccardi, Sheri L; Kimwaga, Emmanuel A; Mathayo, Joshua; Spitzmacher, Jared A; Rolian, Campbell; Jamniczky, Heather A; Weinberg, Seth M; Roseman, Charles C; Klein, Ophir; Lukowiak, Ken; Spritz, Richard A; Hallgrimsson, Benedikt

2018-02-01

Morphological integration, or the tendency for covariation, is commonly seen in complex traits such as the human face. The effects of growth on shape, or allometry, represent a ubiquitous but poorly understood axis of integration. We address the question of to what extent age and measures of size converge on a single pattern of allometry for human facial shape. Our study is based on two large cross-sectional cohorts of children, one from Tanzania and the other from the United States (N = 7,173). We employ 3D facial imaging and geometric morphometrics to relate facial shape to age and anthropometric measures. The two populations differ significantly in facial shape, but the magnitude of this difference is small relative to the variation within each group. Allometric variation for facial shape is similar in both populations, representing a small but significant proportion of total variation in facial shape. Different measures of size are associated with overlapping but statistically distinct aspects of shape variation. Only half of the size-related variation in facial shape can be explained by the first principal component of four size measures and age while the remainder associates distinctly with individual measures. Allometric variation in the human face is complex and should not be regarded as a singular effect. This finding has important implications for how size is treated in studies of human facial shape and for the developmental basis for allometric variation more generally. © 2017 Wiley Periodicals, Inc.

Analysis of subsequent publication of scientific orally presented abstracts of the French National Congress of Radiology. Part II: Focus on the French abstracts.

PubMed

Dangouloff-Ros, V; Ronot, M; Lagadec, M; Vilgrain, V

2015-05-01

To evaluate the publication rate of scientific abstracts that were presented orally at the 2008, 2009, and 2010 annual meetings of the French Society of Radiology by French radiologists, and to perform a French regional analysis. Orally presented abstracts were identified by examining online abstract books of the 2008, 2009, and 2010 annual meetings of the French Society of Radiology, and cross-checked by reviewing the paper version of abstracts for the same period. Only abstracts from French teams were selected. The administrative region of submission was noted for each abstract and for each region the total population, the number of active radiologists, the number of active members of the French Society of Radiology and the number of academic radiologists were noted. Imaging subspecialties were also noted. 625 abstracts were identified resulting in 268 publications (publication rate: 43%). The median number of presentations and publications per region was 18 (range: 1-255) and 7 (range: 0-101), respectively. The ratio per million inhabitants was 7.5 and 3 respectively. The median number of presentations and publications per 100 active radiologists (respectively members of the FSR) was 7 and 3 (respectively 10 and 4). The median number of presentations and publications per academic radiologist were 2.6, and 1.2, respectively. The regional variations for each indicator were high (40-180%). Three subspecialties had a publication rate of more than 50%: thoracic imaging (58%), abdominal imaging (52%), and genitourinary imaging (51%). The publication rate of orally presented French scientific abstracts was high, with important variations according to the regions of origin and imaging subspecialties. Copyright © 2015 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Atmospheric water mapping with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Mountain Pass, California

NASA Technical Reports Server (NTRS)

Conel, James E.; Green, Robert O.; Carrere, Veronique; Margolis, Jack S.; Alley, Ronald E.; Vane, Gregg; Bruegge, Carol J.; Gary, Bruce L.

1988-01-01

Observations are given of the spatial variation of atmospheric precipitable water using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over a desert area in eastern California, derived using a band ratio method and the 940 nm atmospheric water band and 870 nm continuum radiances. The ratios yield total path water from curves of growth supplied by the LOWTRAN 7 atmospheric model. An independent validation of the AVIRIS-derived column abundance at a point is supplied by a spectral hygrometer calibrated with respect to radiosonde observations. Water values conform to topography and fall off with surface elevation. The edge of the water vapor boundary layer defined by topography is thought to have been recovered. The ratio method yields column abundance estimates of good precision and high spatial resolution.

Tailoring magnetic field gradient design to magnet cryostat geometry.

PubMed

Trakic, A; Liu, F; Lopez, H S; Wang, H; Crozier, S

2006-01-01

Eddy currents induced within a magnetic resonance imaging (MRI) cryostat bore during pulsing of gradient coils can be applied constructively together with the gradient currents that generate them, to obtain good quality gradient uniformities within a specified imaging volume over time. This can be achieved by simultaneously optimizing the spatial distribution and temporal pre-emphasis of the gradient coil current, to account for the spatial and temporal variation of the secondary magnetic fields due to the induced eddy currents. This method allows the tailored design of gradient coil/magnet configurations and consequent engineering trade-offs. To compute the transient eddy currents within a realistic cryostat vessel, a low-frequency finite-difference time-domain (FDTD) method using total-field scattered-field (TFSF) scheme has been performed and validated.

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

PubMed Central

Zhang, Rongxiao; Gladstone, David J.; Williams, Benjamin B.; Glaser, Adam K.; Pogue, Brian W.; Jarvis, Lesley A.

2016-01-01

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, composite images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R2 = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial angles, to only 9.8% with the angles optimized. A linear relationship between angle spread and SSD was observed, ranging from 35° at 441 cm, to 39° at 300 cm, with no significant variation in percent-depth dose at midline (R2 = 0.998). For patient studies, factors influencing in vivo correlation between Cherenkov intensity and measured surface dose are still being investigated. Conclusions: Cherenkov intensity correlates to relative dose measured at depth of maximum dose in a uniform, flat phantom. Imaging of phantoms can thus be used to analyze and optimize TSET treatment geometry more extensively and rapidly than thermoluminescent dosimeters or ionization chambers. This work suggests that there could be an expanded role for Cherenkov imaging as a tool to efficiently improve treatment protocols and as a potential verification tool for routine monitoring of unique patient treatments. PMID:26843259

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

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

Andreozzi, Jacqueline M., E-mail: Jacqueline.M.Andreozzi.th@dartmouth.edu, E-mail: Lesley.A.Jarvis@hitchcock.org; Glaser, Adam K.; Zhang, Rongxiao

2016-02-15

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, compositemore » images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R{sup 2} = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial angles, to only 9.8% with the angles optimized. A linear relationship between angle spread and SSD was observed, ranging from 35° at 441 cm, to 39° at 300 cm, with no significant variation in percent-depth dose at midline (R{sup 2} = 0.998). For patient studies, factors influencing in vivo correlation between Cherenkov intensity and measured surface dose are still being investigated. Conclusions: Cherenkov intensity correlates to relative dose measured at depth of maximum dose in a uniform, flat phantom. Imaging of phantoms can thus be used to analyze and optimize TSET treatment geometry more extensively and rapidly than thermoluminescent dosimeters or ionization chambers. This work suggests that there could be an expanded role for Cherenkov imaging as a tool to efficiently improve treatment protocols and as a potential verification tool for routine monitoring of unique patient treatments.« less

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

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

Lee, J; Nishikawa, R; Reiser, I

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benignmore » or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or classification performance. The best segmentation Result does not necessarily lead to the best classification Result. This work has been supported in part by grants from the NIH R21-EB015053. R Nishikawa is receives royalties form Hologic, Inc.« less

WE-EF-303-02: BEST IN PHYSICS (JOINT IMAGING- THERAPY): A Comprehensive Simulation of Image Guided Beam Gating for Liver Tumor Treatments Using Scanned Proton Therapy

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

Zhang, Y; Knopf, A; Weber, D

2015-06-15

Purpose: To evaluate the effectiveness of image guided beam gating for PBS liver treatments under realistic breathing conditions. Methods: We have previously proposed a Beams’ Eye View (BEV) X-ray image system as an online motion monitoring device for deriving a gating signal for PBS proton therapy. Using dedicated 4D dose calculations (4DDC), in this work we have simulated gated liver treatments using three amplitude-based gating windows (10/5/3mm) based on motion extracted from BEV imaging of fiducial markers or the diaphragm. In order to improve motion mitigation, BEV guided gating has also been combined with either volumetric (VS) or layered (LS)more » rescanning. Nine 4DCT(MRI) liver data-sets have been used for the investigation, which not only consider realistic patient geometries but also motion variations between different breathing cycles. All 4D plans have been quantified in terms of plan homogeneity in the PTV (D5-D95), the total estimated treatment time and the beam-on duty cycle. Results: Neither gating nor rescanning can fully retrieve a comparable plan homogeneity to the static case, and considerable reductions of the duty cycle (<10%) were observed as a Result motion variations when small gating windows are used. However, once combined with rescanning, dose homogeneity within 1% of the static plan could be achieved with reasonable prolongation of the treatment time for all 9 subjects. No differences were observed between the efficacy of layered or volumetric re-scanning, or of gating signals extracted from fiducial or diaphragm motions. However, layered rescanning may be preferred over volumetric rescanning when performed in combination with gating as it is generally more time-efficient and dosimetrically robust to patient and motion variations Conclusion Combining BEV beam gating with rescanning is an efficient and effective approach to treating mobile liver tumours, and is equally effective if either the diaphragm or fiducial markers are used as motion surrogates.« less

Individualized statistical learning from medical image databases: application to identification of brain lesions.

PubMed

Erus, Guray; Zacharaki, Evangelia I; Davatzikos, Christos

2014-04-01

This paper presents a method for capturing statistical variation of normal imaging phenotypes, with emphasis on brain structure. The method aims to estimate the statistical variation of a normative set of images from healthy individuals, and identify abnormalities as deviations from normality. A direct estimation of the statistical variation of the entire volumetric image is challenged by the high-dimensionality of images relative to smaller sample sizes. To overcome this limitation, we iteratively sample a large number of lower dimensional subspaces that capture image characteristics ranging from fine and localized to coarser and more global. Within each subspace, a "target-specific" feature selection strategy is applied to further reduce the dimensionality, by considering only imaging characteristics present in a test subject's images. Marginal probability density functions of selected features are estimated through PCA models, in conjunction with an "estimability" criterion that limits the dimensionality of estimated probability densities according to available sample size and underlying anatomy variation. A test sample is iteratively projected to the subspaces of these marginals as determined by PCA models, and its trajectory delineates potential abnormalities. The method is applied to segmentation of various brain lesion types, and to simulated data on which superiority of the iterative method over straight PCA is demonstrated. Copyright © 2014 Elsevier B.V. All rights reserved.

Individualized Statistical Learning from Medical Image Databases: Application to Identification of Brain Lesions

PubMed Central

Erus, Guray; Zacharaki, Evangelia I.; Davatzikos, Christos

2014-01-01

This paper presents a method for capturing statistical variation of normal imaging phenotypes, with emphasis on brain structure. The method aims to estimate the statistical variation of a normative set of images from healthy individuals, and identify abnormalities as deviations from normality. A direct estimation of the statistical variation of the entire volumetric image is challenged by the high-dimensionality of images relative to smaller sample sizes. To overcome this limitation, we iteratively sample a large number of lower dimensional subspaces that capture image characteristics ranging from fine and localized to coarser and more global. Within each subspace, a “target-specific” feature selection strategy is applied to further reduce the dimensionality, by considering only imaging characteristics present in a test subject’s images. Marginal probability density functions of selected features are estimated through PCA models, in conjunction with an “estimability” criterion that limits the dimensionality of estimated probability densities according to available sample size and underlying anatomy variation. A test sample is iteratively projected to the subspaces of these marginals as determined by PCA models, and its trajectory delineates potential abnormalities. The method is applied to segmentation of various brain lesion types, and to simulated data on which superiority of the iterative method over straight PCA is demonstrated. PMID:24607564

Multimodal Imaging and Lighting Bias Correction for Improved μPAD-based Water Quality Monitoring via Smartphones

NASA Astrophysics Data System (ADS)

McCracken, Katherine E.; Angus, Scott V.; Reynolds, Kelly A.; Yoon, Jeong-Yeol

2016-06-01

Smartphone image-based sensing of microfluidic paper analytical devices (μPADs) offers low-cost and mobile evaluation of water quality. However, consistent quantification is a challenge due to variable environmental, paper, and lighting conditions, especially across large multi-target μPADs. Compensations must be made for variations between images to achieve reproducible results without a separate lighting enclosure. We thus developed a simple method using triple-reference point normalization and a fast-Fourier transform (FFT)-based pre-processing scheme to quantify consistent reflected light intensity signals under variable lighting and channel conditions. This technique was evaluated using various light sources, lighting angles, imaging backgrounds, and imaging heights. Further testing evaluated its handle of absorbance, quenching, and relative scattering intensity measurements from assays detecting four water contaminants - Cr(VI), total chlorine, caffeine, and E. coli K12 - at similar wavelengths using the green channel of RGB images. Between assays, this algorithm reduced error from μPAD surface inconsistencies and cross-image lighting gradients. Although the algorithm could not completely remove the anomalies arising from point shadows within channels or some non-uniform background reflections, it still afforded order-of-magnitude quantification and stable assay specificity under these conditions, offering one route toward improving smartphone quantification of μPAD assays for in-field water quality monitoring.

Nakagami-based total variation method for speckle reduction in thyroid ultrasound images.

PubMed

Koundal, Deepika; Gupta, Savita; Singh, Sukhwinder

2016-02-01

A good statistical model is necessary for the reduction in speckle noise. The Nakagami model is more general than the Rayleigh distribution for statistical modeling of speckle in ultrasound images. In this article, the Nakagami-based noise removal method is presented to enhance thyroid ultrasound images and to improve clinical diagnosis. The statistics of log-compressed image are derived from the Nakagami distribution following a maximum a posteriori estimation framework. The minimization problem is solved by optimizing an augmented Lagrange and Chambolle's projection method. The proposed method is evaluated on both artificial speckle-simulated and real ultrasound images. The experimental findings reveal the superiority of the proposed method both quantitatively and qualitatively in comparison with other speckle reduction methods reported in the literature. The proposed method yields an average signal-to-noise ratio gain of more than 2.16 dB over the non-convex regularizer-based speckle noise removal method, 3.83 dB over the Aubert-Aujol model, 1.71 dB over the Shi-Osher model and 3.21 dB over the Rudin-Lions-Osher model on speckle-simulated synthetic images. Furthermore, visual evaluation of the despeckled images shows that the proposed method suppresses speckle noise well while preserving the textures and fine details. © IMechE 2015.

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

Altunbas, Cem, E-mail: caltunbas@gmail.com; Lai, Chao-Jen; Zhong, Yuncheng

Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrancemore » exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results: 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear pixel gain variations as a function of change in x-ray spectrum and intensity. Hence, it can better suppress image artifacts due to beam hardening as well as artifacts that arise from detector entrance exposure variation.« less

Time lapse microscopy observation of cellular structural changes and image analysis of drug treated cancer cells to characterize the cellular heterogeneity.

PubMed

Vaiyapuri, Periasamy S; Ali, Alshatwi A; Mohammad, Akbarsha A; Kandhavelu, Jeyalakshmi; Kandhavelu, Meenakshisundaram

2015-01-01

The effect of Calotropis gigantea latex (CGLX) on human mammary carcinoma cells is not well established. We present the results of this drug activity at total population and single cell level. CGLX inhibited the growth of MCF7 cancer cells at lower IC50 concentration (17 µL/mL). Microscopy of IC50 drug treated cells at 24 hr confirming the appearance of morphological characteristics of apoptotic and necrotic cells, associated with 70% of DNA damage. FACS analysis confirmed that, 10 and 20% of the disruption of cellular mitochondrial nature by at 24 and 48 h, respectively. Microscopic image analysis of total population level proved that MMP changes were statistically significant with P values. The cell to cell variation was confirmed by functional heterogeneity analysis which proves that CGLX was able to induce the apoptosis without the contribution of mitochondria. We conclude that CGLX inhibits cell proliferation, survival, and heterogeneity of pathways in human mammary carcinoma cells. © 2014 Wiley Periodicals, Inc.

The evaluation of lateral pterygoid muscle pathologic changes and insertion patterns in temporomandibular joints with or without disc displacement using magnetic resonance imaging.

PubMed

Imanimoghaddam, M; Madani, A S; Hashemi, E M

2013-09-01

Temporomandibular joint (TMJ) disc displacement is a common disorder in patients with internal derangement. Certain anatomic features of TMJ may make the patient prone to this condition, namely lateral pterygoid muscle (LPM) insertion variations. The aim of this study was to investigate LPM attachments and their relationships with disc displacement and subsequent pathologic changes. A total of 26 patients with clinical temporomandibular disorders (TMDs) and a control group of 14 unaffected individuals were studied. Magnetic resonance images (MRIs) were taken to evaluate LPM insertion patterns, superior LPM head pathologic changes, and relative disc to condyle position. Data registration and analysis were done using SPSS v. 16.0. The most common variation (type I) was shown to be the superior head with two bundles, one attached to the disc and another to the condyle. No significant relationship between LPM insertion type and disc displacement or pathologic changes of the muscle was found. However, a link between disc displacement and muscle pathologic changes was established (P=0.001). Copyright © 2013 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Functional Validation and Comparison Framework for EIT Lung Imaging

PubMed Central

Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Introduction Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. Methods We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Results and Conclusions Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT. PMID:25110887

Regolith thickness over Sinus Iridum: Results from morphology and size-frequency distribution of small impact craters

NASA Astrophysics Data System (ADS)

Fa, Wenzhe; Liu, Tiantian; Zhu, Meng-Hua; Haruyama, Junichi

2014-08-01

High-resolution optical images returned from recent lunar missions provide a new chance for estimation of lunar regolith thickness using morphology and the size-frequency distribution of small impact craters. In this study, regolith thickness over the Sinus Iridum region is estimated using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Cameras (NACs) images. A revised relationship between crater geometry and regolith thickness is proposed based on old experimental data that takes into considering the effect of the illumination angle of the images. In total, 227 high-resolution LROC NAC images are used, and 378,556 impact craters with diameters from 4.2 to 249.8 m are counted, and their morphologies are identified. Our results show that 50% of the Sinus Iridum region has a regolith thickness between 5.1 and 10.7 m, and the mean and median regolith thicknesses are 8.5 and 8.0 m, respectively. There are substantial regional variations in the regolith thickness, with its median value varying from 2.6 to 12.0 m for most regions. Local variations of regolith thickness are found to be correlated with the lunar surface age: the older the surface, the greater the thickness. In addition, sporadically distributed impact ejecta and crater rays are associated with relatively larger regolith thickness, which might result from excavation and transport of materials during the formation of the secondaries of Copernican-aged craters. Our estimated regolith thickness can help with future analysis of Chang'E-3 lunar penetrating radar echoes and studies of the subsurface stratigraphic structure of the Moon.

Peripapillary nerve fiber layer thickness measurement reproducibility using optical coherence tomography.

PubMed

Villain, Max A; Greenfield, David S

2003-01-01

To assess reproducibility of quadrantic and clock hour sectors of retinal nerve fiber layer thickness in normal eyes using optical coherence tomography. Normal eyes of healthy volunteers meeting eligibility criteria were imaged by two inexperienced operators. Six 360 degrees circular scans with a diameter of 3.4 mm centered on the optic disc were obtained during each scanning session, and a baseline image was formed using 3 high-quality images defined by the software. Images were obtained on three different days within a 4-week period. Variance and coefficient of variation (CV) were calculated for quadrantic and retinal nerve fiber layer clock hour sectors obtained from the baseline image. Five normal eyes were scanned. Intraoperator reproducibility was high. The mean (+/- SD) CV for total retinal nerve fiber layer thickness was 5.3 +/- 3.82% and 4.33 +/- 3.7% for operators 1 and 2, respectively. Interoperator reproducibility was good with statistically similar variance for all quadrantic and clock hour retinal nerve fiber layer parameters (P = .42 to .99). The nasal retinal nerve fiber layer was the most variable sector for both operators (mean CV: 10.42% and 7.83% for operators 1 and 2, respectively). Differences in mean total, nasal, temporal, and superior retinal nerve fiber layer thickness were not statistically significant between operators for all eyes; however, for inferior retinal nerve fiber layer thickness, there was a significant (P = .0007) difference between operators in one eye. Peripapillary retinal nerve fiber layer thickness assessments using optical coherence tomography have good intraoperator and interoperator reproducibility. Inexperienced operators can generate useful measurement data with acceptable levels of variance.

Identifying water mass depletion in Northern Iraq observed by GRACE

NASA Astrophysics Data System (ADS)

Mulder, Gert; Olsthoorn, Theo; Al-Manmi, Diary; Schrama, Ernst; Smidt, Ebel

2014-05-01

Observations acquired by Gravity Recovery And Climate Experiment (GRACE) mission indicates a mass loss of 31±3 km3 or 130±14 mm in Northern Iraq between 2006 and 2009. This data is used as an independent validation of a hydrologic model of the region including lake mass variations. We developed a rainfall-runoff model for five tributaries of the Tigris River, based on local geology and climate conditions. Model inputs are precipitation data from Tropical Rainfall Measurement Mission (TRMM) observations, and potential evaporation from GLDAS parameters. Our model includes an extensive network of karstified aquifers that causes large natural groundwater variations in this region. Observed river discharges have been used to calibrate our model. In order to get the total mass variations, we correct for lake mass variations derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data in combination with satellite altimetry and some in-situ data. Our rainfall-runoff model confirms that Northern Iraq suffered a drought between 2006 and 2009 and is consistent with the mass loss observed by GRACE in that period. Also, GRACE picks up the annual cycle predicted by the rainfall-runoff model. The total mass depletion seen by GRACE between 2006 and 2009 is 130±14 mm, which is mainly explained by a lake mass depletion of 74±4 mm and a natural groundwater depletion of approximately 50 mm. Our findings indicate that man-made groundwater extraction has a minor influence in this region while depletion of lake mass and geology play a key role.

[Medical image segmentation based on the minimum variation snake model].

PubMed

Zhou, Changxiong; Yu, Shenglin

2007-02-01

It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

Learning-based stochastic object models for use in optimizing imaging systems

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

It is widely known that the optimization of imaging systems based on objective, or task-based, measures of image quality via computer-simulation requires use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in anatomy within a specified ensemble of patients remains a challenging task. Because they are established by use of image data corresponding a single patient, previously reported numerical anatomical models lack of the ability to accurately model inter- patient variations in anatomy. In certain applications, however, databases of high-quality volumetric images are available that can facilitate this task. In this work, a novel and tractable methodology for learning a SOM from a set of volumetric training images is developed. The proposed method is based upon geometric attribute distribution (GAD) models, which characterize the inter-structural centroid variations and the intra-structural shape variations of each individual anatomical structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations learned from training data. By use of the GAD models, random organ shapes and positions can be generated and integrated to form an anatomical phantom. The randomness in organ shape and position will reflect the variability of anatomy present in the training data. To demonstrate the methodology, a SOM corresponding to the pelvis of an adult male was computed and a corresponding ensemble of phantoms was created. Additionally, computer-simulated X-ray projection images corresponding to the phantoms were computed, from which tomographic images were reconstructed.

Quantifying floral shape variation in 3D using microcomputed tomography: a case study of a hybrid line between actinomorphic and zygomorphic flowers.

PubMed

Wang, Chun-Neng; Hsu, Hao-Chun; Wang, Cheng-Chun; Lee, Tzu-Kuei; Kuo, Yan-Fu

2015-01-01

The quantification of floral shape variations is difficult because flower structures are both diverse and complex. Traditionally, floral shape variations are quantified using the qualitative and linear measurements of two-dimensional (2D) images. The 2D images cannot adequately describe flower structures, and thus lead to unsatisfactory discrimination of the flower shape. This study aimed to acquire three-dimensional (3D) images by using microcomputed tomography (μCT) and to examine the floral shape variations by using geometric morphometrics (GM). To demonstrate the advantages of the 3D-μCT-GM approach, we applied the approach to a second-generation population of florist's gloxinia (Sinningia speciosa) crossed from parents of zygomorphic and actinomorphic flowers. The flowers in the population considerably vary in size and shape, thereby served as good materials to test the applicability of the proposed phenotyping approach. Procedures were developed to acquire 3D volumetric flower images using a μCT scanner, to segment the flower regions from the background, and to select homologous characteristic points (i.e., landmarks) from the flower images for the subsequent GM analysis. The procedures identified 95 landmarks for each flower and thus improved the capability of describing and illustrating the flower shapes, compared with typically lower number of landmarks in 2D analyses. The GM analysis demonstrated that flower opening and dorsoventral symmetry were the principal shape variations of the flowers. The degrees of flower opening and corolla asymmetry were then subsequently quantified directly from the 3D flower images. The 3D-μCT-GM approach revealed shape variations that could not be identified using typical 2D approaches and accurately quantified the flower traits that presented a challenge in 2D images. The approach opens new avenues to investigate floral shape variations.

Head circumference and brain size in autism spectrum disorder: A systematic review and meta-analysis.

PubMed

Sacco, Roberto; Gabriele, Stefano; Persico, Antonio M

2015-11-30

Macrocephaly and brain overgrowth have been associated with autism spectrum disorder. We performed a systematic review and meta-analysis to provide an overall estimate of effect size and statistical significance for both head circumference and total brain volume in autism. Our literature search strategy identified 261 and 391 records, respectively; 27 studies defining percentages of macrocephalic patients and 44 structural brain imaging studies providing total brain volumes for patients and controls were included in our meta-analyses. Head circumference was significantly larger in autistic compared to control individuals, with 822/5225 (15.7%) autistic individuals displaying macrocephaly. Structural brain imaging studies measuring brain volume estimated effect size. The effect size is higher in low functioning autistics compared to high functioning and ASD individuals. Brain overgrowth was recorded in 142/1558 (9.1%) autistic patients. Finally, we found a significant interaction between age and total brain volume, resulting in larger head circumference and brain size during early childhood. Our results provide conclusive effect sizes and prevalence rates for macrocephaly and brain overgrowth in autism, confirm the variation of abnormal brain growth with age, and support the inclusion of this endophenotype in multi-biomarker diagnostic panels for clinical use. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

MUNSELL COLOR ANALYSIS OF LANDSAT COLOR-RATIO-COMPOSITE IMAGES OF LIMONITIC AREAS IN SOUTHWEST NEW MEXICO.

USGS Publications Warehouse

Kruse, Fred A.

1984-01-01

Green areas on Landsat 4/5 - 4/6 - 6/7 (red - blue - green) color-ratio-composite (CRC) images represent limonite on the ground. Color variation on such images was analyzed to determine the causes of the color differences within and between the green areas. Digital transformation of the CRC data into the modified cylindrical Munsell color coordinates - hue, value, and saturation - was used to correlate image color characteristics with properties of surficial materials. The amount of limonite visible to the sensor is the primary cause of color differences in green areas on the CRCs. Vegetation density is a secondary cause of color variation of green areas on Landsat CRC images. Digital color analysis of Landsat CRC images can be used to map unknown areas. Color variations of green pixels allows discrimination among limonitic bedrock, nonlimonitic bedrock, nonlimonitic alluvium, and limonitic alluvium.

Influence of temperature variations on the entropy and correlation of the Grey-Level Co-occurrence Matrix from B-Mode images.

PubMed

Alvarenga, André V; Teixeira, César A; Ruano, Maria Graça; Pereira, Wagner C A

2010-02-01

In this work, the feasibility of texture parameters extracted from B-Mode images were explored in quantifying medium temperature variation. The goal is to understand how parameters obtained from the gray-level content can be used to improve the actual state-of-the-art methods for non-invasive temperature estimation (NITE). B-Mode images were collected from a tissue mimic phantom heated in a water bath. The phantom is a mixture of water, glycerin, agar-agar and graphite powder. This mixture aims to have similar acoustical properties to in vivo muscle. Images from the phantom were collected using an ultrasound system that has a mechanical sector transducer working at 3.5 MHz. Three temperature curves were collected, and variations between 27 and 44 degrees C during 60 min were allowed. Two parameters (correlation and entropy) were determined from Grey-Level Co-occurrence Matrix (GLCM) extracted from image, and then assessed for non-invasive temperature estimation. Entropy values were capable of identifying variations of 2.0 degrees C. Besides, it was possible to quantify variations from normal human body temperature (37 degrees C) to critical values, as 41 degrees C. In contrast, despite correlation parameter values (obtained from GLCM) presented a correlation coefficient of 0.84 with temperature variation, the high dispersion of values limited the temperature assessment.

Robust resolution enhancement optimization methods to process variations based on vector imaging model

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong

2012-03-01

Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.

Identification and Modelling of the In-Plane Reinforcement Orientation Variations in a CFRP Laminate Produced by Manual Lay-Up

NASA Astrophysics Data System (ADS)

Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri

2017-08-01

Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.

Identification and Modelling of the In-Plane Reinforcement Orientation Variations in a CFRP Laminate Produced by Manual Lay-Up

NASA Astrophysics Data System (ADS)

Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri

2018-06-01

Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.

FDG-PET/CT imaging for tumor staging and definition of tumor volumes in radiation treatment planning in non-small cell lung cancer.

PubMed

Zheng, Yuanda; Sun, Xiaojiang; Wang, Jian; Zhang, Lingnan; DI, Xiaoyun; Xu, Yaping

2014-04-01

18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) has the potential to improve the staging and radiation treatment (RT) planning of various tumor sites. However, from a clinical standpoint, questions remain with regard to what extent PET/CT changes the target volume and whether PET/CT reduces interobserver variability in target volume delineation. The present study analyzed the use of FDG-PET/CT images for staging and evaluated the impact of FDG-PET/CT on the radiotherapy volume delineation compared with CT in patients with non-small cell lung cancer (NSCLC) who were candidates for radiotherapy. Intraobserver variation in delineating tumor volumes was also observed. In total, 23 patients with stage I-III NSCLC were enrolled and treated with fractionated RT-based therapy with or without chemotherapy. FDG-PET/CT scans were acquired within two weeks prior to RT. PET and CT data sets were sent to the treatment planning system, Pinnacle, through compact discs. The CT and PET images were subsequently fused by means of a dedicated RT planning system. Gross tumor volume (GTV) was contoured by four radiation oncologists on CT (GTV-CT) and PET/CT images (GTV-PET/CT). The resulting volumes were analyzed and compared. For the first phase, two radiation oncologists outlined the contours together, achieving a final consensus. Based on PET/CT, changes in tumor-node-metastasis categories occurred in 8/23 cases (35%). Radiation targeting with fused FDG-PET and CT images resulted in alterations in radiation therapy planning in 12/20 patients (60%) in comparison with CT targeting. The most prominent changes in GTV were observed in cases with atelectasis. For the second phase, the variation in delineating tumor volumes was assessed by four observers. The mean ratio of largest to smallest CT-based GTV was 2.31 (range, 1.01-5.96). The addition of the PET results reduced the mean ratio to 1.46 (range, 1.02-2.27). PET/CT fusion images may have a potential impact on tumor staging and treatment planning. Implementing matched PET/CT results reduced observer variation in delineating tumor volumes significantly with respect to CT only.

Adiposity is associated with structural properties of the adolescent brain.

PubMed

Schwartz, Deborah H; Dickie, Erin; Pangelinan, Melissa M; Leonard, Gabriel; Perron, Michel; Pike, G Bruce; Richer, Louis; Veillette, Suzanne; Pausova, Zdenka; Paus, Tomáš

2014-12-01

Obesity, a major risk factor for cardiometabolic disease, is associated with variations in a number of structural properties in the adult brain, as assessed with magnetic resonance imaging (MRI). In this study, we investigated the cross-sectional relationship between visceral fat (VF), total body fat (TBF) and three MRI parameters in the brains of typically developing adolescents: (i) T1-weighted (T1W) signal intensity; (ii) T1W signal contrast between white matter (WM) and gray matter (GM); and (iii) magnetization transfer ratio (MTR). In a community-based sample of 970 adolescents (12-18 years old, 466 males), VF was quantified using MRI, and total body fat was measured using a multifrequency bioimpedance. T1W images of the brain were used to determine signal intensity in lobar GM and WM, as well as WM:GM signal contrast. A magnetization transfer (MT) sequence of MT(ON) and MT(OFF) was used to obtain MTR in GM and WM. We found that both larger volumes of VF and more TBF were independently associated with higher signal intensity in WM and higher WM:GM signal contrast, as well as higher MTR in both GM and WM. These relationships were independent of a number of potential confounders, including age, sex, puberty stage, household income and height. Our results suggest that both visceral fat and fat deposited elsewhere in the body are associated independently with structural properties of the adolescent brain. We speculate that these relationships suggest the presence of adiposity-related variations in phospholipid composition of brain lipids. Copyright © 2014. Published by Elsevier Inc.

A Comprehensive Texture Segmentation Framework for Segmentation of Capillary Non-Perfusion Regions in Fundus Fluorescein Angiograms

PubMed Central

Zheng, Yalin; Kwong, Man Ting; MacCormick, Ian J. C.; Beare, Nicholas A. V.; Harding, Simon P.

2014-01-01

Capillary non-perfusion (CNP) in the retina is a characteristic feature used in the management of a wide range of retinal diseases. There is no well-established computation tool for assessing the extent of CNP. We propose a novel texture segmentation framework to address this problem. This framework comprises three major steps: pre-processing, unsupervised total variation texture segmentation, and supervised segmentation. It employs a state-of-the-art multiphase total variation texture segmentation model which is enhanced by new kernel based region terms. The model can be applied to texture and intensity-based multiphase problems. A supervised segmentation step allows the framework to take expert knowledge into account, an AdaBoost classifier with weighted cost coefficient is chosen to tackle imbalanced data classification problems. To demonstrate its effectiveness, we applied this framework to 48 images from malarial retinopathy and 10 images from ischemic diabetic maculopathy. The performance of segmentation is satisfactory when compared to a reference standard of manual delineations: accuracy, sensitivity and specificity are 89.0%, 73.0%, and 90.8% respectively for the malarial retinopathy dataset and 80.8%, 70.6%, and 82.1% respectively for the diabetic maculopathy dataset. In terms of region-wise analysis, this method achieved an accuracy of 76.3% (45 out of 59 regions) for the malarial retinopathy dataset and 73.9% (17 out of 26 regions) for the diabetic maculopathy dataset. This comprehensive segmentation framework can quantify capillary non-perfusion in retinopathy from two distinct etiologies, and has the potential to be adopted for wider applications. PMID:24747681

Face landmark point tracking using LK pyramid optical flow

NASA Astrophysics Data System (ADS)

Zhang, Gang; Tang, Sikan; Li, Jiaquan

2018-04-01

LK pyramid optical flow is an effective method to implement object tracking in a video. It is used for face landmark point tracking in a video in the paper. The landmark points, i.e. outer corner of left eye, inner corner of left eye, inner corner of right eye, outer corner of right eye, tip of a nose, left corner of mouth, right corner of mouth, are considered. It is in the first frame that the landmark points are marked by hand. For subsequent frames, performance of tracking is analyzed. Two kinds of conditions are considered, i.e. single factors such as normalized case, pose variation and slowly moving, expression variation, illumination variation, occlusion, front face and rapidly moving, pose face and rapidly moving, and combination of the factors such as pose and illumination variation, pose and expression variation, pose variation and occlusion, illumination and expression variation, expression variation and occlusion. Global measures and local ones are introduced to evaluate performance of tracking under different factors or combination of the factors. The global measures contain the number of images aligned successfully, average alignment error, the number of images aligned before failure, and the local ones contain the number of images aligned successfully for components of a face, average alignment error for the components. To testify performance of tracking for face landmark points under different cases, tests are carried out for image sequences gathered by us. Results show that the LK pyramid optical flow method can implement face landmark point tracking under normalized case, expression variation, illumination variation which does not affect facial details, pose variation, and that different factors or combination of the factors have different effect on performance of alignment for different landmark points.

Blood vessel segmentation in color fundus images based on regional and Hessian features.

PubMed

Shah, Syed Ayaz Ali; Tang, Tong Boon; Faye, Ibrahima; Laude, Augustinus

2017-08-01

To propose a new algorithm of blood vessel segmentation based on regional and Hessian features for image analysis in retinal abnormality diagnosis. Firstly, color fundus images from the publicly available database DRIVE were converted from RGB to grayscale. To enhance the contrast of the dark objects (blood vessels) against the background, the dot product of the grayscale image with itself was generated. To rectify the variation in contrast, we used a 5 × 5 window filter on each pixel. Based on 5 regional features, 1 intensity feature and 2 Hessian features per scale using 9 scales, we extracted a total of 24 features. A linear minimum squared error (LMSE) classifier was trained to classify each pixel into a vessel or non-vessel pixel. The DRIVE dataset provided 20 training and 20 test color fundus images. The proposed algorithm achieves a sensitivity of 72.05% with 94.79% accuracy. Our proposed algorithm achieved higher accuracy (0.9206) at the peripapillary region, where the ocular manifestations in the microvasculature due to glaucoma, central retinal vein occlusion, etc. are most obvious. This supports the proposed algorithm as a strong candidate for automated vessel segmentation.

Wide-field spectrally resolved quantitative fluorescence imaging system: toward neurosurgical guidance in glioma resection

NASA Astrophysics Data System (ADS)

Xie, Yijing; Thom, Maria; Ebner, Michael; Wykes, Victoria; Desjardins, Adrien; Miserocchi, Anna; Ourselin, Sebastien; McEvoy, Andrew W.; Vercauteren, Tom

2017-11-01

In high-grade glioma surgery, tumor resection is often guided by intraoperative fluorescence imaging. 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) provides fluorescent contrast between normal brain tissue and glioma tissue, thus achieving improved tumor delineation and prolonged patient survival compared with conventional white-light-guided resection. However, commercially available fluorescence imaging systems rely solely on visual assessment of fluorescence patterns by the surgeon, which makes the resection more subjective than necessary. We developed a wide-field spectrally resolved fluorescence imaging system utilizing a Generation II scientific CMOS camera and an improved computational model for the precise reconstruction of the PpIX concentration map. In our model, the tissue's optical properties and illumination geometry, which distort the fluorescent emission spectra, are considered. We demonstrate that the CMOS-based system can detect low PpIX concentration at short camera exposure times, while providing high-pixel resolution wide-field images. We show that total variation regularization improves the contrast-to-noise ratio of the reconstructed quantitative concentration map by approximately twofold. Quantitative comparison between the estimated PpIX concentration and tumor histopathology was also investigated to further evaluate the system.

Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol.

PubMed

Gao, Yang; Bian, Zhaoying; Huang, Jing; Zhang, Yunwan; Niu, Shanzhou; Feng, Qianjin; Chen, Wufan; Liang, Zhengrong; Ma, Jianhua

2014-06-16

To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as "ASR-TV-POCS." To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation.

The 13 years of TRMM Lightning Imaging Sensor: From Individual Flash Characteristics to Decadal Tendencies

NASA Technical Reports Server (NTRS)

Albrecht, R. I.; Goodman, S. J.; Petersen, W. A.; Buechler, D. E.; Bruning, E. C.; Blakeslee, R. J.; Christian, H. J.

2011-01-01

How often lightning strikes the Earth has been the object of interest and research for decades. Several authors estimated different global flash rates using ground-based instruments, but it has been the satellite era that enabled us to monitor lightning thunderstorm activity on the time and place that lightning exactly occurs. Launched into space as a component of NASA s Tropical Rainfall Measuring Mission (TRMM) satellite, in November 1997, the Lighting Imaging Sensor (LIS) is still operating. LIS detects total lightning (i.e., intracloud and cloud-to-ground) from space in a low-earth orbit (35deg orbit). LIS has collected lightning measurements for 13 years (1998-2010) and here we present a fully revised and current total lightning climatology over the tropics. Our analysis includes the individual flash characteristics (number of events and groups, total radiance, area footprint, etc.), composite climatological maps, and trends for the observed total lightning during these 13 years. We have identified differences in the energetics of the flashes and/or the optical scattering properties of the storms cells due to cell-relative variations in microphysics and kinematics (i.e., convective or stratiform rainfall). On the climatological total lightning maps we found a dependency on the scale of analysis (resolution) in identifying the lightning maximums in the tropics. The analysis of total lightning trends observed by LIS from 1998 to 2010 in different temporal (annual and seasonal) and spatial (large and regional) scales, showed no systematic trends in the median to lower-end of the distributions, but most places in the tropics presented a decrease in the highest total lightning flash rates (higher-end of the distributions).

Optimization image of magnetic resonance imaging (MRI) T2 fast spin echo (FSE) with variation echo train length (ETL) on the rupture tendon achilles case

NASA Astrophysics Data System (ADS)

Muzamil, Akhmad; Haries Firmansyah, Achmad

2017-05-01

The research was done the optimization image of Magnetic Resonance Imaging (MRI) T2 Fast Spin Echo (FSE) with variation Echo Train Length (ETL) on the Rupture Tendon Achilles case. This study aims to find the variations Echo Train Length (ETL) from the results of ankle’s MRI image and find out how the value of Echo Train Length (ETL) works on the MRI ankle to produce optimal image. In this research, the used ETL variations were 12 and 20 with the interval 2 on weighting T2 FSE sagittal. The study obtained the influence of Echo Train Length (ETL) on the quality of ankle MRI image sagittal using T2 FSE weighting and analyzed in 25 images of five patients. The data analysis has done quantitatively with the Region of Interest (ROI) directly on computer MRI image planes which conducted statistical tests Signal to Noise Ratio (SNR) and Contras to Noise Ratio (CNR). The Signal to Noise Ratio (SNR) was the highest finding on fat tissue, while the Contras to Noise Ratio (CNR) on the Tendon-Fat tissue with ETL 12 found in two patients. The statistics test showed the significant SNR value of the 0.007 (p<0.05) of Tendon tissue, 0.364 (p>0.05) of the Fat, 0.912 (p>0.05) of the Fibula, and 0.436 (p>0.05) of the Heel Bone. For the contrast to noise ratio (CNR) of the Tendon-FAT tissue was about 0.041 (p>0.05). The results of the study showed that ETL variation with T2 FSE sagittal weighting had difference at Tendon tissue and Tendon-Fat tissue for MRI imaging quality. SNR and CNR were an important aspect on imaging optimization process to give the diagnose information.

Performance evaluation of image denoising developed using convolutional denoising autoencoders in chest radiography

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Choi, Sunghoon; Kim, Hee-Joung

2018-03-01

When processing medical images, image denoising is an important pre-processing step. Various image denoising algorithms have been developed in the past few decades. Recently, image denoising using the deep learning method has shown excellent performance compared to conventional image denoising algorithms. In this study, we introduce an image denoising technique based on a convolutional denoising autoencoder (CDAE) and evaluate clinical applications by comparing existing image denoising algorithms. We train the proposed CDAE model using 3000 chest radiograms training data. To evaluate the performance of the developed CDAE model, we compare it with conventional denoising algorithms including median filter, total variation (TV) minimization, and non-local mean (NLM) algorithms. Furthermore, to verify the clinical effectiveness of the developed denoising model with CDAE, we investigate the performance of the developed denoising algorithm on chest radiograms acquired from real patients. The results demonstrate that the proposed denoising algorithm developed using CDAE achieves a superior noise-reduction effect in chest radiograms compared to TV minimization and NLM algorithms, which are state-of-the-art algorithms for image noise reduction. For example, the peak signal-to-noise ratio and structure similarity index measure of CDAE were at least 10% higher compared to conventional denoising algorithms. In conclusion, the image denoising algorithm developed using CDAE effectively eliminated noise without loss of information on anatomical structures in chest radiograms. It is expected that the proposed denoising algorithm developed using CDAE will be effective for medical images with microscopic anatomical structures, such as terminal bronchioles.

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Prevalence of eating disorder risk and body image distortion among National Collegiate Athletic Association Division I varsity equestrian athletes.

PubMed

Torres-McGehee, Toni M; Monsma, Eva V; Gay, Jennifer L; Minton, Dawn M; Mady-Foster, Ashley N

2011-01-01

Participation in appearance-based sports, particularly at the collegiate level, may place additional pressures on female athletes to be thin, which may increase the likelihood of their resorting to drastic weight control measures, such as disordered eating behaviors. (1) To estimate the prevalence and sources of eating disorder risk classification by academic status (freshman, sophomore, junior, or senior) and riding discipline (English and Western), (2) to examine riding style and academic status variations in body mass index (BMI) and silhouette type, and (3) to examine these variations across eating disorder risk classification type (eg, body image disturbances). Cross-sectional study. Seven universities throughout the United States. A total of 138 participants volunteered (mean age = 19.88 ± 1.29 years). They represented 2 equestrian disciplines English riding (n = 91) and Western riding (n = 47). Participants self-reported menstrual cycle history, height, and weight. We screened for eating disorder risk behaviors with the Eating Attitudes Test and for body disturbance with sex-specific BMI silhouettes. Based on the Eating Attitudes Test, estimated eating disorder prevalence was 42.0% in the total sample, 38.5% among English riders, and 48.9% among Western riders. No BMI or silhouette differences were found across academic status or discipline in disordered eating risk. Overall, participants perceived their body images as significantly larger than their actual physical sizes (self-reported BMI) and wanted to be significantly smaller in both normal clothing and competitive uniforms. Disordered eating risk prevalence among equestrian athletes was similar to that reported in other aesthetic sports and lower than that in nonaesthetic sports. Athletic trainers working with these athletes should be sensitive to these risks and refer athletes as needed to clinicians knowledgeable about disordered eating. Professionals working with this population should avoid making negative comments about physical size and appearance.

Magnetic resonance imaging of the calcaneus: preliminary assessment of trabecular bone-dependent regional variations in marrow relaxation time compared with dual X-ray absorptiometry

NASA Technical Reports Server (NTRS)

Guglielmi, G.; Selby, K.; Blunt, B. A.; Jergas, M.; Newitt, D. C.; Genant, H. K.; Majumdar, S.

1996-01-01

RATIONALE AND OBJECTIVES: Marrow transverse relaxation time (T2*) in magnetic resonance (MR) imaging may be related to the density and structure of the surrounding trabecular network. We investigated regional variations of T2* in the human calcaneus and compared the findings with bone mineral density (BMD), as measured by dual X-ray absorpiometry (DXA). Short- and long-term precisions were evaluated first to determine whether MR imaging would be useful for the clinical assessment of disease status and progression in osteoporosis. METHODS: Gradient-recalled echo MR images of the calcaneus were acquired at 1.5 T from six volunteers. Measurements of T2* were compared with BMD and (for one volunteer) conventional radiography. RESULTS: T2* values showed significant regional variation; they typically were shortest in the superior region of the calcaneus. There was a linear correlation between MR and DXA measurements (r = .66 for 1/T2* versus BMD). Differences in T2* attributable to variations in analysis region-of-interest placement were not significant for five of the six volunteers. Sagittal MR images had short- and long-term precision errors of 4.2% and 3.3%, respectively. For DXA, the precision was 1.3% (coefficient of variation). CONCLUSION: MR imaging may be useful for trabecular bone assessment in the calcaneus. However, given the large regional variations in bone density and structure, the choice of an ROI is likely to play a major role in the accuracy, precision, and overall clinical efficacy of T2* measurements.

Artifact reduction in short-scan CBCT by use of optimization-based reconstruction

PubMed Central

Zhang, Zheng; Han, Xiao; Pearson, Erik; Pelizzari, Charles; Sidky, Emil Y; Pan, Xiaochuan

2017-01-01

Increasing interest in optimization-based reconstruction in research on, and applications of, cone-beam computed tomography (CBCT) exists because it has been shown to have to potential to reduce artifacts observed in reconstructions obtained with the Feldkamp–Davis–Kress (FDK) algorithm (or its variants), which is used extensively for image reconstruction in current CBCT applications. In this work, we carried out a study on optimization-based reconstruction for possible reduction of artifacts in FDK reconstruction specifically from short-scan CBCT data. The investigation includes a set of optimization programs such as the image-total-variation (TV)-constrained data-divergency minimization, data-weighting matrices such as the Parker weighting matrix, and objects of practical interest for demonstrating and assessing the degree of artifact reduction. Results of investigative work reveal that appropriately designed optimization-based reconstruction, including the image-TV-constrained reconstruction, can reduce significant artifacts observed in FDK reconstruction in CBCT with a short-scan configuration. PMID:27046218

A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning.

PubMed

Zhang, Cheng; Zhang, Tao; Zheng, Jian; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

2015-01-01

In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time.

Chip-based wide field-of-view nanoscopy

NASA Astrophysics Data System (ADS)

Diekmann, Robin; Helle, Øystein I.; Øie, Cristina I.; McCourt, Peter; Huser, Thomas R.; Schüttpelz, Mark; Ahluwalia, Balpreet S.

2017-04-01

Present optical nanoscopy techniques use a complex microscope for imaging and a simple glass slide to hold the sample. Here, we demonstrate the inverse: the use of a complex, but mass-producible optical chip, which hosts the sample and provides a waveguide for the illumination source, and a standard low-cost microscope to acquire super-resolved images via two different approaches. Waveguides composed of a material with high refractive-index contrast provide a strong evanescent field that is used for single-molecule switching and fluorescence excitation, thus enabling chip-based single-molecule localization microscopy. Additionally, multimode interference patterns induce spatial fluorescence intensity variations that enable fluctuation-based super-resolution imaging. As chip-based nanoscopy separates the illumination and detection light paths, total-internal-reflection fluorescence excitation is possible over a large field of view, with up to 0.5 mm × 0.5 mm being demonstrated. Using multicolour chip-based nanoscopy, we visualize fenestrations in liver sinusoidal endothelial cells.

Estimation of urinary stone composition by automated processing of CT images.

PubMed

Chevreau, Grégoire; Troccaz, Jocelyne; Conort, Pierre; Renard-Penna, Raphaëlle; Mallet, Alain; Daudon, Michel; Mozer, Pierre

2009-10-01

The objective of this article was developing an automated tool for routine clinical practice to estimate urinary stone composition from CT images based on the density of all constituent voxels. A total of 118 stones for which the composition had been determined by infrared spectroscopy were placed in a helical CT scanner. A standard acquisition, low-dose and high-dose acquisitions were performed. All voxels constituting each stone were automatically selected. A dissimilarity index evaluating variations of density around each voxel was created in order to minimize partial volume effects: stone composition was established on the basis of voxel density of homogeneous zones. Stone composition was determined in 52% of cases. Sensitivities for each compound were: uric acid: 65%, struvite: 19%, cystine: 78%, carbapatite: 33.5%, calcium oxalate dihydrate: 57%, calcium oxalate monohydrate: 66.5%, brushite: 75%. Low-dose acquisition did not lower the performances (P < 0.05). This entirely automated approach eliminates manual intervention on the images by the radiologist while providing identical performances including for low-dose protocols.

Large-scale time-lapse microscopy of Oct4 expression in human embryonic stem cell colonies.

PubMed

Bhadriraju, Kiran; Halter, Michael; Amelot, Julien; Bajcsy, Peter; Chalfoun, Joe; Vandecreme, Antoine; Mallon, Barbara S; Park, Kye-Yoon; Sista, Subhash; Elliott, John T; Plant, Anne L

2016-07-01

Identification and quantification of the characteristics of stem cell preparations is critical for understanding stem cell biology and for the development and manufacturing of stem cell based therapies. We have developed image analysis and visualization software that allows effective use of time-lapse microscopy to provide spatial and dynamic information from large numbers of human embryonic stem cell colonies. To achieve statistically relevant sampling, we examined >680 colonies from 3 different preparations of cells over 5days each, generating a total experimental dataset of 0.9 terabyte (TB). The 0.5 Giga-pixel images at each time point were represented by multi-resolution pyramids and visualized using the Deep Zoom Javascript library extended to support viewing Giga-pixel images over time and extracting data on individual colonies. We present a methodology that enables quantification of variations in nominally-identical preparations and between colonies, correlation of colony characteristics with Oct4 expression, and identification of rare events. Copyright © 2016. Published by Elsevier B.V.

Onboard data-processing architecture of the soft X-ray imager (SXI) on NeXT satellite

NASA Astrophysics Data System (ADS)

Ozaki, Masanobu; Dotani, Tadayasu; Tsunemi, Hiroshi; Hayashida, Kiyoshi; Tsuru, Takeshi G.

2004-09-01

NeXT is the X-ray satellite proposed for the next Japanese space science mission. While the satellite total mass and the launching vehicle are similar to the prior satellite Astro-E2, the sensitivity is much improved; it requires all the components to be lighter and faster than previous architecture. This paper shows the data processing architecture of the X-ray CCD camera system SXI (Soft X-ray Imager), which is the top half of the WXI (Wide-band X-ray Imager) of the sensitivity in 0.2-80keV. The system is basically a variation of Astro-E2 XIS, but event extraction speed is much faster than it to fulfill the requirements coming from the large effective area and fast exposure period. At the same time, data transfer lines between components are redesigned in order to reduce the number and mass of the wire harnesses that limit the flexibility of the component distribution.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

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

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca

Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less

Optimising diffusion-weighted MR imaging for demonstrating pancreatic cancer: a comparison of respiratory-triggered, free-breathing and breath-hold techniques.

PubMed

Kartalis, Nikolaos; Loizou, Louiza; Edsborg, Nick; Segersvärd, Ralf; Albiin, Nils

2012-10-01

To compare respiratory-triggered, free-breathing, and breath-hold DWI techniques regarding (1) image quality, and (2) signal intensity (SI) and ADC measurements in pancreatic ductal adenocarcinoma (PDAC). Fifteen patients with histopathologically proven PDAC underwent DWI prospectively at 1.5 T (b = 0, 50, 300, 600 and 1,000 s/mm(2)) with the three techniques. Two radiologists, independently and blindly, assigned total image quality scores [sum of rating diffusion images (lesion detection, anatomy, presence of artefacts) and ADC maps (lesion characterisation, overall image quality)] per technique and ranked them. The lesion SI, signal-to-noise ratio, mean ADC and coefficient of variation (CV) were compared. Total image quality scores for respiratory-triggered, free-breathing and breath-hold techniques were 17.9, 16.5 and 17.1 respectively (respiratory-triggered was significantly higher than free-breathing but not breath-hold). The respiratory-triggered technique had a significantly higher ranking. Lesion SI on all b-values and signal-to-noise ratio on b300 and b600 were significantly higher for the respiratory-triggered technique. For respiratory-triggered, free-breathing and breath-hold techniques the mean ADCs were 1.201, 1.132 and 1.253 × 10(-3) mm(2)/s, and mean CVs were 8.9, 10.8 and 14.1 % respectively (respiratory-triggered and free-breathing techniques had a significantly lower mean CV than the breath-hold technique). In both analyses, respiratory-triggered DWI showed superiority and seems the optimal DWI technique for demonstrating PDAC. • Diffusion-weighted magnetic resonance imaging is increasingly used to detect pancreatic cancer • Images are acquired using various breathing techniques and multiple b-values • Breathing techniques used: respiratory-triggering, free-breathing and breath-hold • Respiratory-triggering seems the optimal breathing technique for demonstrating pancreatic cancer.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PubMed

Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2015-11-01

The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.

Linear measurements in 2-dimensional pelvic floor imaging: the impact of slice tilt angles on measurement reproducibility.

PubMed

Hoyte, L; Ratiu, P

2001-09-01

Magnetic resonance imaging techniques have improved the study of female pelvic dysfunction. However, disagreements between magnetic resonance measurements and their derived 3-dimensional reconstructions were noted. We tested the hypothesis that these discrepancies stemmed from variations in magnetic resonance acquisition angle. Images from the pelvis of the Visible Human Female (a thinly sliced cadaveric image data set) were obtained. Slices in the axial plane were rotated around pivot points in the pelvis to yield a set of similar-appearing para-axial images. A parameter that described the maximum anterior-posterior dimension of the levator hiatus was defined. This levator hiatus parameter was measured on all of the rotated images and compared with an expected value that was calculated from trigonometry. The levator hiatus was also measured on a group of similar-appearing slices rotated slightly around a defined point. In 1 group of slices, expected levator hiatus variation was 1.5 to 6.1%, whereas measured variation was 4% to 15%. Among the similar-appearing rotated slices, 4.8% to 16.0% variations were seen in the levator hiatus. Identical measurements made on radiologic images can vary widely. Slice acquisition must be standardized to avoid errors in data comparison.

Clinical decision-making tools for exam selection, reporting and dose tracking.

PubMed

Brink, James A

2014-10-01

Although many efforts have been made to reduce the radiation dose associated with individual medical imaging examinations to "as low as reasonably achievable," efforts to ensure such examinations are performed only when medically indicated and appropriate are equally if not more important. Variations in the use of ionizing radiation for medical imaging are concerning, regardless of whether they occur on a local, regional or national basis. Such variations among practices can be reduced with the use of decision support tools at the time of order entry. These tools help reduce radiation exposure among practices through the appropriate use of medical imaging. Similarly, adoption of best practices among imaging facilities can be promoted through tracking the radiation exposure among imaging patients. Practices can benchmark their aggregate radiation exposures for medical imaging through the use of dose index registries. However several variables must be considered when contemplating individual patient dose tracking. The specific dose measures and the variation among them introduced by variations in body habitus must be understood. Moreover the uncertainties in risk estimation from dose metrics related to age, gender and life expectancy must also be taken into account.

Segmentation of prostate from ultrasound images using level sets on active band and intensity variation across edges.

PubMed

Li, Xu; Li, Chunming; Fedorov, Andriy; Kapur, Tina; Yang, Xiaoping

2016-06-01

In this paper, the authors propose a novel efficient method to segment ultrasound images of the prostate with weak boundaries. Segmentation of the prostate from ultrasound images with weak boundaries widely exists in clinical applications. One of the most typical examples is the diagnosis and treatment of prostate cancer. Accurate segmentation of the prostate boundaries from ultrasound images plays an important role in many prostate-related applications such as the accurate placement of the biopsy needles, the assignment of the appropriate therapy in cancer treatment, and the measurement of the prostate volume. Ultrasound images of the prostate are usually corrupted with intensity inhomogeneities, weak boundaries, and unwanted edges, which make the segmentation of the prostate an inherently difficult task. Regarding to these difficulties, the authors introduce an active band term and an edge descriptor term in the modified level set energy functional. The active band term is to deal with intensity inhomogeneities and the edge descriptor term is to capture the weak boundaries or to rule out unwanted boundaries. The level set function of the proposed model is updated in a band region around the zero level set which the authors call it an active band. The active band restricts the authors' method to utilize the local image information in a banded region around the prostate contour. Compared to traditional level set methods, the average intensities inside∖outside the zero level set are only computed in this banded region. Thus, only pixels in the active band have influence on the evolution of the level set. For weak boundaries, they are hard to be distinguished by human eyes, but in local patches in the band region around prostate boundaries, they are easier to be detected. The authors incorporate an edge descriptor to calculate the total intensity variation in a local patch paralleled to the normal direction of the zero level set, which can detect weak boundaries and avoid unwanted edges in the ultrasound images. The efficiency of the proposed model is demonstrated by experiments on real 3D volume images and 2D ultrasound images and comparisons with other approaches. Validation results on real 3D TRUS prostate images show that the authors' model can obtain a Dice similarity coefficient (DSC) of 94.03% ± 1.50% and a sensitivity of 93.16% ± 2.30%. Experiments on 100 typical 2D ultrasound images show that the authors' method can obtain a sensitivity of 94.87% ± 1.85% and a DSC of 95.82% ± 2.23%. A reproducibility experiment is done to evaluate the robustness of the proposed model. As far as the authors know, prostate segmentation from ultrasound images with weak boundaries and unwanted edges is a difficult task. A novel method using level sets with active band and the intensity variation across edges is proposed in this paper. Extensive experimental results demonstrate that the proposed method is more efficient and accurate.

New Pn and Sn tomographic images of the uppermost mantle beneath the Mediterranean region

NASA Astrophysics Data System (ADS)

Gil, A.; Díaz, J.; Gallart, J.

2012-04-01

We present here new images of the seismic velocity and anisotropy variations in the uppermost mantle beneath the Mediterranean region, compiled from inversion of Pn and Sn phases. The method of Hearn (1996) has been applied to Pn and Sn lectures from the catalogs of the International Seismological Center and the Spanish Instituto Geografico Nacional. A total of 1,172,293 Pn arrivals coming from 16,527 earthquakes recorded at 1,657 stations with epicentral distances between 220 km and 1400 km have been retained (331,567 arrivals from 15,487events at 961 stations for Sn). Our results, grossly consistent with available 3D tomography images, show significant features well correlated with surface geology. The Pn velocities are high (>8.2 km/s) beneath major sedimentary basins (western Alboran Sea, Valencia Trough, Adriatic Sea, Aquitaine, Guadalquivir, Rharb, Aquitaine and Po basins), and low (<7.8 km/s) in orogenic areas (Betics, Pyrenees, Alps, Apennines, Dinarides, Helenides and Calabrian Arc), confirming the existence of marked variations in crustal thicknesses already documented in some active seismic experiments. The lowest velocity values are found under the Betics and the eastern and western Alps. Another low velocity anomaly is located below the south of Balearic Islands, probably related to a thermal anomaly associated to the westward displacement of the Alboran block along the Emile Baudot escarpment 16 Ma ago. The Pn anisotropic image shows consistent orientations sub-parallel to major orogenic structures, such as Betics, Apennines, Calabrian Arc and Alps. The station delays beneath Betic and Rif ranges are strongly negative, suggesting the presence of crustal thickening all along the Gibraltar Arc. However, only the Betics have a very strong low-velocity anomaly and a pronounced anisotropy pattern. The Sn tomographic image correlates well with the Pn image, even if some relevant differences can be observed beneath particular regions.

SPECT reconstruction with nonuniform attenuation from highly under-sampled projection data

NASA Astrophysics Data System (ADS)

Li, Cuifen; Wen, Junhai; Zhang, Kangping; Shi, Donghao; Dong, Haixiang; Li, Wenxiao; Liang, Zhengrong

2012-03-01

Single photon emission computed tomography (SPECT) is an important nuclear medicine imaging technique and has been using in clinical diagnoses. The SPECT image can reflect not only organizational structure but also functional activities of human body, therefore diseases can be found much earlier. In SPECT, the reconstruction is based on the measurement of gamma photons emitted by the radiotracer. The number of gamma photons detected is proportional to the dose of radiopharmaceutical, but the dose is limited because of patient safety. There is an upper limit in the number of gamma photons that can be detected per unit time, so it takes a long time to acquire SPECT projection data. Sometimes we just can obtain highly under-sampled projection data because of the limit of the scanning time or imaging hardware. How to reconstruct an image using highly under-sampled projection data is an interesting problem. One method is to minimize the total variation (TV) of the reconstructed image during the iterative reconstruction. In this work, we developed an OSEM-TV SPECT reconstruction algorithm, which could reconstruct the image from highly under-sampled projection data with non-uniform attenuation. Simulation results demonstrate that the OSEM-TV algorithm performs well in SPECT reconstruction with non-uniform attenuation.

Fast and low-dose computed laminography using compressive sensing based technique

NASA Astrophysics Data System (ADS)

Abbas, Sajid; Park, Miran; Cho, Seungryong

2015-03-01

Computed laminography (CL) is well known for inspecting microstructures in the materials, weldments and soldering defects in high density packed components or multilayer printed circuit boards. The overload problem on x-ray tube and gross failure of the radio-sensitive electronics devices during a scan are among important issues in CL which needs to be addressed. The sparse-view CL can be one of the viable option to overcome such issues. In this work a numerical aluminum welding phantom was simulated to collect sparsely sampled projection data at only 40 views using a conventional CL scanning scheme i.e. oblique scan. A compressive-sensing inspired total-variation (TV) minimization algorithm was utilized to reconstruct the images. It is found that the images reconstructed using sparse view data are visually comparable with the images reconstructed using full scan data set i.e. at 360 views on regular interval. We have quantitatively confirmed that tiny structures such as copper and tungsten slags, and copper flakes in the reconstructed images from sparsely sampled data are comparable with the corresponding structure present in the fully sampled data case. A blurring effect can be seen near the edges of few pores at the bottom of the reconstructed images from sparsely sampled data, despite the overall image quality is reasonable for fast and low-dose NDT.

Building block extraction and classification by means of aerial images fused with super-resolution reconstructed elevation data

NASA Astrophysics Data System (ADS)

Panagiotopoulou, Antigoni; Bratsolis, Emmanuel; Charou, Eleni; Perantonis, Stavros

2017-10-01

The detailed three-dimensional modeling of buildings utilizing elevation data, such as those provided by light detection and ranging (LiDAR) airborne scanners, is increasingly demanded today. There are certain application requirements and available datasets to which any research effort has to be adapted. Our dataset includes aerial orthophotos, with a spatial resolution 20 cm, and a digital surface model generated from LiDAR, with a spatial resolution 1 m and an elevation resolution 20 cm, from an area of Athens, Greece. The aerial images are fused with LiDAR, and we classify these data with a multilayer feedforward neural network for building block extraction. The innovation of our approach lies in the preprocessing step in which the original LiDAR data are super-resolution (SR) reconstructed by means of a stochastic regularized technique before their fusion with the aerial images takes place. The Lorentzian estimator combined with the bilateral total variation regularization performs the SR reconstruction. We evaluate the performance of our approach against that of fusing unprocessed LiDAR data with aerial images. We present the classified images and the statistical measures confusion matrix, kappa coefficient, and overall accuracy. The results demonstrate that our approach predominates over that of fusing unprocessed LiDAR data with aerial images.

Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

PubMed Central

Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

Explicit Filtering Based Low-Dose Differential Phase Reconstruction Algorithm with the Grating Interferometry.

PubMed

Jiang, Xiaolei; Zhang, Li; Zhang, Ran; Yin, Hongxia; Wang, Zhenchang

2015-01-01

X-ray grating interferometry offers a novel framework for the study of weakly absorbing samples. Three kinds of information, that is, the attenuation, differential phase contrast (DPC), and dark-field images, can be obtained after a single scanning, providing additional and complementary information to the conventional attenuation image. Phase shifts of X-rays are measured by the DPC method; hence, DPC-CT reconstructs refraction indexes rather than attenuation coefficients. In this work, we propose an explicit filtering based low-dose differential phase reconstruction algorithm, which enables reconstruction from reduced scanning without artifacts. The algorithm adopts a differential algebraic reconstruction technique (DART) with the explicit filtering based sparse regularization rather than the commonly used total variation (TV) method. Both the numerical simulation and the biological sample experiment demonstrate the feasibility of the proposed algorithm.

Explicit Filtering Based Low-Dose Differential Phase Reconstruction Algorithm with the Grating Interferometry

PubMed Central

Zhang, Li; Zhang, Ran; Yin, Hongxia; Wang, Zhenchang

2015-01-01

X-ray grating interferometry offers a novel framework for the study of weakly absorbing samples. Three kinds of information, that is, the attenuation, differential phase contrast (DPC), and dark-field images, can be obtained after a single scanning, providing additional and complementary information to the conventional attenuation image. Phase shifts of X-rays are measured by the DPC method; hence, DPC-CT reconstructs refraction indexes rather than attenuation coefficients. In this work, we propose an explicit filtering based low-dose differential phase reconstruction algorithm, which enables reconstruction from reduced scanning without artifacts. The algorithm adopts a differential algebraic reconstruction technique (DART) with the explicit filtering based sparse regularization rather than the commonly used total variation (TV) method. Both the numerical simulation and the biological sample experiment demonstrate the feasibility of the proposed algorithm. PMID:26089971

Medical services and associated costs vary widely among surgeons treating patients with hand osteoarthritis.

PubMed

Becker, Stéphanie J E; Teunis, Teun; Blauth, Johann; Kortlever, Joost T P; Dyer, George S M; Ring, David

2015-03-01

There are substantial variations in medical services that are difficult to explain based on differences in pathophysiology alone. The scale of variation and the number of people affected suggest substantial potential to lower healthcare costs with the reduction of practice variation. Our study assessed practice variation across three affiliated urban sites in one city in the United States and related healthcare costs following the diagnosis of hand osteoarthritis (OA) in patients. (1) What are the factors associated with increased costs and surgery in the first year after diagnosis of hand OA? (2) How much practice variation exists among hand surgeons in terms of the number of patient visits, use of imaging tests, use of injections, occupational therapy use, and surgery? (3) What proportion of total cost is accounted for by patients who consult with an additional provider? Patients receiving a new diagnosis of primary hand OA between January 1, 2007, and December 31, 2011, were identified from the research database of three affiliated urban hospitals in a single city in the United States. We included 2814 patients (69%, 1929 women) treated by six hand surgeons. We recorded all visits, imaging tests, injections, occupational therapy visits, and surgical procedures in the first year after that diagnosis. Costs were extracted from the Medicare Physician Fee Schedule. Reliability of the database was assessed by manual checking of 120 patient charts (4.3% of all data); reliability was determined to be 94% (113 of 120) for diagnoses, 97% (116 of 120) correct surgeon, 100% (120 of 120) second surgeon, 99% (278 of 282) visits, 99% (132 of 134) imaging procedures, 92% (11 of 12) injections, 95% (21 of 22) surgical procedures, and 85% (102 of 120) prescribing occupational therapy. Predictors of increased costs included younger patient age (regression coefficient [β] -3.5, semipartial R(2) 0.0049, 95% confidence interval [CI] -5.4 to -1.7, p < 0.001), seeing a second surgeon (β 283, semipartial R(2) 0.0095, 95% CI 176-391, p < 0.001), and specific surgeons (surgeon 1: β -243, semipartial R(2) 0.026, 95% CI -298 to -188, p < 0.001; surgeon 2: β -177, semipartial R(2) 0.0090, 95% CI -246 to -109, p < 0.001; surgeon 6: β 124, semipartial R(2) 0.0050, 95% CI 59-189, p < 0.001) (adjusted R(2) = 0.056). Similarly, factors associated with increased surgical intervention included younger patient age (β -0.0026, semipartial R(2) 0.0071, 95% CI -0.0037 to -0.0015, p < 0.001), male sex (β 0.041, semipartial R(2) 0.0028, 95% CI -0.069 to -0.012, p = 0.005), seeing a second surgeon (β 0.16, semipartial R(2) 0.0091, 95% CI 0.094-0.22, p < 0.001), and specific surgeons (surgeon 1: β -0.14, semipartial R(2) 0.026, 95% CI -0.18 to -0.11, p < 0.001; surgeon 2: β -0.13, semipartial R(2) 0.014, 95% CI -0.17 to -0.091, p < 0.001). There were large variations in the average number of visits (1.5-fold), imaging tests (threefold), use of injections (51-fold), occupational therapy (twofold), and surgery rates (sevenfold) among providers. One hundred twenty patients (4.3%) consulted a second surgeon within the first year after receiving the diagnosis of hand OA, which accounted for 8.1% (USD 68,826/USD 845,304) of the total costs. Patients who saw additional providers and who were of younger age incurred higher costs and a greater likelihood of undergoing surgery; the latter was also greater in male patients. Use of medical services and associated costs vary widely among providers treating patients with hand OA. Initiatives addressing practice variation-increased use of decision aids, for example-merit additional study. Level III, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.

A function space framework for structural total variation regularization with applications in inverse problems

NASA Astrophysics Data System (ADS)

Hintermüller, Michael; Holler, Martin; Papafitsoros, Kostas

2018-06-01

In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semi-continuous envelope (relaxation) of a suitable TV type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted TV for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddle-point problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson log-likelihood data discrepancy terms. Finally, we provide proof-of-concept numerical examples where we solve the saddle-point problem for weighted TV denoising as well as for MR guided PET image reconstruction.

Ophthalmic laser system integrated with speckle variance optical coherence tomography for real-time temperature monitoring

NASA Astrophysics Data System (ADS)

Lee, Soohyun; Lee, Changho; Cheon, Gyeongwoo; Kim, Jongmin; Jo, Dongki; Lee, Jihoon; Kang, Jin U.

2018-02-01

A commercial ophthalmic laser system (R;GEN, Lutronic Corp) was integrated with a swept-source optical coherence tomography (OCT) imaging system for real-time tissue temperature monitoring. M-scan OCT images were acquired during laser-pulse radiation, and speckle variance OCT (svOCT) images were analyzed to deduce temporal signal variations related to tissue temperature change from laser-pulse radiation. A phantom study shows that svOCT magnitude increases abruptly after laser pulse radiation and recovered exponentially, and the peak intensity of svOCT image was linearly dependent on pulse laser energy until it saturates. A study using bovine iris also showed signal variation dependence on the laser pulse radiation, and the variation was more distinctive with higher energy level.

Variations in the size of focal nodular hyperplasia on magnetic resonance imaging.

PubMed

Ramírez-Fuentes, C; Martí-Bonmatí, L; Torregrosa, A; Del Val, A; Martínez, C

2013-01-01

To evaluate the changes in the size of focal nodular hyperplasia (FNH) during long-term magnetic resonance imaging (MRI) follow-up. We reviewed 44 FNHs in 30 patients studied with MRI with at least two MRI studies at least 12 months apart. We measured the largest diameter of the lesion (inmm) in contrast-enhanced axial images and calculated the percentage of variation as the difference between the maximum diameter in the follow-up and the maximum diameter in the initial study. We defined significant variation in size as variation greater than 20%. We also analyzed predisposing hormonal factors. The mean interval between the two imaging studies was 35±2 months (range: 12-94). Most lesions (80%) remained stable during follow-up. Only 9 of the 44 lesions (20%) showed a significant variation in diameter: 7 (16%) decreased in size and 2 (4%) increased, with variations that reached the double of the initial size. The change in size was not related to pregnancy, menopause, or the use of birth control pills or corticoids. Changes in the size of FNHs during follow-up are relatively common and should not lead to a change in the diagnosis. These variations in size seem to be independent of hormonal factors that are considered to predispose. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

Assessment of the menstrual cycle upon total hemoglobin, water concentration, and oxygen saturation in the female breast

NASA Astrophysics Data System (ADS)

Jiang, Shudong; Pogue, Brian W.; Srinivasan, Subhadra; Soho, Sandra; Poplack, Steven P.; Tosteson, Tor D.; Paulsen, Keith D.

2003-07-01

Near-infrared imaging can be used in humans to characterize changes in breast tumor tissue by imaging total hemoglobin and water concentrations as well as oxygen saturation. In order to improve our understanding of these changes, we need to carefully quantify the range of variation possible in normal tissues for these parameters. In this study, the effect of the subject"s menstrual cycle was examined by imaging their breast at the follicular (7-14 days of the cycle) and secretory phases (21-28 days of the cycle), using our NIR tomographic system. In this system, a three layer patient interface is used to measure 3 planes along the breast from chest wall towards the nipple at 1cm increments. Seven volunteers in their 40s were observed for 2 menstrual cycles and all of these volunteers recently had normal mammograms (ACR 1) with heterogeneously dense breast composition. The results show that average total hemoglobin in the breast increased in many subjects between 0 to 15% from the follicular phase to secretory phase. Oxygen saturation and water concentration changes between these 2 parts of the cycle were between -6.5% to 12% for saturation and between -33% to 28% for water concentration. While the data averaged between subjects showed no significant change existed between phases, it was clear that individual subjects did exhibit changes in composition which were consistent from cycle to cycle. Understanding what leads to this heterogeneity between subjects will be an important factor in utilizing these measurements in clinical practice.

Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging.

PubMed

Han, Yiyong; Tzoumas, Stratis; Nunes, Antonio; Ntziachristos, Vasilis; Rosenthal, Amir

2015-09-01

With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. The optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV-L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. In all cases, model-based TV-L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV-L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV-L1 inversion yielded sharper images and weaker streak artifact. The results herein show that TV-L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV-L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging.

The role of body image in prenatal and postpartum depression: a critical review of the literature.

PubMed

Silveira, Marushka L; Ertel, Karen A; Dole, Nancy; Chasan-Taber, Lisa

2015-06-01

Maternal depression increases risk of adverse perinatal outcomes, and recent evidence suggests that body image may play an important role in depression. This systematic review identifies studies of body image and perinatal depression with the goal of elucidating the complex role that body image plays in prenatal and postpartum depression, improving measurement, and informing next steps in research. We conducted a literature search of the PubMed database (1996-2014) for English language studies of (1) depression, (2) body image, and (3) pregnancy or postpartum. In total, 19 studies matched these criteria. Cross-sectional studies consistently found a positive association between body image dissatisfaction and perinatal depression. Prospective cohort studies found that body image dissatisfaction predicted incident prenatal and postpartum depression; findings were consistent across different aspects of body image and various pregnancy and postpartum time periods. Prospective studies that examined the reverse association found that depression influenced the onset of some aspects of body image dissatisfaction during pregnancy, but few evaluated the postpartum onset of body image dissatisfaction. The majority of studies found that body image dissatisfaction is consistently but weakly associated with the onset of prenatal and postpartum depression. Findings were less consistent for the association between perinatal depression and subsequent body image dissatisfaction. While published studies provide a foundation for understanding these issues, methodologically rigorous studies that capture the perinatal variation in depression and body image via instruments validated in pregnant women, consistently adjust for important confounders, and include ethnically diverse populations will further elucidate this association.

Quantifying and visualizing variations in sets of images using continuous linear optimal transport

NASA Astrophysics Data System (ADS)

Kolouri, Soheil; Rohde, Gustavo K.

2014-03-01

Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.

Rapid variations of balmer line strengths in the spectra of Be stars. Ph.D. Thesis; [photoelectric spectrophotometric measurements

NASA Technical Reports Server (NTRS)

Mcbeath, K. B.

1974-01-01

Low resolution photoelectric spectrophotometric measurements of the first four members of the Balmer series in the spectra of one Be and five Be (shell) stars were obtained with the 92-cm telescope and image dissecting scanner. Equivalent widths were computed for each observation, and their standard deviations from the mean values were examined. Results indicate that in three of the program stars, at least one of the Balmer lines shows significant fluctuations in equivalent width. These fluctuations amount to a few per cent of total line strength and the time scales appear to be on the order of three to thirty minutes. The fluctuations are not always present in a given star, indicating that the mechanism producing them may not be continuous. The noncontinuous and nonperiodic nature of the variations, along with their short time scale suggest some form of flare-like or shock origin for the phenomenon.

Global Electric Circuit Diurnal Variation Derived from Storm Overflight and Satellite Optical Lightning Datasets

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Blakeslee, R. J.; Bateman, M. J.; Bailey, J. C.

2011-01-01

We have combined analyses of over 1000 high altitude aircraft observations of electrified clouds with diurnal lightning statistics from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to produce an estimate of the diurnal variation in the global electric circuit. Using basic assumptions about the mean storm currents as a function of flash rate and location, and the global electric circuit, our estimate of the current in the global electric circuit matches the Carnegie curve diurnal variation to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Mean contributions to the global electric circuit from land and ocean thunderstorms are 1.1 kA (land) and 0.7 kA (ocean). Contributions to the global electric circuit from ESCs are 0.22 kA for ocean storms and 0.04 kA for land storms. Using our analysis, the mean total conduction current for the global electric circuit is 2.0 kA.

Achieving optimum diffraction based overlay performance

NASA Astrophysics Data System (ADS)

Leray, Philippe; Laidler, David; Cheng, Shaunee; Coogans, Martyn; Fuchs, Andreas; Ponomarenko, Mariya; van der Schaar, Maurits; Vanoppen, Peter

2010-03-01

Diffraction Based Overlay (DBO) metrology has been shown to have significantly reduced Total Measurement Uncertainty (TMU) compared to Image Based Overlay (IBO), primarily due to having no measurable Tool Induced Shift (TIS). However, the advantages of having no measurable TIS can be outweighed by increased susceptibility to WIS (Wafer Induced Shift) caused by target damage, process non-uniformities and variations. The path to optimum DBO performance lies in having well characterized metrology targets, which are insensitive to process non-uniformities and variations, in combination with optimized recipes which take advantage of advanced DBO designs. In this work we examine the impact of different degrees of process non-uniformity and target damage on DBO measurement gratings and study their impact on overlay measurement accuracy and precision. Multiple wavelength and dual polarization scatterometry are used to characterize the DBO design performance over the range of process variation. In conclusion, we describe the robustness of DBO metrology to target damage and show how to exploit the measurement capability of a multiple wavelength, dual polarization scatterometry tool to ensure the required measurement accuracy for current and future technology nodes.

New method for estimating digestion of Paracoccidioides brasiliensis by phagocytic cells in vitro.

PubMed Central

Goihman-Yahr, M; Essenfeld-Yahr, E; Albornoz, M C; Yarzábal, L; de Gómez, M H; San Martín, B; Ocanto, A; Convit, J

1979-01-01

We describe a method by which phagocytosis and digestion of Paracoccidioides brasiliensis yeast cells by polymorphonuclear leukocytes or other phagocytic cells may be estimated. Suspensions of P. brasiliensis in its yeastlike phase were sonicated, counted, and incubated with known numbers of peripheral blood polymorphonuclear leukocytes. At given intervals, cytocentrifuge droplets were stained by a variation of Papanicolaou's method. Stained preparations were examined with phase-contrast optics. Digested organisms showed total or partial disappearance of protoplasm. Green-stained cell walls resisted digestion. The proportion of digested cells as a function of time was estimated. Images PMID:90683

The Aymara of Western Bolivia. IV. Gene frequencies for eight blood groups and 19 protein and erythrocyte enzyme systems.

PubMed Central

Ferrell, R E; Bertin, T; Young, R; Barton, S A; Murillo, F; Schull, W J

1978-01-01

A total of 315 individuals, mainly of Aymara origin, from western Bolivia were examined for genetic variation at eight red cell antigen and 19 serum protein and red cell enzyme loci. The gene frequencies for polymorphic loci and the discovery of several rare variants are discussed in terms of previous work among the Aymara and the closely related Quechua. The effect of inclusion of related individuals in the sample on gene frequency, variance of gene frequency and genetic distance, is discussed. Images Fig. 1 PMID:736042

Analysis of a New Variational Model to Restore Point-Like and Curve-Like Singularities in Imaging

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

Aubert, Gilles, E-mail: gaubert@unice.fr; Blanc-Feraud, Laure, E-mail: Laure.Blanc-Feraud@inria.fr; Graziani, Daniele, E-mail: Daniele.Graziani@inria.fr

2013-02-15

The paper is concerned with the analysis of a new variational model to restore point-like and curve-like singularities in biological images. To this aim we investigate the variational properties of a suitable energy which governs these pathologies. Finally in order to realize numerical experiments we minimize, in the discrete setting, a regularized version of this functional by fast descent gradient scheme.

Integrated Ground-based Hyperspectral Imaging and Geochemical Study of the Eagle Ford Group in West Texas

NASA Astrophysics Data System (ADS)

Sun, L.; Khan, S.; Godet, A.

2017-12-01

This study used ground-based hyperspectral imaging to map an outcrop of the Eagle Ford Group in west Texas. The Eagle Ford Group consists of alternating layers of mudstone - wackestone, grainstone - packstone facies and volcanic ash deposits with high total organic carbon content deposited during the Late Cenomanian - Turonian time period. It is one of the few unconventional source rock and reservoirs that have surface representations. Ground-based hyperspectral imaging scanned an outcrop and hand samples at close ranges with very fine spatial resolution (centimeter to sub-millimeter). Spectral absorption modeling of clay minerals and calcite with the modified Gaussian model (MGM) allowed quantification of variations of mineral abundances. Petrographic analysis confirmed mineral identifications and shed light on sedimentary textures. Major element geochemistry confirmed the mineral quantification. Enrichment of molybdenum (Mo) and uranium (U) indicated "unrestricted marine" paleo-hydrogeology and anoxic to euxinic paleo-redox bottom water conditions. Mineral quantification resulted in mapping of mudstone - wackestone, grainstone - packstone facies and claystones (volcanic ash beds). The lack of spatial associations between the grainstones and claystones on the outcrop calls into question the hypothesis that the primary productivity is controlled by iron availability from volcanic ash beds. Hyperspectral remote sensing data also helped in creating a virtual outcrop model with detailed mineralogical compositions, and provided reservoir analog to extract compositional and geo-mechanical characteristics and variations. The utilization of these new techniques in geo-statistical analysis provides a workflow for employing remote sensing in resource exploration and exploitation.

Integrated ground-based hyperspectral imaging and geochemical study of the Eagle Ford Group in West Texas

NASA Astrophysics Data System (ADS)

Sun, Lei; Khan, Shuhab; Godet, Alexis

2018-01-01

This study used ground-based hyperspectral imaging to map an outcrop of the Eagle Ford Group in west Texas. The Eagle Ford Group consists of alternating layers of mudstone - wackestone, grainstone - packstone facies and volcanic ash deposits with high total organic content deposited during the Cenomanian - Turonian time period. It is one of the few unconventional source rock and reservoirs that have surface representations. Ground-based hyperspectral imaging scanned an outcrop and hand samples at close ranges with very fine spatial resolution (centimeter to sub-millimeter). Spectral absorption modeling of clay minerals and calcite with the modified Gaussian model (MGM) allowed quantification of variations of mineral abundances. Petrographic analysis confirmed mineral identifications and shed light on sedimentary textures, and major element geochemistry supported the mineral quantification. Mineral quantification resulted in mapping of mudstone - wackestone, grainstone - packstone facies and bentonites (volcanic ash beds). The lack of spatial associations between the grainstones and bentonites on the outcrop calls into question the hypothesis that the primary productivity is controlled by iron availability from volcanic ash beds. Enrichment of molybdenum (Mo) and uranium (U) indicated "unrestricted marine" paleo-hydrogeology and anoxic to euxinic paleo-redox bottom water conditions. Hyperspectral remote sensing data also helped in creating a virtual outcrop model with detailed mineralogical compositions, and provided reservoir analog to extract compositional and geo-mechanical characteristics and variations. The utilization of these new techniques in geo-statistical analysis provides a workflow for employing remote sensing in resource exploration and exploitation.

3D Late Gadolinium Enhancement in a Single Prolonged Breath-hold using Supplemental Oxygenation and Hyperventilation

PubMed Central

Roujol, Sébastien; Basha, Tamer A.; Akçakaya, Mehmet; Foppa, Murilo; Chan, Raymond H.; Kissinger, Kraig V.; Goddu, Beth; Berg, Sophie; Manning, Warren J.; Nezafat, Reza

2013-01-01

Purpose: To evaluate the feasibility of 3D single breath-hold late gadolinium enhancement (LGE) of the left ventricle (LV) using supplemental oxygen and hyperventilation and compressed-sensing acceleration. Methods: Breath-hold metrics (breath-hold duration, diaphragmatic/LV position drift, and maximum variation of RR interval) without and with supplemental oxygen and hyperventilation were assessed in healthy adult subjects using a real time single shot acquisition. Ten healthy subjects and 13 patients then underwent assessment of the proposed 3D breath-hold LGE acquisition (FOV=320×320×100 mm3, resolution=1.6×1.6×5.0 mm3, acceleration rate of 4) and a free breathing acquisition with right hemidiaphragm navigator (NAV) respiratory gating. Semi-quantitative grading of overall image quality, motion artifact, myocardial nulling, and diagnostic value was performed by consensus of two blinded observers. Results: Supplemental oxygenation and hyperventilation increased the breath-hold duration (35±11 s to 58±21 s, p<0.0125) without significant impact on diaphragmatic/LV position drift or maximum variation of RR interval (both p>0.01). LGE images were of similar quality when compared to free breathing acquisitions but with reduced total scan time (85±22 s to 35±6 s, p<0.001). Conclusions: Supplemental oxygenation and hyperventilation allow for prolonged breath-holding and enable single breath-hold 3D accelerated LGE with similar image quality as free breathing with NAV. PMID:24186772

Comparison of centric and reverse-centric trajectories for highly accelerated three-dimensional saturation recovery cardiac perfusion imaging.

PubMed

Wang, Haonan; Bangerter, Neal K; Park, Daniel J; Adluru, Ganesh; Kholmovski, Eugene G; Xu, Jian; DiBella, Edward

2015-10-01

Highly undersampled three-dimensional (3D) saturation-recovery sequences are affected by k-space trajectory since the magnetization does not reach steady state during the acquisition and the slab excitation profile yields different flip angles in different slices. This study compares centric and reverse-centric 3D cardiac perfusion imaging. An undersampled (98 phase encodes) 3D ECG-gated saturation-recovery sequence that alternates centric and reverse-centric acquisitions each time frame was used to image phantoms and in vivo subjects. Flip angle variation across the slices was measured, and contrast with each trajectory was analyzed via Bloch simulation. Significant variations in flip angle were observed across slices, leading to larger signal variation across slices for the centric acquisition. In simulation, severe transient artifacts were observed when using the centric trajectory with higher flip angles, placing practical limits on the maximum flip angle used. The reverse-centric trajectory provided less contrast, but was more robust to flip angle variations. Both of the k-space trajectories can provide reasonable image quality. The centric trajectory can have higher CNR, but is more sensitive to flip angle variation. The reverse-centric trajectory is more robust to flip angle variation. © 2014 Wiley Periodicals, Inc.

Efficient generation of image chips for training deep learning algorithms

NASA Astrophysics Data System (ADS)

Han, Sanghui; Fafard, Alex; Kerekes, John; Gartley, Michael; Ientilucci, Emmett; Savakis, Andreas; Law, Charles; Parhan, Jason; Turek, Matt; Fieldhouse, Keith; Rovito, Todd

2017-05-01

Training deep convolutional networks for satellite or aerial image analysis often requires a large amount of training data. For a more robust algorithm, training data need to have variations not only in the background and target, but also radiometric variations in the image such as shadowing, illumination changes, atmospheric conditions, and imaging platforms with different collection geometry. Data augmentation is a commonly used approach to generating additional training data. However, this approach is often insufficient in accounting for real world changes in lighting, location or viewpoint outside of the collection geometry. Alternatively, image simulation can be an efficient way to augment training data that incorporates all these variations, such as changing backgrounds, that may be encountered in real data. The Digital Imaging and Remote Sensing Image Image Generation (DIRSIG) model is a tool that produces synthetic imagery using a suite of physics-based radiation propagation modules. DIRSIG can simulate images taken from different sensors with variation in collection geometry, spectral response, solar elevation and angle, atmospheric models, target, and background. Simulation of Urban Mobility (SUMO) is a multi-modal traffic simulation tool that explicitly models vehicles that move through a given road network. The output of the SUMO model was incorporated into DIRSIG to generate scenes with moving vehicles. The same approach was used when using helicopters as targets, but with slight modifications. Using the combination of DIRSIG and SUMO, we quickly generated many small images, with the target at the center with different backgrounds. The simulations generated images with vehicles and helicopters as targets, and corresponding images without targets. Using parallel computing, 120,000 training images were generated in about an hour. Some preliminary results show an improvement in the deep learning algorithm when real image training data are augmented with the simulated images, especially when obtaining sufficient real data was particularly challenging.

Denoising Medical Images using Calculus of Variations

PubMed Central

Kohan, Mahdi Nakhaie; Behnam, Hamid

2011-01-01

We propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. This method reduces any additive noise and preserves small patterns and edges of images. A pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. The experimental results show that the proposed method has visual improvement as well as a better SNR, RMSE and PSNR than common medical image denoising methods. Experimental results in denoising a sample Magnetic Resonance image show that SNR, PSNR and RMSE have been improved by 19, 9 and 21 percents respectively. PMID:22606674

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Spatial variations in a.c. susceptibility and microstructure for the YBa2Cu3O(7-x) superconductor and their correlation with room-temperature ultrasonic measurements

NASA Technical Reports Server (NTRS)

Roth, Don J.; Hepp, Aloysius F.; Deguire, Mark R.; Dolhert, Leonard E.

1991-01-01

The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu30(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.

Spatial variations in ac susceptibility and microstructure for the YBa2Cu3O(7-x) superconductor and their correlation with room-temperature ultrasonic measurements

NASA Technical Reports Server (NTRS)

Roth, Don J.; Deguire, Mark R.; Dolhert, Leonard E.; Hepp, Aloysius F.

1991-01-01

The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu3O(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

The Landsat Image Mosaic of Antarctica

USGS Publications Warehouse

Bindschadler, Robert; Vornberger, P.; Fleming, A.; Fox, A.; Mullins, J.; Binnie, D.; Paulsen, S.J.; Granneman, Brian J.; Gorodetzky, D.

2008-01-01

The Landsat Image Mosaic of Antarctica (LIMA) is the first true-color, high-spatial-resolution image of the seventh continent. It is constructed from nearly 1100 individually selected Landsat-7 ETM+ scenes. Each image was orthorectified and adjusted for geometric, sensor and illumination variations to a standardized, almost seamless surface reflectance product. Mosaicing to avoid clouds produced a high quality, nearly cloud-free benchmark data set of Antarctica for the International Polar Year from images collected primarily during 1999-2003. Multiple color composites and enhancements were generated to illustrate additional characteristics of the multispectral data including: the true appearance of the surface; discrimination between snow and bare ice; reflectance variations within bright snow; recovered reflectance values in regions of sensor saturation; and subtle topographic variations associated with ice flow. LIMA is viewable and individual scenes or user defined portions of the mosaic are downloadable at http://lima.usgs.gov. Educational materials associated with LIMA are available at http://lima.nasa.gov.

Some uses of wavelets for imaging dynamic processes in live cochlear structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

Variations in the anatomy of the celiac trunk: A systematic review and clinical implications.

PubMed

Panagouli, Eleni; Venieratos, Dionysios; Lolis, Evangelos; Skandalakis, Panagiotis

2013-12-01

The normal pattern of the celiac trunk (CT) implies its bifurcation to three branches, the common hepatic, the splenic and the left gastric artery. According to the available literature the CT presents several anatomical variations. The purpose of our study is to investigate the different types of these variations, the corresponding incidences and the probable influence of genetic factors, as they are presented in the existing literature. Four databases were searched for eligible articles for the period up to January 2013 and a total of 36 studies were collected. The CT was trifurcated into the three basic branches in the 89.42% (10,906/12,196) of the cases. Bifurcation of the CT occurred in the 7.40% of the pooled samples (903/12,196). Absence of the CT was the rarest variation with a percentage of 0.38% (46/12,196), hepatosplenomesenteric trunk was found in 49 out of the 12,196 cases (0.40%) and the celiacomesenteric trunk presented an incidence of 0.76% (93/12,196). Other variations of the CT were detected in the 1.64% of the pooled cases (199/12,196). The 14.9% of the cases in the cadaveric series (489/3278 specimens), the 10.5% in the imaging series (675/6501 specimens) and the 4.6% (104/2261) in the liver transplantation series presented variations. These differences are statistically significant (p<0.001). The Japanese and Korean populations presented more variations in the CT than Caucasians (p<0.05 and p<0.001). Negro, colored and black populations presented more variations of the CT than Indian ones (p>0.05). Using those data, a novel classification of CT variations is proposed. Copyright © 2013 Elsevier GmbH. All rights reserved.

Elimination of RF inhomogeneity effects in segmentation.

PubMed

Agus, Onur; Ozkan, Mehmed; Aydin, Kubilay

2007-01-01

There are various methods proposed for the segmentation and analysis of MR images. However the efficiency of these techniques is effected by various artifacts that occur in the imaging system. One of the most encountered problems is the intensity variation across an image. To overcome this problem different methods are used. In this paper we propose a method for the elimination of intensity artifacts in segmentation of MRI images. Inter imager variations are also minimized to produce the same tissue segmentation for the same patient. A well-known multivariate classification algorithm, maximum likelihood is employed to illustrate the enhancement in segmentation.

Effects of spatial variation of skull and cerebrospinal fluid layers on optical mapping of brain activities

NASA Astrophysics Data System (ADS)

Wang, Shuping; Shibahara, Nanae; Kuramashi, Daishi; Okawa, Shinpei; Kakuta, Naoto; Okada, Eiji; Maki, Atsushi; Yamada, Yukio

2010-07-01

In order to investigate the effects of anatomical variation in human heads on the optical mapping of brain activity, we perform simulations of optical mapping by solving the photon diffusion equation for layered-models simulating human heads using the finite element method (FEM). Particularly, the effects of the spatial variations in the thicknesses of the skull and cerebrospinal fluid (CSF) layers on mapping images are investigated. Mapping images of single active regions in the gray matter layer are affected by the spatial variations in the skull and CSF layer thicknesses, although the effects are smaller than those of the positions of the active region relative to the data points. The increase in the skull thickness decreases the sensitivity of the images to active regions, while the increase in the CSF layer thickness increases the sensitivity in general. The images of multiple active regions are also influenced by their positions relative to the data points and by their depths from the skin surface.

Improved JPEG anti-forensics with better image visual quality and forensic undetectability.

PubMed

Singh, Gurinder; Singh, Kulbir

2017-08-01

There is an immediate need to validate the authenticity of digital images due to the availability of powerful image processing tools that can easily manipulate the digital image information without leaving any traces. The digital image forensics most often employs the tampering detectors based on JPEG compression. Therefore, to evaluate the competency of the JPEG forensic detectors, an anti-forensic technique is required. In this paper, two improved JPEG anti-forensic techniques are proposed to remove the blocking artifacts left by the JPEG compression in both spatial and DCT domain. In the proposed framework, the grainy noise left by the perceptual histogram smoothing in DCT domain can be reduced significantly by applying the proposed de-noising operation. Two types of denoising algorithms are proposed, one is based on the constrained minimization problem of total variation of energy and other on the normalized weighted function. Subsequently, an improved TV based deblocking operation is proposed to eliminate the blocking artifacts in the spatial domain. Then, a decalibration operation is applied to bring the processed image statistics back to its standard position. The experimental results show that the proposed anti-forensic approaches outperform the existing state-of-the-art techniques in achieving enhanced tradeoff between image visual quality and forensic undetectability, but with high computational cost. Copyright © 2017 Elsevier B.V. All rights reserved.

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

Quantitative evaluation of phase processing approaches in susceptibility weighted imaging

NASA Astrophysics Data System (ADS)

Li, Ningzhi; Wang, Wen-Tung; Sati, Pascal; Pham, Dzung L.; Butman, John A.

2012-03-01

Susceptibility weighted imaging (SWI) takes advantage of the local variation in susceptibility between different tissues to enable highly detailed visualization of the cerebral venous system and sensitive detection of intracranial hemorrhages. Thus, it has been increasingly used in magnetic resonance imaging studies of traumatic brain injury as well as other intracranial pathologies. In SWI, magnitude information is combined with phase information to enhance the susceptibility induced image contrast. Because of global susceptibility variations across the image, the rate of phase accumulation varies widely across the image resulting in phase wrapping artifacts that interfere with the local assessment of phase variation. Homodyne filtering is a common approach to eliminate this global phase variation. However, filter size requires careful selection in order to preserve image contrast and avoid errors resulting from residual phase wraps. An alternative approach is to apply phase unwrapping prior to high pass filtering. A suitable phase unwrapping algorithm guarantees no residual phase wraps but additional computational steps are required. In this work, we quantitatively evaluate these two phase processing approaches on both simulated and real data using different filters and cutoff frequencies. Our analysis leads to an improved understanding of the relationship between phase wraps, susceptibility effects, and acquisition parameters. Although homodyne filtering approaches are faster and more straightforward, phase unwrapping approaches perform more accurately in a wider variety of acquisition scenarios.

Scaling up the Single Transducer Thickness-Independent Ultrasonic Imaging Method for Accurate Characterization of Microstructural Gradients in Monolithic and Composite Tubular Structures

NASA Technical Reports Server (NTRS)

Roth, Don J.; Carney, Dorothy V.; Baaklini, George Y.; Bodis, James R.; Rauser, Richard W.

1998-01-01

Ultrasonic velocity/time-of-flight imaging that uses back surface reflections to gauge volumetric material quality is highly suited for quantitative characterization of microstructural gradients including those due to pore fraction, density, fiber fraction, and chemical composition variations. However, a weakness of conventional pulse-echo ultrasonic velocity/time-of-flight imaging is that the image shows the effects of thickness as well as microstructural variations unless the part is uniformly thick. This limits this imaging method's usefulness in practical applications. Prior studies have described a pulse-echo time-of-flight-based ultrasonic imaging method that requires using a single transducer in combination with a reflector plate placed behind samples that eliminates the effect of thickness variation in the image. In those studies, this method was successful at isolating ultrasonic variations due to material microstructure in plate-like samples of silicon nitride, metal matrix composite, and polymer matrix composite. In this study, the method is engineered for inspection of more complex-shaped structures-those having (hollow) tubular/curved geometry. The experimental inspection technique and results are described as applied to (1) monolithic mullite ceramic and polymer matrix composite 'proof-of-concept' tubular structures that contain machined patches of various depths and (2) as-manufactured monolithic silicon nitride ceramic and silicon carbide/silicon carbide composite tubular structures that might be used in 'real world' applications.

Comparison between multi-shot gradient echo EPI and balanced SSFP in unenhanced 3T MRA of thoracic aorta in healthy volunteers.

PubMed

Iyama, Yuji; Nakaura, Takeshi; Nagayama, Yasunori; Oda, Seitaro; Utsunomiya, Daisuke; Kidoh, Masafumi; Yuki, Hideaki; Hirata, Kenichiro; Namimoto, Tomohiro; Kitajima, Mika; Morita, Kosuke; Funama, Yoshinori; Takemura, Atsushi; Tokuyasu, Shinichi; Okuaki, Tomoyuki; Yamashita, Yasuyuki

2017-11-01

The purpose of this study was to compare scan time and image quality between magnetic resonance angiography (MRA) of the thoracic aorta using a multi-shot gradient echo planar imaging (MSG-EPI) and MRA using balanced steady-state free precession (b-SSFP). Healthy volunteers (n=17) underwent unenhanced thoracic aorta MRA using balanced steady-state free precession (b-SSFP) and MSG-EPI sequences on a 3T MRI. The acquisition time, total scan time, signal-to-noise ratio (SNR) of the thoracic aorta, and the coefficient of variation (CV) of thoracic aorta were compared with paired t-tests. Two radiologists independently recorded the images' contrast, noise, sharpness, artifacts, and overall quality on a 4-point scale. The acquisition time was 36.2% shorter for MSG-EPI than b-SSFP (115.5±14.4 vs 181.0±14.9s, p<0.01). The total scan time was 40.4% shorter for MSG-EPI than b-SSFP (272±78 vs 456±144s, p<0.01). There was no significant difference in mean SNR between MSG-EPI and b-SSFP scans (17.3±3.6 vs 15.2±4.3, p=0.08). The CV was significantly lower for MSG-EPI than b-SSFP (0.2±0.1 vs. 0.5±0.2, p<0.01). All qualitative scores except for image noise were significantly higher in MSG-EPI than b-SSFP scans (p<0.05). The MSG-EPI sequence is a promising technique for shortening scan time and yielding more homogenous image quality in MRA of thoracic aorta on 3T scanners compared with the b-SSFP. Copyright © 2017 Elsevier B.V. All rights reserved.

Explicit area-based accuracy assessment for mangrove tree crown delineation using Geographic Object-Based Image Analysis (GEOBIA)

NASA Astrophysics Data System (ADS)

Kamal, Muhammad; Johansen, Kasper

2017-10-01

Effective mangrove management requires spatially explicit information of mangrove tree crown map as a basis for ecosystem diversity study and health assessment. Accuracy assessment is an integral part of any mapping activities to measure the effectiveness of the classification approach. In geographic object-based image analysis (GEOBIA) the assessment of the geometric accuracy (shape, symmetry and location) of the created image objects from image segmentation is required. In this study we used an explicit area-based accuracy assessment to measure the degree of similarity between the results of the classification and reference data from different aspects, including overall quality (OQ), user's accuracy (UA), producer's accuracy (PA) and overall accuracy (OA). We developed a rule set to delineate the mangrove tree crown using WorldView-2 pan-sharpened image. The reference map was obtained by visual delineation of the mangrove tree crowns boundaries form a very high-spatial resolution aerial photograph (7.5cm pixel size). Ten random points with a 10 m radius circular buffer were created to calculate the area-based accuracy assessment. The resulting circular polygons were used to clip both the classified image objects and reference map for area comparisons. In this case, the area-based accuracy assessment resulted 64% and 68% for the OQ and OA, respectively. The overall quality of the calculation results shows the class-related area accuracy; which is the area of correctly classified as tree crowns was 64% out of the total area of tree crowns. On the other hand, the overall accuracy of 68% was calculated as the percentage of all correctly classified classes (tree crowns and canopy gaps) in comparison to the total class area (an entire image). Overall, the area-based accuracy assessment was simple to implement and easy to interpret. It also shows explicitly the omission and commission error variations of object boundary delineation with colour coded polygons.

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

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

Lee, Soyoung

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanelmore » of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.« less

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy. © RSNA, 2013 PMID:24062559

Image denoising by a direct variational minimization

NASA Astrophysics Data System (ADS)

Janev, Marko; Atanacković, Teodor; Pilipović, Stevan; Obradović, Radovan

2011-12-01

In this article we introduce a novel method for the image de-noising which combines a mathematically well-posdenes of the variational modeling with the efficiency of a patch-based approach in the field of image processing. It based on a direct minimization of an energy functional containing a minimal surface regularizer that uses fractional gradient. The minimization is obtained on every predefined patch of the image, independently. By doing so, we avoid the use of an artificial time PDE model with its inherent problems of finding optimal stopping time, as well as the optimal time step. Moreover, we control the level of image smoothing on each patch (and thus on the whole image) by adapting the Lagrange multiplier using the information on the level of discontinuities on a particular patch, which we obtain by pre-processing. In order to reduce the average number of vectors in the approximation generator and still to obtain the minimal degradation, we combine a Ritz variational method for the actual minimization on a patch, and a complementary fractional variational principle. Thus, the proposed method becomes computationally feasible and applicable for practical purposes. We confirm our claims with experimental results, by comparing the proposed method with a couple of PDE-based methods, where we get significantly better denoising results specially on the oscillatory regions.

Adaptations of phytoplankton in the Indian Ocean sector of the Southern Ocean during austral summer of 1998—2014

NASA Astrophysics Data System (ADS)

Mishra, R. K.; Naik, R. K.; Anil Kumar, N.

2015-12-01

This study investigates the effects of light and temperature on the surface water diatoms and chlorophytes, phytoplankton in the Indian Ocean sector of the Southern Ocean (SO) during the austral summer of 1998‒2014. Significant longitudinal variations in hydrographic and biological parameters were observed at the Sub tropical front (STF), Sub Antarctic front (SAF) and Polar front (PF) along 56°E‒58°E. The concentrations of total surface chlorophyll a ( Chl a), diatoms, and chlorophytes measured by the National Aeronautics Space Agency (NASA) estimated by the Sea-Viewing Wide Field-of-View Sensors (SeaWiFS), the Moderate Resolution Imaging Spectro Radiometer (MODIS), and the NASA Ocean Biological Model (NOBM) were used in the study. Variations in the concentration of total Chl a was remarkable amongst the fronts during the study period. The contribution of diatoms to the total concentration of surface Chl a increased towards south from the STF to the PF while it decreased in the case of chlorophytes. The maximum photosynthetically active radiation (PAR) was observed at the STF and it progressively decreased to the PF through the SAF. At the PF region the contribution of diatoms to the total Chl a biomass was ≥80%. On the other hand, the chlorophytes showed a contrary distribution pattern with ≥70% of the total Chl a biomass recorded at the STF which gradually decreased towards the PF, mainly attributed to the temperate adaptation. This clearly reveals that the trend of diatoms increased at the STF and decreased at the SAF and the PF. Further, the trend of chlorophytes was increased at the STF, SAF and PF with a shift in the community in the frontal system of the Indian Ocean sector of the SO.

Investigation of skin structures based on infrared wave parameter indirect microscopic imaging

NASA Astrophysics Data System (ADS)

Zhao, Jun; Liu, Xuefeng; Xiong, Jichuan; Zhou, Lijuan

2017-02-01

Detailed imaging and analysis of skin structures are becoming increasingly important in modern healthcare and clinic diagnosis. Nanometer resolution imaging techniques such as SEM and AFM can cause harmful damage to the sample and cannot measure the whole skin structure from the very surface through epidermis, dermis to subcutaneous. Conventional optical microscopy has the highest imaging efficiency, flexibility in onsite applications and lowest cost in manufacturing and usage, but its image resolution is too low to be accepted for biomedical analysis. Infrared parameter indirect microscopic imaging (PIMI) uses an infrared laser as the light source due to its high transmission in skins. The polarization of optical wave through the skin sample was modulated while the variation of the optical field was observed at the imaging plane. The intensity variation curve of each pixel was fitted to extract the near field polarization parameters to form indirect images. During the through-skin light modulation and image retrieving process, the curve fitting removes the blurring scattering from neighboring pixels and keeps only the field variations related to local skin structures. By using the infrared PIMI, we can break the diffraction limit, bring the wide field optical image resolution to sub-200nm, in the meantime of taking advantage of high transmission of infrared waves in skin structures.

Analysis of water level variation of lakes and reservoirs in Xinjiang, China using ICESat laser altimetry data (2003–2009)

PubMed Central

Liu, Hongxing; Chen, Yaning; Shu, Song; Wu, Qiusheng; Wang, Shujie

2017-01-01

This study utilizes ICESat Release 33 GLA14 data to analyse water level variation of Xinjiang’s lakes and reservoirs from 2003 to 2009. By using Landsat images, lakes and reservoirs with area larger than 1 km2 are numerically delineated with a software tool. Based on ICESat observations, we analyse the characteristics of water level variation in different geographic environments, as well as investigate the reasons for the variation. Results indicate that climatic warming contributes to rising water levels in lakes in mountainous areas, especially for lakes that are recharged by snow and glacial melting. For lakes in oases, the water levels are affected jointly by human activity and climate change, while the water levels of reservoirs are mainly affected by human activity. Comparing the annual average rates of water levels, those of lakes are higher than those of reservoirs in oasis areas. The main reasons for the decreasing water levels in desert regions are the reduction of recharged runoff and high evaporation. By analysing the variation of water levels and water volume in different geologic environments, it is found that water level and volume increased in mountainous regions, and decreased in oasis regions and desert regions. Finding also demonstrate that decreasing volume is greater than increasing volume, which results in decreasing total volume of Xinjiang lakes and reservoirs. PMID:28873094

Total variation regularization for seismic waveform inversion using an adaptive primal dual hybrid gradient method

NASA Astrophysics Data System (ADS)

Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan

2018-04-01

Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.

Setup Variations in Radiotherapy of Anal Cancer: Advantages of Target Volume Reduction Using Image-Guided Radiation Treatment

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

Chen Yijen, E-mail: yichen@coh.org; Suh, Steve; Nelson, Rebecca A.

2012-09-01

Purpose: To define setup variations in the radiation treatment (RT) of anal cancer and to report the advantages of image-guided RT (IGRT) in terms of reduction of target volume and treatment-related side effects. Methods and Materials: Twelve consecutive patients with anal cancer treated by combined chemoradiation by use of helical tomotherapy from March 2007 to November 2008 were selected. With patients immobilized and positioned in place, megavoltage computed tomography (MVCT) scans were performed before each treatment and were automatically registered to planning CT scans. Patients were shifted per the registration data and treated. A total of 365 MVCT scans weremore » analyzed. The primary site received a median dose of 55 Gy. To evaluate the potential dosimetric advantage(s) of IGRT, cases were replanned according to Radiation Therapy Oncology Group 0529, with and without adding recommended setup variations from the current study. Results: Significant setup variations were observed throughout the course of RT. The standard deviations for systematic setup correction in the anterior-posterior (AP), lateral, and superior-inferior (SI) directions and roll rotation were 1.1, 3.6, and 3.2 mm, and 0.3 Degree-Sign , respectively. The average random setup variations were 3.8, 5.5, and 2.9 mm, and 0.5 Degree-Sign , respectively. Without daily IGRT, margins of 4.9, 11.1, and 8.5 mm in the AP, lateral, and SI directions would have been needed to ensure that the planning target volume (PTV) received {>=}95% of the prescribed dose. Conversely, daily IGRT required no extra margins on PTV and resulted in a significant reduction of V15 and V45 of intestine and V10 of pelvic bone marrow. Favorable toxicities were observed, except for acute hematologic toxicity. Conclusions: Daily MVCT scans before each treatment can effectively detect setup variations and thereby reduce PTV margins in the treatment of anal cancer. The use of concurrent chemotherapy and IGRT provided favorable toxicities, except for acute hematologic toxicity.« less

An infrared-visible image fusion scheme based on NSCT and compressed sensing

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Maldague, Xavier

2015-05-01

Image fusion, as a research hot point nowadays in the field of infrared computer vision, has been developed utilizing different varieties of methods. Traditional image fusion algorithms are inclined to bring problems, such as data storage shortage and computational complexity increase, etc. Compressed sensing (CS) uses sparse sampling without knowing the priori knowledge and greatly reconstructs the image, which reduces the cost and complexity of image processing. In this paper, an advanced compressed sensing image fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. NSCT provides better sparsity than the wavelet transform in image representation. Throughout the NSCT decomposition, the low-frequency and high-frequency coefficients can be obtained respectively. For the fusion processing of low-frequency coefficients of infrared and visible images , the adaptive regional energy weighting rule is utilized. Thus only the high-frequency coefficients are specially measured. Here we use sparse representation and random projection to obtain the required values of high-frequency coefficients, afterwards, the coefficients of each image block can be fused via the absolute maximum selection rule and/or the regional standard deviation rule. In the reconstruction of the compressive sampling results, a gradient-based iterative algorithm and the total variation (TV) method are employed to recover the high-frequency coefficients. Eventually, the fused image is recovered by inverse NSCT. Both the visual effects and the numerical computation results after experiments indicate that the presented approach achieves much higher quality of image fusion, accelerates the calculations, enhances various targets and extracts more useful information.

Thickness-Independent Ultrasonic Imaging Applied to Abrasive Cut-Off Wheels: An Advanced Aerospace Materials Characterization Method for the Abrasives Industry. A NASA Lewis Research Center Technology Transfer Case History

NASA Technical Reports Server (NTRS)

Roth, Don J.; Farmer, Donald A.

1998-01-01

Abrasive cut-off wheels are at times unintentionally manufactured with nonuniformity that is difficult to identify and sufficiently characterize without time-consuming, destructive examination. One particular nonuniformity is a density variation condition occurring around the wheel circumference or along the radius, or both. This density variation, depending on its severity, can cause wheel warpage and wheel vibration resulting in unacceptable performance and perhaps premature failure of the wheel. Conventional nondestructive evaluation methods such as ultrasonic c-scan imaging and film radiography are inaccurate in their attempts at characterizing the density variation because a superimposing thickness variation exists as well in the wheel. In this article, the single transducer thickness-independent ultrasonic imaging method, developed specifically to allow more accurate characterization of aerospace components, is shown to precisely characterize the extent of the density variation in a cut-off wheel having a superimposing thickness variation. The method thereby has potential as an effective quality control tool in the abrasives industry for the wheel manufacturer.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Variational mode decomposition based approach for accurate classification of color fundus images with hemorrhages

NASA Astrophysics Data System (ADS)

Lahmiri, Salim; Shmuel, Amir

2017-11-01

Diabetic retinopathy is a disease that can cause a loss of vision. An early and accurate diagnosis helps to improve treatment of the disease and prognosis. One of the earliest characteristics of diabetic retinopathy is the appearance of retinal hemorrhages. The purpose of this study is to design a fully automated system for the detection of hemorrhages in a retinal image. In the first stage of our proposed system, a retinal image is processed with variational mode decomposition (VMD) to obtain the first variational mode, which captures the high frequency components of the original image. In the second stage, four texture descriptors are extracted from the first variational mode. Finally, a classifier trained with all computed texture descriptors is used to distinguish between images of healthy and unhealthy retinas with hemorrhages. Experimental results showed evidence of the effectiveness of the proposed system for detection of hemorrhages in the retina, since a perfect detection rate was achieved. Our proposed system for detecting diabetic retinopathy is simple and easy to implement. It requires only short processing time, and it yields higher accuracy in comparison with previously proposed methods for detecting diabetic retinopathy.

Learnable despeckling framework for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Adabi, Saba; Rashedi, Elaheh; Clayton, Anne; Mohebbi-Kalkhoran, Hamed; Chen, Xue-wen; Conforto, Silvia; Nasiriavanaki, Mohammadreza

2018-01-01

Optical coherence tomography (OCT) is a prevalent, interferometric, high-resolution imaging method with broad biomedical applications. Nonetheless, OCT images suffer from an artifact called speckle, which degrades the image quality. Digital filters offer an opportunity for image improvement in clinical OCT devices, where hardware modification to enhance images is expensive. To reduce speckle, a wide variety of digital filters have been proposed; selecting the most appropriate filter for an OCT image/image set is a challenging decision, especially in dermatology applications of OCT where a different variety of tissues are imaged. To tackle this challenge, we propose an expandable learnable despeckling framework, we call LDF. LDF decides which speckle reduction algorithm is most effective on a given image by learning a figure of merit (FOM) as a single quantitative image assessment measure. LDF is learnable, which means when implemented on an OCT machine, each given image/image set is retrained and its performance is improved. Also, LDF is expandable, meaning that any despeckling algorithm can easily be added to it. The architecture of LDF includes two main parts: (i) an autoencoder neural network and (ii) filter classifier. The autoencoder learns the FOM based on several quality assessment measures obtained from the OCT image including signal-to-noise ratio, contrast-to-noise ratio, equivalent number of looks, edge preservation index, and mean structural similarity index. Subsequently, the filter classifier identifies the most efficient filter from the following categories: (a) sliding window filters including median, mean, and symmetric nearest neighborhood, (b) adaptive statistical-based filters including Wiener, homomorphic Lee, and Kuwahara, and (c) edge preserved patch or pixel correlation-based filters including nonlocal mean, total variation, and block matching three-dimensional filtering.

Primal-dual convex optimization in large deformation diffeomorphic metric mapping: LDDMM meets robust regularizers

NASA Astrophysics Data System (ADS)

Hernandez, Monica

2017-12-01

This paper proposes a method for primal-dual convex optimization in variational large deformation diffeomorphic metric mapping problems formulated with robust regularizers and robust image similarity metrics. The method is based on Chambolle and Pock primal-dual algorithm for solving general convex optimization problems. Diagonal preconditioning is used to ensure the convergence of the algorithm to the global minimum. We consider three robust regularizers liable to provide acceptable results in diffeomorphic registration: Huber, V-Huber and total generalized variation. The Huber norm is used in the image similarity term. The primal-dual equations are derived for the stationary and the non-stationary parameterizations of diffeomorphisms. The resulting algorithms have been implemented for running in the GPU using Cuda. For the most memory consuming methods, we have developed a multi-GPU implementation. The GPU implementations allowed us to perform an exhaustive evaluation study in NIREP and LPBA40 databases. The experiments showed that, for all the considered regularizers, the proposed method converges to diffeomorphic solutions while better preserving discontinuities at the boundaries of the objects compared to baseline diffeomorphic registration methods. In most cases, the evaluation showed a competitive performance for the robust regularizers, close to the performance of the baseline diffeomorphic registration methods.

Variations in the origins of the thyroid arteries on CT angiography.

PubMed

Esen, Kaan; Ozgur, Anil; Balci, Yuksel; Tok, Sermin; Kara, Engin

2018-02-01

To investigate the anatomical variations in the origins of the thyroid arteries on CT angiography images. The presence and the origins of the superior thyroid artery, the inferior thyroid artery, and the thyroidea ima artery were retrospectively evaluated based on carotid CT angiography examinations. The bifurcation level of the common carotid artery with respect to the cervical vertebrae and disc spaces was also determined. A total of 640 patients were included in the study. The right and left superior thyroid arteries arose from the external carotid artery in 413 (64.5%) and 254 (39.7%) patients, from the bifurcation of the common carotid artery in 131 (20.5%) and 148 (23.1%) patients, and from the common carotid artery in 90 (14.1%) and 226 (35.3%) patients, respectively. We could not observe the right and the left superior thyroid arteries in 6 (0.9%) and 12 (1.9%) of the patients, respectively. However, the right and left inferior thyroid arteries were not identified in 14 (2.2%) and 45 (7%) of the patients, respectively. The thyroidea ima artery was detected in 2.3% of the patients. The visualization of thyroid arteries on CT angiography images enables the anatomy of the arterial supply system of the thyroid gland to be explored in a noninvasive manner prior to surgery.

Inference of dust opacities for the 1977 Martian great dust storms from Viking Lander 1 pressure data

NASA Technical Reports Server (NTRS)

Zurek, R. W.

1981-01-01

The tidal heating components for the dusty Martian atmosphere are computed based on dust optical parameters estimated from Viking Lander imaging data, and used to compute the variation of the tidal surface pressure components at the Viking Lander sites as a function of season and the total vertical extinction optical depth of the atmosphere. An atmospheric tidal model is used which is based on the inviscid, hydrostatic primitive equations linearized about a motionless basic state the temperature of which varies only with height, and the profiles of the tidal forcing components are computed using a delta-Eddington approximation to the radiative transfer equations. Comparison of the model results with the observed variations of surface pressure and overhead dust opacity at the Viking Lander 1 site reveal that the dust opacities and optical parameters derived from imaging data are roughly representative of the global dust haze necessary to reproduce the observed surface pressure amplitudes, with the exception of the model-inferred asymmetry parameter, which is smaller during the onset of a great storm. The observed preferential enhancement of the semidiurnal tide with respect to the diurnal tide during dust storm onset is shown to be due primarily to the elevation of the tidal heating source in a very dusty atmosphere.

Study of morphological changes in scattering and optically anisotropic medium through correlation images

NASA Astrophysics Data System (ADS)

Jain, Neha; Shukla, Prashant; Singh, Jai

2018-05-01

Correlation images are very useful in determining the morphological changes. We have investigated the correlation image analysis on depolarization and retardance matrices of polystyrene and gelatine samples respectively. We observed that that correlation images have a potential to show a significant variation with change in the concentration of samples (polystyrene and gelatine). For polystyrene microspheres the correlation value decreases with increasing scattering coefficient. In gelatine samples the correlation also decreases with sample concentration. This variation in correlation for retardance shows the change in a birefringence property of gelatine solution.

Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets.

PubMed

Daboul, Amro; Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea

2018-01-01

Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'.

Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets

PubMed Central

Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea

2018-01-01

Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'. PMID:29787586

Diel mercury-concentration variations in streams affected by mining and geothermal discharge

USGS Publications Warehouse

Nimick, D.A.; McCleskey, R. Blaine; Gammons, C.H.; Cleasby, T.E.; Parker, S.R.

2007-01-01

Diel variations of concentrations of unfiltered and filtered total Hg and filtered methyl Hg were documented during 24-h sampling episodes in water from Silver Creek, which drains a historical gold-mining district near Helena, Montana, and the Madison River, which drains the geothermal system of Yellowstone National Park. The concentrations of filtered methyl Hg had relatively large diel variations (increases of 68 and 93% from morning minima) in both streams. Unfiltered and filtered (0.1-??m filtration) total Hg in Silver Creek had diel concentration increases of 24% and 7%, respectively. In the Madison River, concentrations of unfiltered and filtered total Hg did not change during the sampling period. The concentration variation of unfiltered total Hg in Silver Creek followed the diel variation in suspended-particle concentration. The concentration variation of filtered total and methyl Hg followed the solar photocycle, with highest concentrations during the early afternoon and evening and lowest concentrations during the morning. None of the diel Hg variations correlated with diel variation in streamflow or major ion concentrations. The diel variation in filtered total Hg could have been produced by adsorption-desorption of Hg2+ or by reduction of Hg(II) to Hg0 and subsequent evasion of Hg0. The diel variation in filtered methyl Hg could have been produced by sunlight- and temperature-dependent methylation. This study is the first to examine diel Hg cycling in streams, and its results reinforce previous conclusions that diel trace-element cycling in streams is widespread but often not recognized and that parts of the biogeochemical Hg cycle respond quickly to the daily photocycle. ?? 2006 Elsevier B.V. All rights reserved.

Variation of a Lightning NOx Indicator for National Climate Assessment

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Vant-Hull, B.; McCaul, E. W.; Peterson, H. S.

2014-01-01

In support of the National Climate Assessment (NCA) program, satellite Lightning Imaging Sensor (LIS) data is used to estimate lightning nitrogen oxides (LNOx) production over the southern portion of the conterminous US. The total energy of each flash is estimated by analyzing the LIS optical event data associated with each flash (i.e., event radiance, event footprint area, and derivable event range). The LIS detects an extremely small fraction of the total flash energy; this fraction is assumed to be constant apart from the variability associated with the flash optical energy detected across the narrow (0.909 nm) LIS band. The estimate of total energy from each flash is converted to moles of LNOx production by assuming a chemical yield of 10(17) molecules Joule(-1). The LIS-inferred variable LNOx production from each flash is summed to obtain total LNOx production, and then appropriately enhanced to account for LIS detection efficiency and LIS view time. Annual geographical plots and time series of LNOx production are provided for a 16 year period (1998-2013).

Measurement of EUV lithography pupil amplitude and phase variation via image-based methodology

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

Levinson, Zachary; Verduijn, Erik; Wood, Obert R.

2016-04-01

Here, an approach to image-based EUV aberration metrology using binary mask targets and iterative model-based solutions to extract both the amplitude and phase components of the aberrated pupil function is presented. The approach is enabled through previously developed modeling, fitting, and extraction algorithms. We seek to examine the behavior of pupil amplitude variation in real-optical systems. Optimized target images were captured under several conditions to fit the resulting pupil responses. Both the amplitude and phase components of the pupil function were extracted from a zone-plate-based EUV mask microscope. The pupil amplitude variation was expanded in three different bases: Zernike polynomials,more » Legendre polynomials, and Hermite polynomials. It was found that the Zernike polynomials describe pupil amplitude variation most effectively of the three.« less