Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

PubMed Central

Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean

2017-01-01

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging. PMID:28106118

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

NASA Astrophysics Data System (ADS)

Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean

2017-01-01

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging.

Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.

PubMed

George, Brandon; Aban, Inmaculada

2015-01-15

Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.

2015-01-01

Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462

Noise and analyzer-crystal angular position analysis for analyzer-based phase-contrast imaging

NASA Astrophysics Data System (ADS)

Majidi, Keivan; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-04-01

The analyzer-based phase-contrast x-ray imaging (ABI) method is emerging as a potential alternative to conventional radiography. Like many of the modern imaging techniques, ABI is a computed imaging method (meaning that images are calculated from raw data). ABI can simultaneously generate a number of planar parametric images containing information about absorption, refraction, and scattering properties of an object. These images are estimated from raw data acquired by measuring (sampling) the angular intensity profile of the x-ray beam passed through the object at different angular positions of the analyzer crystal. The noise in the estimated ABI parametric images depends upon imaging conditions like the source intensity (flux), measurements angular positions, object properties, and the estimation method. In this paper, we use the Cramér-Rao lower bound (CRLB) to quantify the noise properties in parametric images and to investigate the effect of source intensity, different analyzer-crystal angular positions and object properties on this bound, assuming a fixed radiation dose delivered to an object. The CRLB is the minimum bound for the variance of an unbiased estimator and defines the best noise performance that one can obtain regardless of which estimation method is used to estimate ABI parametric images. The main result of this paper is that the variance (hence the noise) in parametric images is directly proportional to the source intensity and only a limited number of analyzer-crystal angular measurements (eleven for uniform and three for optimal non-uniform) are required to get the best parametric images. The following angular measurements only spread the total dose to the measurements without improving or worsening CRLB, but the added measurements may improve parametric images by reducing estimation bias. Next, using CRLB we evaluate the multiple-image radiography, diffraction enhanced imaging and scatter diffraction enhanced imaging estimation techniques, though the proposed methodology can be used to evaluate any other ABI parametric image estimation technique.

Noise and Analyzer-Crystal Angular Position Analysis for Analyzer-Based Phase-Contrast Imaging

PubMed Central

Majidi, Keivan; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-01-01

The analyzer-based phase-contrast X-ray imaging (ABI) method is emerging as a potential alternative to conventional radiography. Like many of the modern imaging techniques, ABI is a computed imaging method (meaning that images are calculated from raw data). ABI can simultaneously generate a number of planar parametric images containing information about absorption, refraction, and scattering properties of an object. These images are estimated from raw data acquired by measuring (sampling) the angular intensity profile (AIP) of the X-ray beam passed through the object at different angular positions of the analyzer crystal. The noise in the estimated ABI parametric images depends upon imaging conditions like the source intensity (flux), measurements angular positions, object properties, and the estimation method. In this paper, we use the Cramér-Rao lower bound (CRLB) to quantify the noise properties in parametric images and to investigate the effect of source intensity, different analyzer-crystal angular positions and object properties on this bound, assuming a fixed radiation dose delivered to an object. The CRLB is the minimum bound for the variance of an unbiased estimator and defines the best noise performance that one can obtain regardless of which estimation method is used to estimate ABI parametric images. The main result of this manuscript is that the variance (hence the noise) in parametric images is directly proportional to the source intensity and only a limited number of analyzer-crystal angular measurements (eleven for uniform and three for optimal non-uniform) are required to get the best parametric images. The following angular measurements only spread the total dose to the measurements without improving or worsening CRLB, but the added measurements may improve parametric images by reducing estimation bias. Next, using CRLB we evaluate the Multiple-Image Radiography (MIR), Diffraction Enhanced Imaging (DEI) and Scatter Diffraction Enhanced Imaging (S-DEI) estimation techniques, though the proposed methodology can be used to evaluate any other ABI parametric image estimation technique. PMID:24651402

Direct Estimation of Kinetic Parametric Images for Dynamic PET

PubMed Central

Wang, Guobao; Qi, Jinyi

2013-01-01

Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed. PMID:24396500

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

PubMed

Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-06-01

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography

PubMed Central

Packham, B; Barnes, G; dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-01-01

Abstract Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity. PMID:27203477

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0597 TITLE: Parametric PET /MR Fusion Imaging to...Parametric PET /MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies...The study investigates whether fusion PET /MRI imaging with 18F-choline PET /CT and diffusion-weighted MRI can be successfully applied to target prostate

Least-squares reverse time migration in elastic media

NASA Astrophysics Data System (ADS)

Ren, Zhiming; Liu, Yang; Sen, Mrinal K.

2017-02-01

Elastic reverse time migration (RTM) can yield accurate subsurface information (e.g. PP and PS reflectivity) by imaging the multicomponent seismic data. However, the existing RTM methods are still insufficient to provide satisfactory results because of the finite recording aperture, limited bandwidth and imperfect illumination. Besides, the P- and S-wave separation and the polarity reversal correction are indispensable in conventional elastic RTM. Here, we propose an iterative elastic least-squares RTM (LSRTM) method, in which the imaging accuracy is improved gradually with iteration. We first use the Born approximation to formulate the elastic de-migration operator, and employ the Lagrange multiplier method to derive the adjoint equations and gradients with respect to reflectivity. Then, an efficient inversion workflow (only four forward computations needed in each iteration) is introduced to update the reflectivity. Synthetic and field data examples reveal that the proposed LSRTM method can obtain higher-quality images than the conventional elastic RTM. We also analyse the influence of model parametrizations and misfit functions in elastic LSRTM. We observe that Lamé parameters, velocity and impedance parametrizations have similar and plausible migration results when the structures of different models are correlated. For an uncorrelated subsurface model, velocity and impedance parametrizations produce fewer artefacts caused by parameter crosstalk than the Lamé coefficient parametrization. Correlation- and convolution-type misfit functions are effective when amplitude errors are involved and the source wavelet is unknown, respectively. Finally, we discuss the dependence of elastic LSRTM on migration velocities and its antinoise ability. Imaging results determine that the new elastic LSRTM method performs well as long as the low-frequency components of migration velocities are correct. The quality of images of elastic LSRTM degrades with increasing noise.

Multiscale reconstruction for MR fingerprinting.

PubMed

Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

2016-06-01

To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode

NASA Astrophysics Data System (ADS)

Zhang, Ji; Li, Tao; Zheng, Shiqiang; Li, Yiyong

2015-03-01

To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48+/-42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

PubMed

Kramer, Gerbrand Maria; Frings, Virginie; Heijtel, Dennis; Smit, E F; Hoekstra, Otto S; Boellaard, Ronald

2017-06-01

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'- 18 F-fluorothymidine ( 18 F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18 F-FLT PET/CT to assess the robustness of these methods. Methods : Ten NSCLC patients underwent dynamic 18 F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V T ) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy ( R 2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K 1 values ( R 2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K 1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18 F-FLT V T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K 1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18 F-FLT PET/CT studies; however, SA can also be used. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Multi-parametric studies of electrically-driven flyer plates

NASA Astrophysics Data System (ADS)

Neal, William; Bowden, Michael; Explosive Trains; Devices Collaboration

2015-06-01

Exploding foil initiator (EFI) detonators function by the acceleration of a flyer plate, by the electrical explosion of a metallic bridge, into an explosive pellet. The length, and therefore time, scales of this shock initation process is dominated by the magnitude and duration of the imparted shock pulse. To predict the dynamics of this initiation, it is critical to further understand the velocity, shape and thickness of this flyer plate. This study uses multi-parametric diagnostics to investigate the geometry and velocity of the flyer plate upon impact including the imparted electrical energy: photon Doppler velocimetry (PDV), dual axis imaging, time-resolved impact imaging, voltage and current. The investigation challenges the validity of traditional assumptions about the state of the flyer plate at impact and discusses the improved understanding of the process.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Ghost imaging via optical parametric amplification

NASA Astrophysics Data System (ADS)

Li, Hong-Guo; Zhang, De-Jian; Xu, De-Qin; Zhao, Qiu-Li; Wang, Sen; Wang, Hai-Bo; Xiong, Jun; Wang, Kaige

2015-10-01

We investigate theoretically and experimentally thermal light ghost imaging where the light transmitted through the object as the seed light is amplified by an optical parametric amplifier (OPA). In conventional lens imaging systems with OPA, the spectral bandwidth of OPA dominates the image resolution. Theoretically, we prove that in ghost imaging via optical parametric amplification (GIOPA) the bandwidth of OPA will not affect the image resolution. The experimental results show that for weak seed light the image quality in GIOPA is better than that of conventional ghost imaging. Our work may be valuable in remote sensing with ghost imaging technique, where the light passed through the object is weak after a long-distance propagation.

Evaluation of sorafenib for advanced hepatocellular carcinoma with low α-fetoprotein in arrival time parametric imaging using contrast-enhanced ultrasonography.

PubMed

Shiozawa, Kazue; Watanabe, Manabu; Ikehara, Takashi; Shimizu, Ryo; Shinohara, Mie; Igarashi, Yoshinori; Sumino, Yasukiyo

2017-01-01

To determine the usefulness of arrival time parametric imaging (AtPI) using contrast-enhanced ultrasonography (CEUS) with Sonazoid in evaluating early response to sorafenib for hepatocellular carcinoma (HCC). Twenty-one advanced HCC patients with low α-fetoprotein (AFP) levels (≤35 ng/ml) who received sorafenib for at least 4 weeks were enrolled in this study. CEUS was performed before and 2 weeks after treatment, and the images of the target lesion in the arterial phase were analyzed by AtPI. In the color mapping images obtained by AtPI, the mean arrival time of the contrast agent in the target lesion from the reference point (mean time: MT) was calculated. In each patient, differences between MT before and MT 2 weeks after treatment were compared. MT (+) and MT (-) groups were defined as difference of 0 s or greater and less than 0 s, respectively. Overall survival was evaluated between the two groups. In the MT (+) (11 patients) and MT (-) (10 patients) groups, the median survival time was 792 and 403 days, respectively, which was statistically significant. The results suggested that AtPI was useful for evaluating early response to sorafenib for advanced HCC with low AFP level.

Documenting the location of systematic transrectal ultrasound-guided prostate biopsies: correlation with multi-parametric MRI.

PubMed

Turkbey, Baris; Xu, Sheng; Kruecker, Jochen; Locklin, Julia; Pang, Yuxi; Shah, Vijay; Bernardo, Marcelino; Baccala, Angelo; Rastinehad, Ardeshir; Benjamin, Compton; Merino, Maria J; Wood, Bradford J; Choyke, Peter L; Pinto, Peter A

2011-03-29

During transrectal ultrasound (TRUS)-guided prostate biopsies, the actual location of the biopsy site is rarely documented. Here, we demonstrate the capability of TRUS-magnetic resonance imaging (MRI) image fusion to document the biopsy site and correlate biopsy results with multi-parametric MRI findings. Fifty consecutive patients (median age 61 years) with a median prostate-specific antigen (PSA) level of 5.8 ng/ml underwent 12-core TRUS-guided biopsy of the prostate. Pre-procedural T2-weighted magnetic resonance images were fused to TRUS. A disposable needle guide with miniature tracking sensors was attached to the TRUS probe to enable fusion with MRI. Real-time TRUS images during biopsy and the corresponding tracking information were recorded. Each biopsy site was superimposed onto the MRI. Each biopsy site was classified as positive or negative for cancer based on the results of each MRI sequence. Sensitivity, specificity, and receiver operating curve (ROC) area under the curve (AUC) values were calculated for multi-parametric MRI. Gleason scores for each multi-parametric MRI pattern were also evaluated. Six hundred and 5 systemic biopsy cores were analyzed in 50 patients, of whom 20 patients had 56 positive cores. MRI identified 34 of 56 positive cores. Overall, sensitivity, specificity, and ROC area values for multi-parametric MRI were 0.607, 0.727, 0.667, respectively. TRUS-MRI fusion after biopsy can be used to document the location of each biopsy site, which can then be correlated with MRI findings. Based on correlation with tracked biopsies, T2-weighted MRI and apparent diffusion coefficient maps derived from diffusion-weighted MRI are the most sensitive sequences, whereas the addition of delayed contrast enhancement MRI and three-dimensional magnetic resonance spectroscopy demonstrated higher specificity consistent with results obtained using radical prostatectomy specimens.

Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

NASA Astrophysics Data System (ADS)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

Coherent white light amplification

DOEpatents

Jovanovic, Igor; Barty, Christopher P.

2004-05-25

A system for coherent simultaneous amplification of a broad spectral range of light that includes an optical parametric amplifier and a source of a seed pulse is described. A first angular dispersive element is operatively connected to the source of a seed pulse. A first imaging telescope is operatively connected to the first angular dispersive element and operatively connected to the optical parametric amplifier. A source of a pump pulse is operatively connected to the optical parametric amplifier. A second imaging telescope is operatively connected to the optical parametric amplifier and a second angular dispersive element is operatively connected to the second imaging telescope.

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy.

PubMed

Tang, Jing; Kuwabara, Hiroto; Wong, Dean F; Rahmim, Arman

2010-08-07

We developed an anatomy-guided 4D closed-form algorithm to directly reconstruct parametric images from projection data for (nearly) irreversible tracers. Conventional methods consist of individually reconstructing 2D/3D PET data, followed by graphical analysis on the sequence of reconstructed image frames. The proposed direct reconstruction approach maintains the simplicity and accuracy of the expectation-maximization (EM) algorithm by extending the system matrix to include the relation between the parametric images and the measured data. A closed-form solution was achieved using a different hidden complete-data formulation within the EM framework. Furthermore, the proposed method was extended to maximum a posterior reconstruction via incorporation of MR image information, taking the joint entropy between MR and parametric PET features as the prior. Using realistic simulated noisy [(11)C]-naltrindole PET and MR brain images/data, the quantitative performance of the proposed methods was investigated. Significant improvements in terms of noise versus bias performance were demonstrated when performing direct parametric reconstruction, and additionally upon extending the algorithm to its Bayesian counterpart using the MR-PET joint entropy measure.

Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography

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

Zhang, Guanglei, E-mail: guangleizhang@bjtu.edu.cn; Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044; Pu, Huangsheng

2015-02-23

Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but alsomore » make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.« less

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

Parametric boundary reconstruction algorithm for industrial CT metrology application.

PubMed

Yin, Zhye; Khare, Kedar; De Man, Bruno

2009-01-01

High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.

Outcome of temporal lobe epilepsy surgery predicted by statistical parametric PET imaging.

PubMed

Wong, C Y; Geller, E B; Chen, E Q; MacIntyre, W J; Morris, H H; Raja, S; Saha, G B; Lüders, H O; Cook, S A; Go, R T

1996-07-01

PET is useful in the presurgical evaluation of temporal lobe epilepsy. The purpose of this retrospective study is to assess the clinical use of statistical parametric imaging in predicting surgical outcome. Interictal 18FDG-PET scans in 17 patients with surgically-treated temporal lobe epilepsy (Group A-13 seizure-free, group B = 4 not seizure-free at 6 mo) were transformed into statistical parametric imaging, with each pixel representing a z-score value by using the mean and s.d. of count distribution in each individual patient, for both visual and quantitative analysis. Mean z-scores were significantly more negative in anterolateral (AL) and mesial (M) regions on the operated side than the nonoperated side in group A (AL: p < 0.00005, M: p = 0.0097), but not in group B (AL: p = 0.46, M: p = 0.08). Statistical parametric imaging correctly lateralized 16 out of 17 patients. Only the AL region, however, was significant in predicting surgical outcome (F = 29.03, p < 0.00005). Using a cut-off z-score value of -1.5, statistical parametric imaging correctly classified 92% of temporal lobes from group A and 88% of those from Group B. The preliminary results indicate that statistical parametric imaging provides both clinically useful information for lateralization in temporal lobe epilepsy and a reliable predictive indicator of clinical outcome following surgical treatment.

Entangled-photon compressive ghost imaging

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

Zerom, Petros; Chan, Kam Wai Clifford; Howell, John C.

2011-12-15

We have experimentally demonstrated high-resolution compressive ghost imaging at the single-photon level using entangled photons produced by a spontaneous parametric down-conversion source and using single-pixel detectors. For a given mean-squared error, the number of photons needed to reconstruct a two-dimensional image is found to be much smaller than that in quantum ghost imaging experiments employing a raster scan. This procedure not only shortens the data acquisition time, but also suggests a more economical use of photons for low-light-level and quantum image formation.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Observation of Geometric Parametric Instability Induced by the Periodic Spatial Self-Imaging of Multimode Waves

NASA Astrophysics Data System (ADS)

Krupa, Katarzyna; Tonello, Alessandro; Barthélémy, Alain; Couderc, Vincent; Shalaby, Badr Mohamed; Bendahmane, Abdelkrim; Millot, Guy; Wabnitz, Stefan

2016-05-01

Spatiotemporal mode coupling in highly multimode physical systems permits new routes for exploring complex instabilities and forming coherent wave structures. We present here the first experimental demonstration of multiple geometric parametric instability sidebands, generated in the frequency domain through resonant space-time coupling, owing to the natural periodic spatial self-imaging of a multimode quasi-continuous-wave beam in a standard graded-index multimode fiber. The input beam was launched in the fiber by means of an amplified microchip laser emitting sub-ns pulses at 1064 nm. The experimentally observed frequency spacing among sidebands agrees well with analytical predictions and numerical simulations. The first-order peaks are located at the considerably large detuning of 123.5 THz from the pump. These results open the remarkable possibility to convert a near-infrared laser directly into a broad spectral range spanning visible and infrared wavelengths, by means of a single resonant parametric nonlinear effect occurring in the normal dispersion regime. As further evidence of our strong space-time coupling regime, we observed the striking effect that all of the different sideband peaks were carried by a well-defined and stable bell-shaped spatial profile.

Time-dependent spatial intensity profiles of near-infrared idler pulses from nanosecond optical parametric oscillators

NASA Astrophysics Data System (ADS)

Olafsen, L. J.; Olafsen, J. S.; Eaves, I. K.

2018-06-01

We report on an experimental investigation of the time-dependent spatial intensity distribution of near-infrared idler pulses from an optical parametric oscillator measured using an infrared (IR) camera, in contrast to beam profiles obtained using traditional knife-edge techniques. Comparisons show the information gained by utilizing the thermal camera provides more detail than the spatially- or time-averaged measurements from a knife-edge profile. Synchronization, averaging, and thresholding techniques are applied to enhance the images acquired. The additional information obtained can improve the process by which semiconductor devices and other IR lasers are characterized for their beam quality and output response and thereby result in IR devices with higher performance.

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

Ray, Jaideep; Lee, Jina; Lefantzi, Sophia

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization.more » The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.« less

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light

NASA Astrophysics Data System (ADS)

Stark, Dominic; Launet, Barthelemy; Schawinski, Kevin; Zhang, Ce; Koss, Michael; Turp, M. Dennis; Sartori, Lia F.; Zhang, Hantian; Chen, Yiru; Weigel, Anna K.

2018-06-01

The study of unobscured active galactic nuclei (AGN) and quasars depends on the reliable decomposition of the light from the AGN point source and the extended host galaxy light. The problem is typically approached using parametric fitting routines using separate models for the host galaxy and the point spread function (PSF). We present a new approach using a Generative Adversarial Network (GAN) trained on galaxy images. We test the method using Sloan Digital Sky Survey r-band images with artificial AGN point sources added that are then removed using the GAN and with parametric methods using GALFIT. When the AGN point source is more than twice as bright as the host galaxy, we find that our method, PSFGAN, can recover point source and host galaxy magnitudes with smaller systematic error and a lower average scatter (49 per cent). PSFGAN is more tolerant to poor knowledge of the PSF than parametric methods. Our tests show that PSFGAN is robust against a broadening in the PSF width of ± 50 per cent if it is trained on multiple PSFs. We demonstrate that while a matched training set does improve performance, we can still subtract point sources using a PSFGAN trained on non-astronomical images. While initial training is computationally expensive, evaluating PSFGAN on data is more than 40 times faster than GALFIT fitting two components. Finally, PSFGAN is more robust and easy to use than parametric methods as it requires no input parameters.

Preclinical evaluation of parametric image reconstruction of [18F]FMISO PET: correlation with ex vivo immunohistochemistry

NASA Astrophysics Data System (ADS)

Cheng, Xiaoyin; Bayer, Christine; Maftei, Constantin-Alin; Astner, Sabrina T.; Vaupel, Peter; Ziegler, Sibylle I.; Shi, Kuangyu

2014-01-01

Compared to indirect methods, direct parametric image reconstruction (PIR) has the advantage of high quality and low statistical errors. However, it is not yet clear if this improvement in quality is beneficial for physiological quantification. This study aimed to evaluate direct PIR for the quantification of tumor hypoxia using the hypoxic fraction (HF) assessed from immunohistological data as a physiological reference. Sixteen mice with xenografted human squamous cell carcinomas were scanned with dynamic [18F]FMISO PET. Afterward, tumors were sliced and stained with H&E and the hypoxia marker pimonidazole. The hypoxic signal was segmented using k-means clustering and HF was specified as the ratio of the hypoxic area over the viable tumor area. The parametric Patlak slope images were obtained by indirect voxel-wise modeling on reconstructed images using filtered back projection and ordered-subset expectation maximization (OSEM) and by direct PIR (e.g., parametric-OSEM, POSEM). The mean and maximum Patlak slopes of the tumor area were investigated and compared with HF. POSEM resulted in generally higher correlations between slope and HF among the investigated methods. A strategy for the delineation of the hypoxic tumor volume based on thresholding parametric images at half maximum of the slope is recommended based on the results of this study.

Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

PubMed

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P; Gee, James C

2009-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.

Automatic Correction of Intensity Nonuniformity from Sparseness of Gradient Distribution in Medical Images

PubMed Central

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P.; Gee, James C.

2013-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities. PMID:20426191

Target Identification Using Harmonic Wavelet Based ISAR Imaging

NASA Astrophysics Data System (ADS)

Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

2006-12-01

A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

Synthesis and Analysis of Custom Bi-directional Reflectivity Distribution Functions in DIRSIG

NASA Astrophysics Data System (ADS)

Dank, J.; Allen, D.

2016-09-01

The bi-directional reflectivity distribution (BRDF) function is a fundamental optical property of materials, characterizing important properties of light scattered by a surface. For accurate radiance calculations using synthetic targets and numerical simulations such as the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model, fidelity of the target BRDFs is critical. While fits to measured BRDF data can be used in DIRSIG, obtaining high-quality data over a large spectral continuum can be time-consuming and expensive, requiring significant investment in illumination sources, sensors, and other specialized hardware. As a consequence, numerous parametric BRDF models are available to approximate actual behavior; but these all have shortcomings. Further, DIRSIG doesn't allow direct visualization of BRDFs, making it difficult for the user to understand the numerical impact of various models. Here, we discuss the innovative use of "mixture maps" to synthesize custom BRDFs as linear combinations of parametric models and measured data. We also show how DIRSIG's interactive mode can be used to visualize and analyze both available parametric models currently used in DIRSIG and custom BRDFs developed using our methods.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical FDG patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection. PMID:24080994

Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical (18)F-deoxyglucose patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30 min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole-body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection.

THz-wave parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We have also developed a novel basic technology for THz imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral trasillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Excitation-resolved multispectral method for imaging pharmacokinetic parameters in dynamic fluorescent molecular tomography

NASA Astrophysics Data System (ADS)

Chen, Maomao; Zhou, Yuan; Su, Han; Zhang, Dong; Luo, Jianwen

2017-04-01

Imaging of the pharmacokinetic parameters in dynamic fluorescence molecular tomography (DFMT) can provide three-dimensional metabolic information for biological studies and drug development. However, owing to the ill-posed nature of the FMT inverse problem, the relatively low quality of the parametric images makes it difficult to investigate the different metabolic processes of the fluorescent targets with small distances. An excitation-resolved multispectral DFMT method is proposed; it is based on the fact that the fluorescent targets with different concentrations show different variations in the excitation spectral domain and can be considered independent signal sources. With an independent component analysis method, the spatial locations of different fluorescent targets can be decomposed, and the fluorescent yields of the targets at different time points can be recovered. Therefore, the metabolic process of each component can be independently investigated. Simulations and phantom experiments are carried out to evaluate the performance of the proposed method. The results demonstrated that the proposed excitation-resolved multispectral method can effectively improve the reconstruction accuracy of the parametric images in DFMT.

Probabilistic images (PBIS): A concise image representation technique for multiple parameters

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

Wu, L.C.; Yeh, S.H.; Chen, Z.

1984-01-01

Based on m parametric images (PIs) derived from a dynamic series (DS), each pixel of DS is regarded as an m-dimensional vector. Given one set of normal samples (pixels) N and another of abnormal samples A, probability density functions (pdfs) of both sets are estimated. Any unknown sample is classified into N or A by calculating the probability of its being in the abnormal set using the Bayes' theorem. Instead of estimating the multivariate pdfs, a distance ratio transformation is introduced to map the m-dimensional sample space to one dimensional Euclidean space. Consequently, the image that localizes the regional abnormalitiesmore » is characterized by the probability of being abnormal. This leads to the new representation scheme of PBIs. Tc-99m HIDA study for detecting intrahepatic lithiasis (IL) was chosen as an example of constructing PBI from 3 parameters derived from DS and such a PBI was compared with those 3 PIs, namely, retention ratio image (RRI), peak time image (TNMAX) and excretion mean transit time image (EMTT). 32 normal subjects and 20 patients with proved IL were collected and analyzed. The resultant sensitivity and specificity of PBI were 97% and 98% respectively. They were superior to those of any of the 3 PIs: RRI (94/97), TMAX (86/88) and EMTT (94/97). Furthermore, the contrast of PBI was much better than that of any other image. This new image formation technique, based on multiple parameters, shows the functional abnormalities in a structural way. Its good contrast makes the interpretation easy. This technique is powerful compared to the existing parametric image method.« less

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant

2011-03-01

Currently, there is significant interest in developing methods for quantitative integration of multi-parametric (structural, functional) imaging data with the objective of building automated meta-classifiers to improve disease detection, diagnosis, and prognosis. Such techniques are required to address the differences in dimensionalities and scales of individual protocols, while deriving an integrated multi-parametric data representation which best captures all disease-pertinent information available. In this paper, we present a scheme called Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE); a powerful, generalizable framework applicable to a variety of domains for multi-parametric data representation and fusion. Our scheme utilizes an ensemble of embeddings (via dimensionality reduction, DR); thereby exploiting the variance amongst multiple uncorrelated embeddings in a manner similar to ensemble classifier schemes (e.g. Bagging, Boosting). We apply this framework to the problem of prostate cancer (CaP) detection on 12 3 Tesla pre-operative in vivo multi-parametric (T2-weighted, Dynamic Contrast Enhanced, and Diffusion-weighted) magnetic resonance imaging (MRI) studies, in turn comprising a total of 39 2D planar MR images. We first align the different imaging protocols via automated image registration, followed by quantification of image attributes from individual protocols. Multiple embeddings are generated from the resultant high-dimensional feature space which are then combined intelligently to yield a single stable solution. Our scheme is employed in conjunction with graph embedding (for DR) and probabilistic boosting trees (PBTs) to detect CaP on multi-parametric MRI. Finally, a probabilistic pairwise Markov Random Field algorithm is used to apply spatial constraints to the result of the PBT classifier, yielding a per-voxel classification of CaP presence. Per-voxel evaluation of detection results against ground truth for CaP extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).

The usability of the optical parametric amplification of light for high-angular-resolution imaging and fast astrometry

NASA Astrophysics Data System (ADS)

Kurek, A. R.; Stachowski, A.; Banaszek, K.; Pollo, A.

2018-05-01

High-angular-resolution imaging is crucial for many applications in modern astronomy and astrophysics. The fundamental diffraction limit constrains the resolving power of both ground-based and spaceborne telescopes. The recent idea of a quantum telescope based on the optical parametric amplification (OPA) of light aims to bypass this limit for the imaging of extended sources by an order of magnitude or more. We present an updated scheme of an OPA-based device and a more accurate model of the signal amplification by such a device. The semiclassical model that we present predicts that the noise in such a system will form so-called light speckles as a result of light interference in the optical path. Based on this model, we analysed the efficiency of OPA in increasing the angular resolution of the imaging of extended targets and the precise localization of a distant point source. According to our new model, OPA offers a gain in resolved imaging in comparison to classical optics. For a given time-span, we found that OPA can be more efficient in localizing a single distant point source than classical telescopes.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Convergence optimization of parametric MLEM reconstruction for estimation of Patlak plot parameters.

PubMed

Angelis, Georgios I; Thielemans, Kris; Tziortzi, Andri C; Turkheimer, Federico E; Tsoumpas, Charalampos

2011-07-01

In dynamic positron emission tomography data many researchers have attempted to exploit kinetic models within reconstruction such that parametric images are estimated directly from measurements. This work studies a direct parametric maximum likelihood expectation maximization algorithm applied to [(18)F]DOPA data using reference-tissue input function. We use a modified version for direct reconstruction with a gradually descending scheme of subsets (i.e. 18-6-1) initialized with the FBP parametric image for faster convergence and higher accuracy. The results compared with analytic reconstructions show quantitative robustness (i.e. minimal bias) and clinical reproducibility within six human acquisitions in the region of clinical interest. Bland-Altman plots for all the studies showed sufficient quantitative agreement between the direct reconstructed parametric maps and the indirect FBP (--0.035x+0.48E--5). Copyright © 2011 Elsevier Ltd. All rights reserved.

Advanced Imaging Methods for Long-Baseline Optical Interferometry

NASA Astrophysics Data System (ADS)

Le Besnerais, G.; Lacour, S.; Mugnier, L. M.; Thiebaut, E.; Perrin, G.; Meimon, S.

2008-11-01

We address the data processing methods needed for imaging with a long baseline optical interferometer. We first describe parametric reconstruction approaches and adopt a general formulation of nonparametric image reconstruction as the solution of a constrained optimization problem. Within this framework, we present two recent reconstruction methods, Mira and Wisard, representative of the two generic approaches for dealing with the missing phase information. Mira is based on an implicit approach and a direct optimization of a Bayesian criterion while Wisard adopts a self-calibration approach and an alternate minimization scheme inspired from radio-astronomy. Both methods can handle various regularization criteria. We review commonly used regularization terms and introduce an original quadratic regularization called ldquosoft support constraintrdquo that favors the object compactness. It yields images of quality comparable to nonquadratic regularizations on the synthetic data we have processed. We then perform image reconstructions, both parametric and nonparametric, on astronomical data from the IOTA interferometer, and discuss the respective roles of parametric and nonparametric approaches for optical interferometric imaging.

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle

PubMed Central

Valentinitsch, Alexander; Karampinos, Dimitrios C.; Alizai, Hamza; Subburaj, Karupppasamy; Kumar, Deepak; Link, Thomas M.; Majumdar, Sharmila

2012-01-01

Purpose To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions in order to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach. Materials and Methods Unsupervised standard k-means clustering was employed to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages including tissue, muscle and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared to a manual segmentation. Results The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R2: 0.96) and for cases with up to moderate IMAT area in the calf (R2: 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation. Conclusion The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total post-processing time. PMID:23097409

Ultrasound parametric imaging of hepatic steatosis using the homodyned-K distribution: An animal study.

PubMed

Fang, Jui; Zhou, Zhuhuang; Chang, Ning-Fang; Wan, Yung-Liang; Tsui, Po-Hsiang

2018-07-01

Hepatic steatosis is an abnormal state where excess lipid mass is accumulated in hepatocyte vesicles. Backscattered ultrasound signals received from the liver contain useful information regarding the degree of steatosis in the liver. The homodyned-K (HK) distribution has been demonstrated as a general model for ultrasound backscattering. The estimator based on the first three integer moments (denoted as "FTM") of the intensity has potential for practical applications because of its simplicity and low computational complexity. This study explored the diagnostic performance of HK parametric imaging based on the FTM method in the assessment of hepatic steatosis. Phantom experiments were initially conducted using the sliding window technique to determine an appropriate window size length (WSL) for HK parametric imaging. Subsequently, hepatic steatosis was induced in male Wistar rats fed a methionine- and choline-deficient (MCD) diet for 0 (i.e., normal control), 1, 2, 4, 6, and 8 weeks (n = 36; six rats in each group). After completing the scheduled MCD diet, ultrasound B-mode and HK imaging of the rat livers were performed in vivo and histopathological examinations were conducted to score the degree of hepatic steatosis. HK parameters μ (related to scatterer number density) and k (related to scatterer periodicity) were expressed as functions of the steatosis stage in terms of the median and interquartile range (IQR). Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance levels of the μ and k parameters. The results showed that an appropriate WSL for HK parametric imaging is seven times the pulse length of the transducer. The median value of the μ parameter increased monotonically from 0.194 (IQR: 0.18-0.23) to 0.893 (IQR: 0.64-1.04) as the steatosis stage increased. Concurrently, the median value of the k parameter increased from 0.279 (IQR: 0.26-0.31) to 0.5 (IQR: 0.41-0.54) in the early stages (normal to mild) and decreased to 0.39 (IQR: 0.29-0.45) in the advanced stages (moderate to severe). The areas under the ROC curves obtained using (μ, k) were (0.947, 0.804), (0.914, 0.575), and (0.813, 0.604) for the steatosis stages of ≥mild, ≥moderate, and ≥severe, respectively. The current findings suggest that ultrasound HK parametric imaging based on FTM estimation has great potential for future clinical diagnoses of hepatic steatosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping

PubMed Central

Keith, Lauren; Ross, Brian D.; Galbán, Craig J.; Luker, Gary D.; Galbán, Stefanie; Zhao, Binsheng; Guo, Xiaotao; Chenevert, Thomas L.; Hoff, Benjamin A.

2017-01-01

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice. PMID:28286871

Perceptual reversals during binocular rivalry: ERP components and their concomitant source differences.

PubMed

Britz, Juliane; Pitts, Michael A

2011-11-01

We used an intermittent stimulus presentation to investigate event-related potential (ERP) components associated with perceptual reversals during binocular rivalry. The combination of spatiotemporal ERP analysis with source imaging and statistical parametric mapping of the concomitant source differences yielded differences in three time windows: reversals showed increased activity in early visual (∼120 ms) and in inferior frontal and anterior temporal areas (∼400-600 ms) and decreased activity in the ventral stream (∼250-350 ms). The combination of source imaging and statistical parametric mapping suggests that these differences were due to differences in generator strength and not generator configuration, unlike the initiation of reversals in right inferior parietal areas. These results are discussed within the context of the extensive network of brain areas that has been implicated in the initiation, implementation, and appraisal of bistable perceptual reversals. Copyright © 2011 Society for Psychophysiological Research.

Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Ghavidel, Sahar; Abolmaesumi, Purang; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Romagnoli, Cesare; Cool, Derek W.; Bastian-Jordan, Matthew; Kassam, Zahra; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Mousavi, Parvin

2016-03-01

Recently, multi-parametric Magnetic Resonance Imaging (mp-MRI) has been used to improve the sensitivity of detecting high-risk prostate cancer (PCa). Prior to biopsy, primary and secondary cancer lesions are identified on mp-MRI. The lesions are then targeted using TRUS guidance. In this paper, for the first time, we present a fused mp-MRI-temporal-ultrasound framework for characterization of PCa, in vivo. Cancer classification results obtained using temporal ultrasound are fused with those achieved using consolidated mp-MRI maps determined by multiple observers. We verify the outcome of our study using histopathology following deformable registration of ultrasound and histology images. Fusion of temporal ultrasound and mp-MRI for characterization of the PCa results in an area under the receiver operating characteristic curve (AUC) of 0.86 for cancerous regions with Gleason scores (GSs)>=3+3, and AUC of 0.89 for those with GSs>=3+4.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, S.M.; Bliss, D.E.; Kimmel, M.W.; Neal, D.R.

1999-08-10

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media. 13 figs.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, Stewart M.; Bliss, David E.; Kimmel, Mark W.; Neal, Daniel R.

1999-01-01

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data.

PubMed

Kotasidis, F A; Mehranian, A; Zaidi, H

2016-05-07

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

NASA Astrophysics Data System (ADS)

Kotasidis, F. A.; Mehranian, A.; Zaidi, H.

2016-05-01

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

PET image reconstruction using multi-parametric anato-functional priors

NASA Astrophysics Data System (ADS)

Mehranian, Abolfazl; Belzunce, Martin A.; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J.

2017-08-01

In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [18F]florbetaben and [18F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical results also showed that the Gaussian prior with voxel-based feature vectors, the Bowsher and the joint Burg entropy priors were the best performing priors. However, for the FDG dataset with simulated tumours, the TV and proposed priors were capable of preserving the PET-unique tumours. Finally, an important outcome was the demonstration that the MAP reconstruction of a low-count FDG PET dataset using the proposed joint entropy prior can lead to comparable image quality to a conventional ML reconstruction with up to 5 times more counts. In conclusion, multi-parametric anato-functional priors provide a solution to address the pitfalls of the conventional priors and are therefore likely to increase the diagnostic confidence in MR-guided PET image reconstructions.

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

PubMed Central

Winfield, Jessica M.; Payne, Geoffrey S.; Weller, Alex; deSouza, Nandita M.

2016-01-01

Abstract Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice. PMID:27748710

A distribution-based parametrization for improved tomographic imaging of solute plumes

USGS Publications Warehouse

Pidlisecky, Adam; Singha, K.; Day-Lewis, F. D.

2011-01-01

Difference geophysical tomography (e.g. radar, resistivity and seismic) is used increasingly for imaging fluid flow and mass transport associated with natural and engineered hydrologic phenomena, including tracer experiments, in situ remediation and aquifer storage and recovery. Tomographic data are collected over time, inverted and differenced against a background image to produce 'snapshots' revealing changes to the system; these snapshots readily provide qualitative information on the location and morphology of plumes of injected tracer, remedial amendment or stored water. In principle, geometric moments (i.e. total mass, centres of mass, spread, etc.) calculated from difference tomograms can provide further quantitative insight into the rates of advection, dispersion and mass transfer; however, recent work has shown that moments calculated from tomograms are commonly biased, as they are strongly affected by the subjective choice of regularization criteria. Conventional approaches to regularization (Tikhonov) and parametrization (image pixels) result in tomograms which are subject to artefacts such as smearing or pixel estimates taking on the sign opposite to that expected for the plume under study. Here, we demonstrate a novel parametrization for imaging plumes associated with hydrologic phenomena. Capitalizing on the mathematical analogy between moment-based descriptors of plumes and the moment-based parameters of probability distributions, we design an inverse problem that (1) is overdetermined and computationally efficient because the image is described by only a few parameters, (2) produces tomograms consistent with expected plume behaviour (e.g. changes of one sign relative to the background image), (3) yields parameter estimates that are readily interpreted for plume morphology and offer direct insight into hydrologic processes and (4) requires comparatively few data to achieve reasonable model estimates. We demonstrate the approach in a series of numerical examples based on straight-ray difference-attenuation radar monitoring of the transport of an ionic tracer, and show that the methodology outlined here is particularly effective when limited data are available. ?? 2011 The Authors Geophysical Journal International ?? 2011 RAS.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Minamide, Hiroaki; Ito, Hiromasa

2005-07-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO3 or MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave source with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni-directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a THz-wave parametric oscillator, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which are illegal, while one is an over-the-counter drug.

Rapid Parametric Mapping of the Longitudinal Relaxation Time T1 Using Two-Dimensional Variable Flip Angle Magnetic Resonance Imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla

PubMed Central

Dieringer, Matthias A.; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I.; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Introduction Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. Methods T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Results Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Conclusion Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization. PMID:24621588

Rapid parametric mapping of the longitudinal relaxation time T1 using two-dimensional variable flip angle magnetic resonance imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla.

PubMed

Dieringer, Matthias A; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization.

Characterization of the Embryogenic Tissue of the Norway Spruce Including a Transition Layer between the Tissue and the Culture Medium by Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Kořínek, R.; Mikulka, J.; Hřib, J.; Hudec, J.; Havel, L.; Bartušek, K.

2017-02-01

The paper describes the visualization of the cells (ESEs) and mucilage (ECMSN) in an embryogenic tissue via magnetic resonance imaging (MRI) relaxometry measurement combined with the subsequent multi-parametric segmentation. The computed relaxometry maps T1 and T2 show a thin layer (transition layer) between the culture medium and the embryogenic tissue. The ESEs, mucilage, and transition layer differ in their relaxation times T1 and T2; thus, these times can be used to characterize the individual parts within the embryogenic tissue. The observed mean values of the relaxation times T1 and T2 of the ESEs, mucilage, and transition layer are as follows: 1469 ± 324 and 53 ± 10 ms, 1784 ± 124 and 74 ± 8 ms, 929 ± 164 and 32 ± 4.7 ms, respectively. The multi-parametric segmentation exploiting the T1 and T2 relaxation times as a classifier shows the distribution of the ESEs and mucilage within the embryogenic tissue. The discussed T1 and T2 indicators can be utilized to characterize both the growth-related changes in an embryogenic tissue and the effect of biotic/abiotic stresses, thus potentially becoming a distinctive indicator of the state of any examined embryogenic tissue.

Method of the active contour for segmentation of bone systems on bitmap images

NASA Astrophysics Data System (ADS)

Vu, Hai Anh; Safonov, Roman A.; Kolesnikova, Anna S.; Kirillova, Irina V.; Kossovich, Leonid U.

2018-02-01

It is developed within a method of the active contours the approach, which is allowing to realize separation of a contour of a object of the image in case of its segmentation. This approach exceeds a parametric method on speed, but also does not concede to it on decision accuracy. The approach is offered within this operation will allow to realize allotment of a contour with high accuracy of the image and quicker than a parametric method of the active contours.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies.

PubMed

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-07

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18 F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18 F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of [Formula: see text], the tracer transport rate (ml · min -1 · ml -1 ), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced [Formula: see text] maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced [Formula: see text] estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies

PubMed Central

Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong

2017-01-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of K1, the tracer transport rate (mL.min−1.mL−1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced K1 maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced K1 estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in-vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance. PMID:28379843

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

NASA Astrophysics Data System (ADS)

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of {{K}1} , the tracer transport rate (ml · min-1 · ml-1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced {{K}1} maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced {{K}1} estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Fitting C 2 Continuous Parametric Surfaces to Frontiers Delimiting Physiologic Structures

PubMed Central

Bayer, Jason D.

2014-01-01

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous. PMID:24782911

Multi-parametric analysis of phagocyte antimicrobial responses using imaging flow cytometry.

PubMed

Havixbeck, Jeffrey J; Wong, Michael E; More Bayona, Juan A; Barreda, Daniel R

2015-08-01

We feature a multi-parametric approach based on an imaging flow cytometry platform for examining phagocyte antimicrobial responses against the gram-negative bacterium Aeromonas veronii. This pathogen is known to induce strong inflammatory responses across a broad range of animal species, including humans. We examined the contribution of A. veronii to the induction of early phagocyte inflammatory processes in RAW 264.7 murine macrophages in vitro. We found that A. veronii, both in live or heat-killed forms, induced similar levels of macrophage activation based on NF-κB translocation. Although these macrophages maintained high levels of viability following heat-killed or live challenges with A. veronii, we identified inhibition of macrophage proliferation as early as 1h post in vitro challenge. The characterization of phagocytic responses showed a time-dependent increase in phagocytosis upon A. veronii challenge, which was paired with a robust induction of intracellular respiratory burst responses. Interestingly, despite the overall increase in the production of reactive oxygen species (ROS) among RAW 264.7 macrophages, we found a significant reduction in the production of ROS among the macrophage subset that had bound A. veronii. Phagocytic uptake of the pathogen further decreased ROS production levels, even beyond those of unstimulated controls. Overall, this multi-parametric imaging flow cytometry-based approach allowed for segregation of unique phagocyte sub-populations and examination of their downstream antimicrobial responses, and should contribute to improved understanding of phagocyte responses against Aeromonas and other pathogens. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous parametric generation and up-conversion of entangled optical images

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

Saygin, M. Yu., E-mail: mihasyu@gmail.com; Chirkin, A. S., E-mail: aschirkin@rambler.r

A quantum theory of parametric amplification and frequency conversion of an optical image in coupled nonlinear optical processes that include one parametric amplification process at high-frequency pumping and two up-conversion processes in the same pump field is developed. The field momentum operator that takes into account the diffraction and group velocities of the waves is used to derive the quantum equations related to the spatial dynamics of the images during the interaction. An optical scheme for the amplification and conversion of a close image is considered. The mean photon number density and signal-to-noise ratio are calculated in the fixed-pump-field approximationmore » for images at various frequencies. It has been established that the signal-to-noise ratio decreases with increasing interaction length in the amplified image and increases in the images at the generated frequencies, tending to asymptotic values for all interacting waves. The variance of the difference of the numbers of photons is calculated for various pairs of frequencies. The quantum entanglement of the optical images formed in a high-frequency pump field is shown to be converted to higher frequencies during the generation of sum frequencies. Thus, two pairs of entangled optical images are produced in the process considered.« less

TU-H-CAMPUS-IeP3-04: Evaluation of Changes in Quantitative Ultrasound Parameters During Prostate Radiotherapy

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

Najafi, M; El Kaffas, A; Han, B

Purpose: Clarity Autoscan ultrasound monitoring system allows acquisition of raw radiofrequency (RF) ultrasound data prior and during radiotherapy. This enables the computation of 3D Quantitative Ultrasound (QUS) tissue parametric maps from. We aim to evaluate whether QUS parameters undergo changes with radiotherapy and thus potentially be used as early predictors and/or markers of treatment response in prostate cancer patients. Methods: In-vivo evaluation was performed under IRB protocol to allow data collection in prostate patients treated with VMAT whereby prostate was imaged through the acoustic window of the perineum. QUS spectroscopy analysis was carried out by computing a tissue power spectrummore » normalized to the power spectrum obtained from a quartz to remove system transfer function effects. A ROI was selected within the 3D image volume of the prostate. Because longitudinal registration was optimal, the same features could be used to select ROIs at roughly the same location in images acquired on different days. Parametric maps were generated within the rectangular ROIs with window sizes that were approximately 8 times the wavelength of the ultrasound. The mid-band fit (MBF), spectral slope (SS) and spectral intercept (SI) QUS parameters were computed for each window within the ROI and displayed as parametric maps. Quantitative parameters were obtained by averaging each of the spectral parameters over the whole ROI. Results: Data was acquired for over 21 treatment fractions. Preliminary results show changes in the parametric maps. MBF values decreased from −33.9 dB to −38.7 dB from pre-treatment to the last day of treatment. The spectral slope increased from −1.1 a.u. to −0.5 a.u., and spectral intercept decreased from −28.2 dB to −36.3 dB over the 21 treatment regimen. Conclusion: QUS parametric maps change over the course of treatment which warrants further investigation in their potential use for treatment planning and predicting treatment outcomes. Research was supported by Elekta.« less

Strong-lensing analysis of A2744 with MUSE and Hubble Frontier Fields images

NASA Astrophysics Data System (ADS)

Mahler, G.; Richard, J.; Clément, B.; Lagattuta, D.; Schmidt, K.; Patrício, V.; Soucail, G.; Bacon, R.; Pello, R.; Bouwens, R.; Maseda, M.; Martinez, J.; Carollo, M.; Inami, H.; Leclercq, F.; Wisotzki, L.

2018-01-01

We present an analysis of Multi Unit Spectroscopic Explorer (MUSE) observations obtained on the massive Frontier Fields (FFs) cluster A2744. This new data set covers the entire multiply imaged region around the cluster core. The combined catalogue consists of 514 spectroscopic redshifts (with 414 new identifications). We use this redshift information to perform a strong-lensing analysis revising multiple images previously found in the deep FF images, and add three new MUSE-detected multiply imaged systems with no obvious Hubble Space Telescope counterpart. The combined strong-lensing constraints include a total of 60 systems producing 188 images altogether, out of which 29 systems and 83 images are spectroscopically confirmed, making A2744 one of the most well-constrained clusters to date. Thanks to the large amount of spectroscopic redshifts, we model the influence of substructures at larger radii, using a parametrization including two cluster-scale components in the cluster core and several group scale in the outskirts. The resulting model accurately reproduces all the spectroscopic multiple systems, reaching an rms of 0.67 arcsec in the image plane. The large number of MUSE spectroscopic redshifts gives us a robust model, which we estimate reduces the systematic uncertainty on the 2D mass distribution by up to ∼2.5 times the statistical uncertainty in the cluster core. In addition, from a combination of the parametrization and the set of constraints, we estimate the relative systematic uncertainty to be up to 9 per cent at 200 kpc.

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Radiofrequency Ablation, MR Thermometry, and High-Spatial-Resolution MR Parametric Imaging with a Single, Minimally Invasive Device.

PubMed

Ertürk, M Arcan; Sathyanarayana Hegde, Shashank; Bottomley, Paul A

2016-12-01

Purpose To develop and demonstrate in vitro and in vivo a single interventional magnetic resonance (MR)-active device that integrates the functions of precise identification of a tissue site with the delivery of radiofrequency (RF) energy for ablation, high-spatial-resolution thermal mapping to monitor thermal dose, and quantitative MR imaging relaxometry to document ablation-induced tissue changes for characterizing ablated tissue. Materials and Methods All animal studies were approved by the institutional animal care and use committee. A loopless MR imaging antenna composed of a tuned microcable either 0.8 or 2.2 mm in diameter with an extended central conductor was switched between a 3-T MR imaging unit and an RF power source to monitor and perform RF ablation in bovine muscle and human artery samples in vitro and in rabbits in vivo. High-spatial-resolution (250-300-μm) proton resonance frequency shift MR thermometry was interleaved with ablations. Quantitative spin-lattice (T1) and spin-spin (T2) relaxation time MR imaging mapping was performed before and after ablation. These maps were compared with findings from gross tissue examination of the region of ablated tissue after MR imaging. Results High-spatial-resolution MR imaging afforded temperature mapping in less than 8 seconds for monitoring ablation temperatures in excess of 85°C delivered by the same device. This produced irreversible thermal injury and necrosis. Quantitative MR imaging relaxation time maps demonstrated up to a twofold variation in mean regional T1 and T2 after ablation versus before ablation. Conclusion A simple, integrated, minimally invasive interventional probe that provides image-guided therapy delivery, thermal mapping of dose, and detection of ablation-associated MR imaging parametric changes was developed and demonstrated. With this single-device approach, coupling-related safety concerns associated with multiple conductor approaches were avoided. © RSNA, 2016 Online supplemental material is available for this article.

4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties

NASA Astrophysics Data System (ADS)

Ralli, George P.; Chappell, Michael A.; McGowan, Daniel R.; Sharma, Ricky A.; Higgins, Geoff S.; Fenwick, John D.

2018-05-01

4D reconstruction of dynamic positron emission tomography (dPET) data can improve the signal-to-noise ratio in reconstructed image sequences by fitting smooth temporal functions to the voxel time-activity-curves (TACs) during the reconstruction, though the optimal choice of function remains an open question. We propose a spline-residue model, which describes TACs as weighted sums of convolutions of the arterial input function with cubic B-spline basis functions. Convolution with the input function constrains the spline-residue model at early time-points, potentially enhancing noise suppression in early time-frames, while still allowing a wide range of TAC descriptions over the entire imaged time-course, thus limiting bias. Spline-residue based 4D-reconstruction is compared to that of a conventional (non-4D) maximum a posteriori (MAP) algorithm, and to 4D-reconstructions based on adaptive-knot cubic B-splines, the spectral model and an irreversible two-tissue compartment (‘2C3K’) model. 4D reconstructions were carried out using a nested-MAP algorithm including spatial and temporal roughness penalties. The algorithms were tested using Monte-Carlo simulated scanner data, generated for a digital thoracic phantom with uptake kinetics based on a dynamic [18F]-Fluromisonidazole scan of a non-small cell lung cancer patient. For every algorithm, parametric maps were calculated by fitting each voxel TAC within a sub-region of the reconstructed images with the 2C3K model. Compared to conventional MAP reconstruction, spline-residue-based 4D reconstruction achieved  >50% improvements for five of the eight combinations of the four kinetics parameters for which parametric maps were created with the bias and noise measures used to analyse them, and produced better results for 5/8 combinations than any of the other reconstruction algorithms studied, while spectral model-based 4D reconstruction produced the best results for 2/8. 2C3K model-based 4D reconstruction generated the most biased parametric maps. Inclusion of a temporal roughness penalty function improved the performance of 4D reconstruction based on the cubic B-spline, spectral and spline-residue models.

Parametric imaging of collagen structural changes in human osteoarthritic cartilage using optical polarization tractography

NASA Astrophysics Data System (ADS)

Ravanfar, Mohammadreza; Pfeiffer, Ferris M.; Bozynski, Chantelle C.; Wang, Yuanbo; Yao, Gang

2017-12-01

Collagen degeneration is an important pathological feature of osteoarthritis. The purpose of this study is to investigate whether the polarization-sensitive optical coherence tomography (PSOCT)-based optical polarization tractography (OPT) can be useful in imaging collagen structural changes in human osteoarthritic cartilage samples. OPT eliminated the banding artifacts in conventional PSOCT by calculating the depth-resolved local birefringence and fiber orientation. A close comparison between OPT and PSOCT showed that OPT provided improved visualization and characterization of the zonal structure in human cartilage. Experimental results obtained in this study also underlined the importance of knowing the collagen fiber orientation in conventional polarized light microscopy assessment. In addition, parametric OPT imaging was achieved by quantifying the surface roughness, birefringence, and fiber dispersion in the superficial zone of the cartilage. These quantitative parametric images provided complementary information on the structural changes in cartilage, which can be useful for a comprehensive evaluation of collagen damage in osteoarthritic cartilage.

Nonlinear PET parametric image reconstruction with MRI information using kernel method

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Non-local means denoising of dynamic PET images.

PubMed

Dutta, Joyita; Leahy, Richard M; Li, Quanzheng

2013-01-01

Dynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data. Model-based interpretation of dynamic PET images by means of parametric fitting, however, is often a challenging task due to high levels of noise, thus necessitating a denoising step. The objective of this paper is to develop and characterize a denoising framework for dynamic PET based on non-local means (NLM). NLM denoising computes weighted averages of voxel intensities assigning larger weights to voxels that are similar to a given voxel in terms of their local neighborhoods or patches. We introduce three key modifications to tailor the original NLM framework to dynamic PET. Firstly, we derive similarities from less noisy later time points in a typical PET acquisition to denoise the entire time series. Secondly, we use spatiotemporal patches for robust similarity computation. Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch. To assess the performance of our denoising technique, we performed a realistic simulation on a dynamic digital phantom based on the Digimouse atlas. For experimental validation, we denoised [Formula: see text] PET images from a mouse study and a hepatocellular carcinoma patient study. We compared the performance of NLM denoising with four other denoising approaches - Gaussian filtering, PCA, HYPR, and conventional NLM based on spatial patches. The simulation study revealed significant improvement in bias-variance performance achieved using our NLM technique relative to all the other methods. The experimental data analysis revealed that our technique leads to clear improvement in contrast-to-noise ratio in Patlak parametric images generated from denoised preclinical and clinical dynamic images, indicating its ability to preserve image contrast and high intensity details while lowering the background noise variance.

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

PubMed

Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

2017-11-01

Parametric response map (PRM) analysis of functional imaging has been shown to be an effective tool for early prediction of cancer treatment outcomes and may also be well-suited toward guiding personalized adaptive radiotherapy (RT) strategies such as sub-volume boosting. However, the PRM method was primarily designed for analysis of longitudinally acquired pairs of single-parameter image data. The purpose of this study was to demonstrate the feasibility of a generalized parametric response map analysis framework, which enables analysis of multi-parametric data while maintaining the key advantages of the original PRM method. MRI-derived apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps acquired at 1 and 3-months post-RT for 19 patients with high-grade glioma were used to demonstrate the algorithm. Images were first co-registered and then standardized using normal tissue image intensity values. Tumor voxels were then plotted in a four-dimensional Cartesian space with coordinate values equal to a voxel's image intensity in each of the image volumes and an origin defined as the multi-parametric mean of normal tissue image intensity values. Voxel positions were orthogonally projected onto a line defined by the origin and a pre-determined response vector. The voxels are subsequently classified as positive, negative or nil, according to whether projected positions along the response vector exceeded a threshold distance from the origin. The response vector was selected by identifying the direction in which the standard deviation of tumor image intensity values was maximally different between responding and non-responding patients within a training dataset. Voxel classifications were visualized via familiar three-class response maps and then the fraction of tumor voxels associated with each of the classes was investigated for predictive utility analogous to the original PRM method. Independent PRM and MPRM analyses of the contrast-enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset. © 2017 American Association of Physicists in Medicine.

sfDM: Open-Source Software for Temporal Analysis and Visualization of Brain Tumor Diffusion MR Using Serial Functional Diffusion Mapping.

PubMed

Ceschin, Rafael; Panigrahy, Ashok; Gopalakrishnan, Vanathi

2015-01-01

A major challenge in the diagnosis and treatment of brain tumors is tissue heterogeneity leading to mixed treatment response. Additionally, they are often difficult or at very high risk for biopsy, further hindering the clinical management process. To overcome this, novel advanced imaging methods are increasingly being adapted clinically to identify useful noninvasive biomarkers capable of disease stage characterization and treatment response prediction. One promising technique is called functional diffusion mapping (fDM), which uses diffusion-weighted imaging (DWI) to generate parametric maps between two imaging time points in order to identify significant voxel-wise changes in water diffusion within the tumor tissue. Here we introduce serial functional diffusion mapping (sfDM), an extension of existing fDM methods, to analyze the entire tumor diffusion profile along the temporal course of the disease. sfDM provides the tools necessary to analyze a tumor data set in the context of spatiotemporal parametric mapping: the image registration pipeline, biomarker extraction, and visualization tools. We present the general workflow of the pipeline, along with a typical use case for the software. sfDM is written in Python and is freely available as an open-source package under the Berkley Software Distribution (BSD) license to promote transparency and reproducibility.

Quantitative Imaging Biomarkers of NAFLD

PubMed Central

Kinner, Sonja; Reeder, Scott B.

2016-01-01

Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

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.

(18)F-alfatide II and (18)F-FDG dual-tracer dynamic PET for parametric, early prediction of tumor response to therapy.

PubMed

Guo, Jinxia; Guo, Ning; Lang, Lixin; Kiesewetter, Dale O; Xie, Qingguo; Li, Quanzheng; Eden, Henry S; Niu, Gang; Chen, Xiaoyuan

2014-01-01

A single dynamic PET acquisition using multiple tracers administered closely in time could provide valuable complementary information about a tumor's status under quasiconstant conditions. This study aimed to investigate the utility of dual-tracer dynamic PET imaging with (18)F-alfatide II ((18)F-AlF-NOTA-E[PEG4-c(RGDfk)]2) and (18)F-FDG for parametric monitoring of tumor responses to therapy. We administered doxorubicin to one group of athymic nude mice with U87MG tumors and paclitaxel protein-bound particles to another group of mice with MDA-MB-435 tumors. To monitor therapeutic responses, we performed dual-tracer dynamic imaging, in sessions that lasted 90 min, starting with injection via the tail vein catheters with (18)F-alfatide II, followed 40 min later by (18)F-FDG. To achieve signal separation of the 2 tracers, we fit a 3-compartment reversible model to the time-activity curve of (18)F-alfatide II for the 40 min before (18)F-FDG injection and then extrapolated to 90 min. The (18)F-FDG tumor time-activity curve was isolated from the 90-min dual-tracer tumor time-activity curve by subtracting the fitted (18)F-alfatide II tumor time-activity curve. With separated tumor time-activity curves, the (18)F-alfatide II binding potential (Bp = k3/k4) and volume of distribution (VD) and (18)F-FDG influx rate ((K1 × k3)/(k2 + k3)) based on the Patlak method were calculated to validate the signal recovery in a comparison with 60-min single-tracer imaging and to monitor therapeutic response. The transport and binding rate parameters K1-k3 of (18)F-alfatide II, calculated from the first 40 min of the dual-tracer dynamic scan, as well as Bp and VD correlated well with the parameters from the 60-min single-tracer scan (R(2) > 0.95). Compared with the results of single-tracer PET imaging, (18)F-FDG tumor uptake and influx were recovered well from dual-tracer imaging. On doxorubicin treatment, whereas no significant changes in static tracer uptake values of (18)F-alfatide II or (18)F-FDG were observed, both (18)F-alfatide II Bp and (18)F-FDG influx from kinetic analysis in tumors showed significant decreases. For therapy of MDA-MB-435 tumors with paclitaxel protein-bound particles, a significant decrease was observed only with (18)F-alfatide II Bp value from kinetic analysis but not (18)F-FDG influx. The parameters fitted with compartmental modeling from the dual-tracer dynamic imaging are consistent with those from single-tracer imaging, substantiating the feasibility of this methodology. Even though no significant differences in tumor size were found until 5 d after doxorubicin treatment started, at day 3 there were already substantial differences in (18)F-alfatide II Bp and (18)F-FDG influx rate. Dual-tracer imaging can measure (18)F-alfatide II Bp value and (18)F-FDG influx simultaneously to evaluate tumor angiogenesis and metabolism. Such changes are known to precede anatomic changes, and thus parametric imaging may offer the promise of early prediction of therapy response.

Spectral decompositions of multiple time series: a Bayesian non-parametric approach.

PubMed

Macaro, Christian; Prado, Raquel

2014-01-01

We consider spectral decompositions of multiple time series that arise in studies where the interest lies in assessing the influence of two or more factors. We write the spectral density of each time series as a sum of the spectral densities associated to the different levels of the factors. We then use Whittle's approximation to the likelihood function and follow a Bayesian non-parametric approach to obtain posterior inference on the spectral densities based on Bernstein-Dirichlet prior distributions. The prior is strategically important as it carries identifiability conditions for the models and allows us to quantify our degree of confidence in such conditions. A Markov chain Monte Carlo (MCMC) algorithm for posterior inference within this class of frequency-domain models is presented.We illustrate the approach by analyzing simulated and real data via spectral one-way and two-way models. In particular, we present an analysis of functional magnetic resonance imaging (fMRI) brain responses measured in individuals who participated in a designed experiment to study pain perception in humans.

Non-invasive breast biopsy method using GD-DTPA contrast enhanced MRI series and F-18-FDG PET/CT dynamic image series

NASA Astrophysics Data System (ADS)

Magri, Alphonso William

This study was undertaken to develop a nonsurgical breast biopsy from Gd-DTPA Contrast Enhanced Magnetic Resonance (CE-MR) images and F-18-FDG PET/CT dynamic image series. A five-step process was developed to accomplish this. (1) Dynamic PET series were nonrigidly registered to the initial frame using a finite element method (FEM) based registration that requires fiducial skin markers to sample the displacement field between image frames. A commercial FEM package (ANSYS) was used for meshing and FEM calculations. Dynamic PET image series registrations were evaluated using similarity measurements SAVD and NCC. (2) Dynamic CE-MR series were nonrigidly registered to the initial frame using two registration methods: a multi-resolution free-form deformation (FFD) registration driven by normalized mutual information, and a FEM-based registration method. Dynamic CE-MR image series registrations were evaluated using similarity measurements, localization measurements, and qualitative comparison of motion artifacts. FFD registration was found to be superior to FEM-based registration. (3) Nonlinear curve fitting was performed for each voxel of the PET/CT volume of activity versus time, based on a realistic two-compartmental Patlak model. Three parameters for this model were fitted; two of them describe the activity levels in the blood and in the cellular compartment, while the third characterizes the washout rate of F-18-FDG from the cellular compartment. (4) Nonlinear curve fitting was performed for each voxel of the MR volume of signal intensity versus time, based on a realistic two-compartment Brix model. Three parameters for this model were fitted: rate of Gd exiting the compartment, representing the extracellular space of a lesion; rate of Gd exiting a blood compartment; and a parameter that characterizes the strength of signal intensities. Curve fitting used for PET/CT and MR series was accomplished by application of the Levenburg-Marquardt nonlinear regression algorithm. The best-fit parameters were used to create 3D parametric images. Compartmental modeling evaluation was based on the ability of parameter values to differentiate between tissue types. This evaluation was used on registered and unregistered image series and found that registration improved results. (5) PET and MR parametric images were registered through FEM- and FFD-based registration. Parametric image registration was evaluated using similarity measurements, target registration error, and qualitative comparison. Comparing FFD and FEM-based registration results showed that the FEM method is superior. This five-step process constitutes a novel multifaceted approach to a nonsurgical breast biopsy that successfully executes each step. Comparison of this method to biopsy still needs to be done with a larger set of subject data.

Experimental demonstration of Klyshko's advanced-wave picture using a coincidence-count based, camera-enabled imaging system

NASA Astrophysics Data System (ADS)

Aspden, Reuben S.; Tasca, Daniel S.; Forbes, Andrew; Boyd, Robert W.; Padgett, Miles J.

2014-04-01

The Klyshko advanced-wave picture is a well-known tool useful in the conceptualisation of parametric down-conversion (SPDC) experiments. Despite being well-known and understood, there have been few experimental demonstrations illustrating its validity. Here, we present an experimental demonstration of this picture using a time-gated camera in an image-based coincidence measurement. We show an excellent agreement between the spatial distributions as predicted by the Klyshko picture and those obtained using the SPDC photon pairs. An interesting speckle feature is present in the Klyshko predictive images due to the spatial coherence of the back-propagated beam in the multi-mode fibre. This effect can be removed by mechanically twisting the fibre, thus degrading the spatial coherence of the beam and time-averaging the speckle pattern, giving an accurate correspondence between the predictive and SPDC images.

Dental caries imaging using hyperspectral stimulated Raman scattering microscopy

NASA Astrophysics Data System (ADS)

Wang, Zi; Zheng, Wei; Jian, Lin; Huang, Zhiwei

2016-03-01

We report the development of a polarization-resolved hyperspectral stimulated Raman scattering (SRS) imaging technique based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of dental caries. In our imaging system, hyperspectral SRS images (512×512 pixels) in both fingerprint region (800-1800 cm-1) and high-wavenumber region (2800-3600 cm-1) are acquired in minutes by scanning the wavelength of OPO output, which is a thousand times faster than conventional confocal micro Raman imaging. SRS spectra variations from normal enamel to caries obtained from the hyperspectral SRS images show the loss of phosphate and carbonate in the carious region. While polarization-resolved SRS images at 959 cm-1 demonstrate that the caries has higher depolarization ratio. Our results demonstrate that the polarization resolved-hyperspectral SRS imaging technique developed allows for rapid identification of the biochemical and structural changes of dental caries.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

PubMed

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

Chen, Li; He, Yu; Yap, Kim-Hui

2011-01-01

This paper proposes a new regularization scheme to address blind color image deconvolution. Color images generally have a significant correlation among the red, green, and blue channels. Conventional blind monochromatic deconvolution algorithms handle each color image channels independently, thereby ignoring the interchannel correlation present in the color images. In view of this, a unified regularization scheme for image is developed to recover edges of color images and reduce color artifacts. In addition, by using the color image properties, a spectral-based regularization operator is adopted to impose constraints on the blurs. Further, this paper proposes a reinforcement regularization framework that integrates a soft parametric learning term in addressing blind color image deconvolution. A blur modeling scheme is developed to evaluate the relevance of manifold parametric blur structures, and the information is integrated into the deconvolution scheme. An optimization procedure called alternating minimization is then employed to iteratively minimize the image- and blur-domain cost functions. Experimental results show that the method is able to achieve satisfactory restored color images under different blurring conditions.

Near-self-imaging cavity for three-mode optoacoustic parametric amplifiers using silicon microresonators.

PubMed

Liu, Jian; Torres, F A; Ma, Yubo; Zhao, C; Ju, L; Blair, D G; Chao, S; Roch-Jeune, I; Flaminio, R; Michel, C; Liu, K-Y

2014-02-10

Three-mode optoacoustic parametric amplifiers (OAPAs), in which a pair of photon modes are strongly coupled to an acoustic mode, provide a general platform for investigating self-cooling, parametric instability and very sensitive transducers. Their realization requires an optical cavity with tunable transverse modes and a high quality-factor mirror resonator. This paper presents the design of a table-top OAPA based on a near-self-imaging cavity design, using a silicon torsional microresonator. The design achieves a tuning coefficient for the optical mode spacing of 2.46  MHz/mm. This allows tuning of the mode spacing between amplification and self-cooling regimes of the OAPA device. Based on demonstrated resonator parameters (frequencies ∼400  kHz and quality-factors ∼7.5×10(5) we predict that the OAPA can achieve parametric instability with 1.6 μW of input power and mode cooling by a factor of 1.9×10(4) with 30 mW of input power.

Geometric Continuity: A Parametrization Independent Measure of Continuity for Computer Aided Geometric Design

DTIC Science & Technology

1985-08-01

in a. typography system, the surface of a. ship hull, or the skin of a.n airplane. To define objects such as these, higher order curve a.nd surface...rate). Thus, a parametrization contains infor- mation about the geometry (the shape or image of the curve), the orientation, and the rate. Figure 2.3...2.3. Each of the curves above has the same image ; they only differ in orientation and rate. Orientation is indicated by arrowheads and rate is

Design constraints of the LST fine guidance sensor

NASA Technical Reports Server (NTRS)

Wissinger, A. B.

1975-01-01

The LST Fine Guidance Sensor design is shaped by the rate of occurrence of suitable guide stars, the competition for telescope focal plane space with the Science Instruments, and the sensitivity of candidate image motion sensors. The relationship between these parameters is presented, and sensitivity to faint stars is shown to be of prime importance. An interferometric technique of image motion sensing is shown to have improved sensitivity and, therefore, a reduced focal plane area requirement in comparison with other candidate techniques (image-splitting prism and image dissector tube techniques). Another design requirement is speed in acquiring the guide star in order to maximize the time available for science observations. The design constraints are shown parametrically, and modelling results are presented.

Rapid computation of single PET scan rest-stress myocardial blood flow parametric images by table look up.

PubMed

Guehl, Nicolas J; Normandin, Marc D; Wooten, Dustin W; Rozen, Guy; Ruskin, Jeremy N; Shoup, Timothy M; Woo, Jonghye; Ptaszek, Leon M; Fakhri, Georges El; Alpert, Nathaniel M

2017-09-01

We have recently reported a method for measuring rest-stress myocardial blood flow (MBF) using a single, relatively short, PET scan session. The method requires two IV tracer injections, one to initiate rest imaging and one at peak stress. We previously validated absolute flow quantitation in ml/min/cc for standard bull's eye, segmental analysis. In this work, we extend the method for fast computation of rest-stress MBF parametric images. We provide an analytic solution to the single-scan rest-stress flow model which is then solved using a two-dimensional table lookup method (LM). Simulations were performed to compare the accuracy and precision of the lookup method with the original nonlinear method (NLM). Then the method was applied to 16 single scan rest/stress measurements made in 12 pigs: seven studied after infarction of the left anterior descending artery (LAD) territory, and nine imaged in the native state. Parametric maps of rest and stress MBF as well as maps of left (f LV ) and right (f RV ) ventricular spill-over fractions were generated. Regions of interest (ROIs) for 17 myocardial segments were defined in bull's eye fashion on the parametric maps. The mean of each ROI was then compared to the rest (K 1r ) and stress (K 1s ) MBF estimates obtained from fitting the 17 regional TACs with the NLM. In simulation, the LM performed as well as the NLM in terms of precision and accuracy. The simulation did not show that bias was introduced by the use of a predefined two-dimensional lookup table. In experimental data, parametric maps demonstrated good statistical quality and the LM was computationally much more efficient than the original NLM. Very good agreement was obtained between the mean MBF calculated on the parametric maps for each of the 17 ROIs and the regional MBF values estimated by the NLM (K 1map LM  = 1.019 × K 1 ROI NLM  + 0.019, R 2  = 0.986; mean difference = 0.034 ± 0.036 mL/min/cc). We developed a table lookup method for fast computation of parametric imaging of rest and stress MBF. Our results show the feasibility of obtaining good quality MBF maps using modest computational resources, thus demonstrating that the method can be applied in a clinical environment to obtain full quantitative MBF information. © 2017 American Association of Physicists in Medicine.

Classical imaging with undetected light

NASA Astrophysics Data System (ADS)

Cardoso, A. C.; Berruezo, L. P.; Ávila, D. F.; Lemos, G. B.; Pimenta, W. M.; Monken, C. H.; Saldanha, P. L.; Pádua, S.

2018-03-01

We obtained the phase and intensity images of an object by detecting classical light which never interacted with it. With a double passage of a pump and a signal laser beams through a nonlinear crystal, we observe interference between the two idler beams produced by stimulated parametric down conversion. The object is placed in the amplified signal beam after its first passage through the crystal and the image is observed in the interference of the generated idler beams. High contrast images can be obtained even for objects with small transmittance coefficient due to the geometry of the interferometer and to the stimulated parametric emission. Like its quantum counterpart, this three-color imaging concept can be useful when the object must be probed with light at a wavelength for which detectors are not available.

Independent Assessment of ITRF Site Velocities using GPS Imaging

NASA Astrophysics Data System (ADS)

Blewitt, G.; Hammond, W. C.; Kreemer, C.; Altamimi, Z.

2015-12-01

The long-term stability of ITRF is critical to the most challenging scientific applications such as the slow variation of sea level, and of ice sheet loading in Greenland and Antarctica. In 2010, the National Research Council recommended aiming for stability at the level of 1 mm/decade in the ITRF origin and scale. This requires that the ITRF include many globally-distributed sites with motions that are predictable to within a few mm/decade, with a significant number of sites having collocated stations of multiple techniques. Quantifying the stability of ITRF stations can be useful to understand stability of ITRF parameters, and to help the selection and weighting of ITRF stations. Here we apply a new suite of techniques for an independent assessment of ITRF site velocities. Our "GPS Imaging" suite is founded on the principle that, for the case of large numbers of data, the trend can be estimated objectively, automatically, robustly, and accurately by applying non-parametric techniques, which use quantile statistics (e.g., the median). At the foundation of GPS Imaging is the estimator "MIDAS" (Median Interannual Difference Adjusted for Skewness). MIDAS estimates the velocity with a realistic error bar based on sub-sampling the coordinate time series. MIDAS is robust to step discontinuities, outliers, seasonality, and heteroscedasticity. Common-mode noise filters enhance regional- to continental-scale precision in MIDAS estimates, just as they do for standard estimation techniques. Secondly, in regions where there is sufficient spatial sampling, GPS Imaging uses MIDAS velocity estimates to generate a regionally-representative velocity map. For this we apply a median spatial filter to despeckle the maps. We use GPS Imaging to address two questions: (1) How well do the ITRF site velocities derived by parametric estimation agree with non-parametric techniques? (2) Are ITRF site velocities regionally representative? These questions aim to get a handle on (1) the accuracy of ITRF site velocities as a function of characteristics of contributing station data, such as number of step parameters and total time span; and (2) evidence of local processes affecting site velocity, which may impact site stability. Such quantification can be used to rank stations in terms the risk that they may pose to the stability of ITRF.

A simple parametric model observer for quality assurance in computer tomography

NASA Astrophysics Data System (ADS)

Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.

2018-04-01

Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Using Spatial Correlations of SPDC Sources for Increasing the Signal to Noise Ratio in Images

NASA Astrophysics Data System (ADS)

Ruíz, A. I.; Caudillo, R.; Velázquez, V. M.; Barrios, E.

2017-05-01

We experimentally show that, by using spatial correlations of photon pairs produced by Spontaneous Parametric Down-Conversion, it is possible to increase the Signal to Noise Ratio in images of objects illuminated with those photons; in comparison, objects illuminated with light from a laser present a minor ratio. Our simple experimental set-up was capable to produce an average improvement in signal to noise ratio of 11dB of Parametric Down-Converted light over laser light. This simple method can be easily implemented for obtaining high contrast images of faint objects and for transmitting information with low noise.

Topics in the two-dimensional sampling and reconstruction of images. [in remote sensing

NASA Technical Reports Server (NTRS)

Schowengerdt, R.; Gray, S.; Park, S. K.

1984-01-01

Mathematical analysis of image sampling and interpolative reconstruction is summarized and extended to two dimensions for application to data acquired from satellite sensors such as the Thematic mapper and SPOT. It is shown that sample-scene phase influences the reconstruction of sampled images, adds a considerable blur to the average system point spread function, and decreases the average system modulation transfer function. It is also determined that the parametric bicubic interpolator with alpha = -0.5 is more radiometrically accurate than the conventional bicubic interpolator with alpha = -1, and this at no additional cost. Finally, the parametric bicubic interpolator is found to be suitable for adaptive implementation by relating the alpha parameter to the local frequency content of an image.

Vectoring of parallel synthetic jets: A parametric study

NASA Astrophysics Data System (ADS)

Berk, Tim; Gomit, Guillaume; Ganapathisubramani, Bharathram

2016-11-01

The vectoring of a pair of parallel synthetic jets can be described using five dimensionless parameters: the aspect ratio of the slots, the Strouhal number, the Reynolds number, the phase difference between the jets and the spacing between the slots. In the present study, the influence of the latter four on the vectoring behaviour of the jets is examined experimentally using particle image velocimetry. Time-averaged velocity maps are used to study the variations in vectoring behaviour for a parametric sweep of each of the four parameters independently. A topological map is constructed for the full four-dimensional parameter space. The vectoring behaviour is described both qualitatively and quantitatively. A vectoring mechanism is proposed, based on measured vortex positions. We acknowledge the financial support from the European Research Council (ERC Grant Agreement No. 277472).

Frequency-agile THz-wave generation and detection system using nonlinear frequency conversion at room temperature.

PubMed

Guo, Ruixiang; Ikar'i, Tomofumi; Zhang, Jun; Minamide, Hiroaki; Ito, Hiromasa

2010-08-02

A surface-emitting THz parametric oscillator is set up to generate a narrow-linewidth, nanosecond pulsed THz-wave radiation. The THz-wave radiation is coherently detected using the frequency up-conversion in MgO: LiNbO(3) crystal. Fast frequency tuning and automatic achromatic THz-wave detection are achieved through a special optical design, including a variable-angle mirror and 1:1 telescope devices in the pump and THz-wave beams. We demonstrate a frequency-agile THz-wave parametric generation and THz-wave coherent detection system. This system can be used as a frequency-domain THz-wave spectrometer operated at room-temperature, and there are a high possible to develop into a real-time two-dimensional THz spectral imaging system.

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Patterns of postictal cerebral perfusion in idiopathic generalized epilepsy: a multi-delay multi-parametric arterial spin labelling perfusion MRI study.

PubMed

Chen, Guangxiang; Lei, Du; Ren, Jiechuan; Zuo, Panli; Suo, Xueling; Wang, Danny J J; Wang, Meiyun; Zhou, Dong; Gong, Qiyong

2016-07-04

The cerebral haemodynamic status of idiopathic generalized epilepsy (IGE) is a very complicated process. Little attention has been paid to cerebral blood flow (CBF) alterations in IGE detected by arterial spin labelling (ASL) perfusion magnetic resonance imaging (MRI). However, the selection of an optimal delay time is difficult for single-delay ASL. Multi-delay multi-parametric ASL perfusion MRI overcomes the limitations of single-delay ASL. We applied multi-delay multi-parametric ASL perfusion MRI to investigate the patterns of postictal cerebral perfusion in IGE patients with absence seizures. A total of 21 IGE patients with absence seizures and 24 healthy control subjects were enrolled. IGE patients exhibited prolonged arterial transit time (ATT) in the left superior temporal gyrus. The mean CBF of IGE patients was significantly increased in the left middle temporal gyrus, left parahippocampal gyrus and left fusiform gyrus. Prolonged ATT in the left superior temporal gyrus was negatively correlated with the age at onset in IGE patients. This study demonstrated that cortical dysfunction in the temporal lobe and fusiform gyrus may be related to epileptic activity in IGE patients with absence seizures. This information can play an important role in elucidating the pathophysiological mechanism of IGE from a cerebral haemodynamic perspective.

Sensitivity enhancement in swept-source optical coherence tomography by parametric balanced detector and amplifier

PubMed Central

Kang, Jiqiang; Wei, Xiaoming; Li, Bowen; Wang, Xie; Yu, Luoqin; Tan, Sisi; Jinata, Chandra; Wong, Kenneth K. Y.

2016-01-01

We proposed a sensitivity enhancement method of the interference-based signal detection approach and applied it on a swept-source optical coherence tomography (SS-OCT) system through all-fiber optical parametric amplifier (FOPA) and parametric balanced detector (BD). The parametric BD was realized by combining the signal and phase conjugated idler band that was newly-generated through FOPA, and specifically by superimposing these two bands at a photodetector. The sensitivity enhancement by FOPA and parametric BD in SS-OCT were demonstrated experimentally. The results show that SS-OCT with FOPA and SS-OCT with parametric BD can provide more than 9 dB and 12 dB sensitivity improvement, respectively, when compared with the conventional SS-OCT in a spectral bandwidth spanning over 76 nm. To further verify and elaborate their sensitivity enhancement, a bio-sample imaging experiment was conducted on loach eyes by conventional SS-OCT setup, SS-OCT with FOPA and parametric BD at different illumination power levels. All these results proved that using FOPA and parametric BD could improve the sensitivity significantly in SS-OCT systems. PMID:27446655

Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

NASA Astrophysics Data System (ADS)

Floberg, J. M.; Holden, J. E.

2013-02-01

We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

Computation of the intensities of parametric holographic scattering patterns in photorefractive crystals.

PubMed

Schwalenberg, Simon

2005-06-01

The present work represents a first attempt to perform computations of output intensity distributions for different parametric holographic scattering patterns. Based on the model for parametric four-wave mixing processes in photorefractive crystals and taking into account realistic material properties, we present computed images of selected scattering patterns. We compare these calculated light distributions to the corresponding experimental observations. Our analysis is especially devoted to dark scattering patterns as they make high demands on the underlying model.

Parametric amplification and bidirectional invisibility in PT -symmetric time-Floquet systems

NASA Astrophysics Data System (ADS)

Koutserimpas, Theodoros T.; Alù, Andrea; Fleury, Romain

2018-01-01

Parity-time (PT )-symmetric wave devices, which exploit balanced interactions between material gain and loss, exhibit extraordinary properties, including lasing and flux-conserving scattering processes. In a seemingly different research field, periodically driven systems, also known as time-Floquet systems, have been widely studied as a relevant platform for reconfigurable active wave control and manipulation. In this article, we explore the connection between PT -symmetry and parametric time-Floquet systems. Instead of relying on material gain, we use parametric amplification by considering a time-periodic modulation of the refractive index at a frequency equal to twice the incident signal frequency. We show that the scattering from a simple parametric slab, whose dynamics follows the Mathieu equation, can be described by a PT -symmetric scattering matrix, whose PT -breaking threshold corresponds to the Mathieu instability threshold. By combining different parametric slabs modulated out of phase, we create PT -symmetric time-Floquet systems that feature exceptional scattering properties, such as coherent perfect absorption (CPA)-laser operation and bidirectional invisibility. These bidirectional properties, rare for regular PT -symmetric systems, are related to a compensation of parametric amplification due to multiple scattering between two parametric systems modulated with a phase difference.

Digital double random amplitude image encryption method based on the symmetry property of the parametric discrete Fourier transform

NASA Astrophysics Data System (ADS)

Bekkouche, Toufik; Bouguezel, Saad

2018-03-01

We propose a real-to-real image encryption method. It is a double random amplitude encryption method based on the parametric discrete Fourier transform coupled with chaotic maps to perform the scrambling. The main idea behind this method is the introduction of a complex-to-real conversion by exploiting the inherent symmetry property of the transform in the case of real-valued sequences. This conversion allows the encrypted image to be real-valued instead of being a complex-valued image as in all existing double random phase encryption methods. The advantage is to store or transmit only one image instead of two images (real and imaginary parts). Computer simulation results and comparisons with the existing double random amplitude encryption methods are provided for peak signal-to-noise ratio, correlation coefficient, histogram analysis, and key sensitivity.

Application of artificial neural network to fMRI regression analysis.

PubMed

Misaki, Masaya; Miyauchi, Satoru

2006-01-15

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Research on High-Intensity Picosecond Pump Laser in Short Pulse Optical Parametric Amplification

NASA Astrophysics Data System (ADS)

Pan, Xue; Peng, Yu-Jie; Wang, Jiang-Feng; Lu, Xing-Hua; Ouyang, Xiao-Ping; Chen, Jia-Lin; Jiang, You-En; Fan, Wei; Li, Xue-Chun

2013-01-01

A 527 nm pump laser generating 1.7 mJ energy with peak power of more than 0.12 GW is demonstrated. The theoretical simulation result shows that it has 106 gain in the picosecond-pump optical parametric chirped pulse amplification when the pump laser peak power is 0.1 GW and the intensity is more than 5 GW/cm2, and that it can limit the parametric fluorescence in the picosecond time scale of pump duration. The pump laser system adopts a master-oscillator power amplifier, which integrates a more than 30 pJ fiber-based oscillator with a 150 μJ regenerative amplifier and a relay-imaged four-pass diode-pump Nd glass amplifier to generate a 1 Hz top hat spatial beam and about 14 ps temporal Guassian pulse with <2% pulse-to-pulse energy stability. The output energy of the power amplifier is limited to 4 mJ for B-integral concern, and the frequency doubling efficiency can reach 65% with input intensity 10 GW/cm2.

Quantitative myocardial blood flow imaging with integrated time-of-flight PET-MR.

PubMed

Kero, Tanja; Nordström, Jonny; Harms, Hendrik J; Sörensen, Jens; Ahlström, Håkan; Lubberink, Mark

2017-12-01

The use of integrated PET-MR offers new opportunities for comprehensive assessment of cardiac morphology and function. However, little is known on the quantitative accuracy of cardiac PET imaging with integrated time-of-flight PET-MR. The aim of the present work was to validate the GE Signa PET-MR scanner for quantitative cardiac PET perfusion imaging. Eleven patients (nine male; mean age 59 years; range 46-74 years) with known or suspected coronary artery disease underwent 15 O-water PET scans at rest and during adenosine-induced hyperaemia on a GE Discovery ST PET-CT and a GE Signa PET-MR scanner. PET-MR images were reconstructed using settings recommended by the manufacturer, including time-of-flight (TOF). Data were analysed semi-automatically using Cardiac VUer software, resulting in both parametric myocardial blood flow (MBF) images and segment-based MBF values. Correlation and agreement between PET-CT-based and PET-MR-based MBF values for all three coronary artery territories were assessed using regression analysis and intra-class correlation coefficients (ICC). In addition to the cardiac PET-MR reconstruction protocol as recommended by the manufacturer, comparisons were made using a PET-CT resolution-matched reconstruction protocol both without and with TOF to assess the effect of time-of-flight and reconstruction parameters on quantitative MBF values. Stress MBF data from one patient was excluded due to movement during the PET-CT scanning. Mean MBF values at rest and stress were (0.92 ± 0.12) and (2.74 ± 1.37) mL/g/min for PET-CT and (0.90 ± 0.23) and (2.65 ± 1.15) mL/g/min for PET-MR (p = 0.33 and p = 0.74). ICC between PET-CT-based and PET-MR-based regional MBF was 0.98. Image quality was improved with PET-MR as compared to PET-CT. ICC between PET-MR-based regional MBF with and without TOF and using different filter and reconstruction settings was 1.00. PET-MR-based MBF values correlated well with PET-CT-based MBF values and the parametric PET-MR images were excellent. TOF and reconstruction settings had little impact on MBF values.

Dissecting hemisphere-specific contributions to visual spatial imagery using parametric brain mapping.

PubMed

Bien, Nina; Sack, Alexander T

2014-07-01

In the current study we aimed to empirically test previously proposed accounts of a division of labour between the left and right posterior parietal cortices during visuospatial mental imagery. The representation of mental images in the brain has been a topic of debate for several decades. Although the posterior parietal cortex is involved bilaterally, previous studies have postulated that hemispheric specialisation might result in a division of labour between the left and right parietal cortices. In the current fMRI study, we used an elaborated version of a behaviourally-controlled spatial imagery paradigm, the mental clock task, which involves mental image generation and a subsequent spatial comparison between two angles. By systematically varying the difference between the two angles that are mentally compared, we induced a symbolic distance effect: smaller differences between the two angles result in higher task difficulty. We employed parametrically weighed brain imaging to reveal brain areas showing a graded activation pattern in accordance with the induced distance effect. The parametric difficulty manipulation influenced behavioural data and brain activation patterns in a similar matter. Moreover, since this difficulty manipulation only starts to play a role from the angle comparison phase onwards, it allows for a top-down dissociation between the initial mental image formation, and the subsequent angle comparison phase of the spatial imagery task. Employing parametrically weighed fMRI analysis enabled us to top-down disentangle brain activation related to mental image formation, and activation reflecting spatial angle comparison. The results provide first empirical evidence for the repeatedly proposed division of labour between the left and right posterior parietal cortices during spatial imagery. Copyright © 2014 Elsevier Inc. All rights reserved.

Real-time terahertz wave imaging by nonlinear optical frequency up-conversion in a 4-dimethylamino-N'-methyl-4'-stilbazolium tosylate crystal

NASA Astrophysics Data System (ADS)

Fan, Shuzhen; Qi, Feng; Notake, Takashi; Nawata, Kouji; Matsukawa, Takeshi; Takida, Yuma; Minamide, Hiroaki

2014-03-01

Real-time terahertz (THz) wave imaging has wide applications in areas such as security, industry, biology, medicine, pharmacy, and arts. In this letter, we report on real-time room-temperature THz imaging by nonlinear optical frequency up-conversion in organic 4-dimethylamino-N'-methyl-4'-stilbazolium tosylate crystal. The active projection-imaging system consisted of (1) THz wave generation, (2) THz-near-infrared hybrid optics, (3) THz wave up-conversion, and (4) an InGaAs camera working at 60 frames per second. The pumping laser system consisted of two optical parametric oscillators pumped by a nano-second frequency-doubled Nd:YAG laser. THz-wave images of handmade samples at 19.3 THz were taken, and videos of a sample moving and a ruler stuck with a black polyethylene film moving were supplied online to show real-time ability. Thanks to the high speed and high responsivity of this technology, real-time THz imaging with a higher signal-to-noise ratio than a commercially available THz micro-bolometer camera was proven to be feasible. By changing the phase-matching condition, i.e., by changing the wavelength of the pumping laser, we suggest THz imaging with a narrow THz frequency band of interest in a wide range from approximately 2 to 30 THz is possible.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Yamashita, M.; Ogawa, Y.; Otani, C.; Kawase, K.

2005-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO 3 or MgO-doped LiNbO 3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a TPO, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which illegal, while one is an over-the-counter drug.

In vivo multiphoton imaging of a diverse array of fluorophores to investigate deep neurovascular structure

PubMed Central

Miller, David R.; Hassan, Ahmed M.; Jarrett, Jeremy W.; Medina, Flor A.; Perillo, Evan P.; Hagan, Kristen; Shams Kazmi, S. M.; Clark, Taylor A.; Sullender, Colin T.; Jones, Theresa A.; Zemelman, Boris V.; Dunn, Andrew K.

2017-01-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. By combining the high repetition rate (511 kHz) and high pulse energy (400 nJ) of our amplifier laser system, we demonstrate imaging of vasculature labeled with Texas Red and Indocyanine Green, and neurons expressing tdTomato and yellow fluorescent protein. We measure the blood flow speed of a single capillary at a depth of 1.2 mm, and image vasculature to a depth of 1.53 mm with fine axial steps (5 μm) and reasonable acquisition times. The high image quality enabled analysis of vascular morphology at depths to 1.45 mm. PMID:28717582

Brain segmentation and the generation of cortical surfaces

NASA Technical Reports Server (NTRS)

Joshi, M.; Cui, J.; Doolittle, K.; Joshi, S.; Van Essen, D.; Wang, L.; Miller, M. I.

1999-01-01

This paper describes methods for white matter segmentation in brain images and the generation of cortical surfaces from the segmentations. We have developed a system that allows a user to start with a brain volume, obtained by modalities such as MRI or cryosection, and constructs a complete digital representation of the cortical surface. The methodology consists of three basic components: local parametric modeling and Bayesian segmentation; surface generation and local quadratic coordinate fitting; and surface editing. Segmentations are computed by parametrically fitting known density functions to the histogram of the image using the expectation maximization algorithm [DLR77]. The parametric fits are obtained locally rather than globally over the whole volume to overcome local variations in gray levels. To represent the boundary of the gray and white matter we use triangulated meshes generated using isosurface generation algorithms [GH95]. A complete system of local parametric quadratic charts [JWM+95] is superimposed on the triangulated graph to facilitate smoothing and geodesic curve tracking. Algorithms for surface editing include extraction of the largest closed surface. Results for several macaque brains are presented comparing automated and hand surface generation. Copyright 1999 Academic Press.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

Entropic Imaging of Cataract Lens: An In Vitro Study

PubMed Central

Shung, K. Kirk; Tsui, Po-Hsiang; Fang, Jui; Ma, Hsiang-Yang; Wu, Shuicai; Lin, Chung-Chih

2014-01-01

Phacoemulsification is a common surgical method for treating advanced cataracts. Determining the optimal phacoemulsification energy depends on the hardness of the lens involved. Previous studies have shown that it is possible to evaluate lens hardness via ultrasound parametric imaging based on statistical models that require data to follow a specific distribution. To make the method more system-adaptive, nonmodel-based imaging approach may be necessary in the visualization of lens hardness. This study investigated the feasibility of applying an information theory derived parameter – Shannon entropy from ultrasound backscatter to quantify lens hardness. To determine the physical significance of entropy, we performed computer simulations to investigate the relationship between the signal-to-noise ratio (SNR) based on the Rayleigh distribution and Shannon entropy. Young's modulus was measured in porcine lenses, in which cataracts had been artificially induced by the immersion in formalin solution in vitro. A 35-MHz ultrasound transducer was used to scan the cataract lenses for entropy imaging. The results showed that the entropy is 4.8 when the backscatter data form a Rayleigh distribution corresponding to an SNR of 1.91. The Young's modulus of the lens increased from approximately 8 to 100 kPa when we increased the immersion time from 40 to 160 min (correlation coefficient r = 0.99). Furthermore, the results indicated that entropy imaging seemed to facilitate visualizing different degrees of lens hardening. The mean entropy value increased from 2.7 to 4.0 as the Young's modulus increased from 8 to 100 kPa (r = 0.85), suggesting that entropy imaging may have greater potential than that of conventional statistical parametric imaging in determining the optimal energy to apply during phacoemulsification. PMID:24760103

Parametric approaches to micro-scale characterization of tissue volumes in vivo and ex vivo: Imaging microvasculature, attenuation, birefringence, and stiffness (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sampson, David D.; Chin, Lixin; Gong, Peijun; Wijesinghe, Philip; Es'haghian, Shaghayegh; Allen, Wesley M.; Klyen, Blake R.; Kirk, Rodney W.; Kennedy, Brendan F.; McLaughlin, Robert A.

2016-03-01

INVITED TALK Advances in imaging tissue microstructure in living subjects, or in freshly excised tissue with minimum preparation and processing, are important for future diagnosis and surgical guidance in the clinical setting, particularly for application to cancer. Whilst microscopy methods continue to advance on the cellular scale and medical imaging is well established on the scale of the whole tumor or organ, it is attractive to consider imaging the tumor environment on the micro-scale, between that of cells and whole tissues. Such a scenario is ideally suited to optical coherence tomography (OCT), with the twin attractions of requiring little or no tissue preparation, and in vivo capability. OCT's intrinsic scattering contrast reveals many morphological features of tumors, but is frequently ineffective in revealing other important aspects, such as microvasculature, or in reliably distinguishing tumor from uninvolved stroma. To address these shortcomings, we are developing several advances on the basic OCT approach. We are exploring speckle fluctuations to image tissue microvasculature and we have been developing several parametric approaches to tissue micro-scale characterization. Our approaches extract, from a three-dimensional OCT data set, a two-dimensional image of an optical parameter, such as attenuation or birefringence, or a mechanical parameter, such as stiffness, that aids in characterizing the tissue. This latter method, termed optical coherence elastography, parallels developments in ultrasound and magnetic resonance imaging. Parametric imaging of birefringence and of stiffness both show promise in addressing the important issue of differentiating cancer from uninvolved stroma in breast tissue.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

The use of algorithmic behavioural transfer functions in parametric EO system performance models

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.

2015-10-01

The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach and architecture are described in detail, and example results based on a practical application are then given which illustrate the performance benefits. Finally, conclusions are drawn and comments given regarding the benefits and uses of the new approach.

Towards an acoustic model-based poroelastic imaging method: II. experimental investigation.

PubMed

Berry, Gearóid P; Bamber, Jeffrey C; Miller, Naomi R; Barbone, Paul E; Bush, Nigel L; Armstrong, Cecil G

2006-12-01

Soft biological tissue contains mobile fluid. The volume fraction of this fluid and the ease with which it may be displaced through the tissue could be of diagnostic significance and may also have consequences for the validity with which strain images can be interpreted according to the traditional idealizations of elastography. In a previous paper, under the assumption of frictionless boundary conditions, the spatio-temporal behavior of the strain field inside a compressed cylindrical poroelastic sample was predicted (Berry et al. 2006). In this current paper, experimental evidence is provided to confirm these predictions. Finite element modeling was first used to extend the previous predictions to allow for the existence of contact friction between the sample and the compressor plates. Elastographic techniques were then applied to image the time-evolution of the strain inside cylindrical samples of tofu (a suitable poroelastic material) during sustained unconfined compression. The observed experimental strain behavior was found to be consistent with the theoretical predictions. In particular, every sample studied confirmed that reduced values of radial strain advance with time from the curved cylindrical surface inwards towards the axis of symmetry. Furthermore, by fitting the predictions of an analytical model to a time sequence of strain images, parametric images of two quantities, each related to one or more of three poroelastic material constants were produced. The two parametric images depicted the Poisson's ratio (nu(s)) of the solid matrix and the product of the aggregate modulus (H(A)) of the solid matrix with the permeability (k) of the solid matrix to the pore fluid. The means of the pixel values in these images, nu(s) = 0.088 (standard deviation 0.023) and H(A)k = 1.449 (standard deviation 0.269) x 10(-7) m(2) s(-1), were in agreement with values derived from previously published data for tofu (Righetti et al. 2005). The results provide the first experimental detection of the fluid-flow-induced characteristic diffusion-like behavior of the strain in a compressed poroelastic material and allow parameters related to the above material constants to be determined. We conclude that it may eventually be possible to use strain data to detect and measure characteristics of diffusely distributed mobile fluid in tissue spaces that are too small to be imaged directly.

Elastic least-squares reverse time migration with velocities and density perturbation

NASA Astrophysics Data System (ADS)

Qu, Yingming; Li, Jinli; Huang, Jianping; Li, Zhenchun

2018-02-01

Elastic least-squares reverse time migration (LSRTM) based on the non-density-perturbation assumption can generate false-migrated interfaces caused by density variations. We perform an elastic LSRTM scheme with density variations for multicomponent seismic data to produce high-quality images in Vp, Vs and ρ components. However, the migrated images may suffer from crosstalk artefacts caused by P- and S-waves coupling in elastic LSRTM no matter what model parametrizations used. We have proposed an elastic LSRTM with density variations method based on wave modes separation to reduce these crosstalk artefacts by using P- and S-wave decoupled elastic velocity-stress equations to derive demigration equations and gradient formulae with respect to Vp, Vs and ρ. Numerical experiments with synthetic data demonstrate the capability and superiority of the proposed method. The imaging results suggest that our method promises imaging results with higher quality and has a faster residual convergence rate. Sensitivity analysis of migration velocity, migration density and stochastic noise verifies the robustness of the proposed method for field data.

Optimizing Nanoscale Quantitative Optical Imaging of Subfield Scattering Targets

PubMed Central

Henn, Mark-Alexander; Barnes, Bryan M.; Zhou, Hui; Sohn, Martin; Silver, Richard M.

2016-01-01

The full 3-D scattered field above finite sets of features has been shown to contain a continuum of spatial frequency information, and with novel optical microscopy techniques and electromagnetic modeling, deep-subwavelength geometrical parameters can be determined. Similarly, by using simulations, scattering geometries and experimental conditions can be established to tailor scattered fields that yield lower parametric uncertainties while decreasing the number of measurements and the area of such finite sets of features. Such optimized conditions are reported through quantitative optical imaging in 193 nm scatterfield microscopy using feature sets up to four times smaller in area than state-of-the-art critical dimension targets. PMID:27805660

Characterization of tissue response to radiofrequency ablation using 3D model-based analysis of interventional MR images

NASA Astrophysics Data System (ADS)

Weinberg, Brent D.; Lazebnik, Roee S.; Breen, Michael S.; Lewin, Jonathan S.; Wilson, David L.

2003-05-01

Using magnetic resonance imaging (MRI), real-time guidance is feasible for radiofrequency (RF) current ablation of pathologic tissue. Lesions have a characteristic two-zone appearance: an inner core (Zone I) surrounded by a hyper-intense rim (Zone II). A better understanding of both the immediate (hyper-acute) and delayed (sub-acute) physiological response of the target tissue will aid development of minimally invasive tumor treatment strategies. We performed in vivo RF ablations in a rabbit thigh model and characterized the tissue response to treatment through contrast enhanced (CE) T1 and T2 weighted MR images at two time points. We measured zonal grayscale changes as well as zone volume changes using a 3D computationally fitted globally deformable parametric model. Comparison over time demonstrated an increase in the volume of both the inner necrotic core (mean 56.5% increase) and outer rim (mean 16.8% increase) of the lesion. Additionally, T2 images of the lesion exhibited contrast greater than or equal to CE T1 (mean 35% improvement). This work establishes a foundation for the clinical use of T2 MR images coupled with a geometric model of the ablation for noninvasive lesion monitoring and characterization.

Extracting 3D Parametric Curves from 2D Images of Helical Objects.

PubMed

Willcocks, Chris G; Jackson, Philip T G; Nelson, Carl J; Obara, Boguslaw

2017-09-01

Helical objects occur in medicine, biology, cosmetics, nanotechnology, and engineering. Extracting a 3D parametric curve from a 2D image of a helical object has many practical applications, in particular being able to extract metrics such as tortuosity, frequency, and pitch. We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. The results show that the extracted 3D curve comes within close Hausdorff distance to the ground truth, and has near identical tortuosity for helical objects with a circular profile. Parameter insensitivity and robustness against high levels of image noise are demonstrated thoroughly and quantitatively.

Stimulated parametric emission microscopy.

PubMed

Isobe, Keisuke; Kataoka, Shogo; Murase, Rena; Watanabe, Wataru; Higashi, Tsunehito; Kawakami, Shigeki; Matsunaga, Sachihiro; Fukui, Kiichi; Itoh, Kazuyoshi

2006-01-23

We propose a novel microscopy technique based on the four-wave mixing (FWM) process that is enhanced by two-photon electronic resonance induced by a pump pulse along with stimulated emission induced by a dump pulse. A Ti:sapphire laser and an optical parametric oscillator are used as light sources for the pump and dump pulses, respectively. We demonstrate that our proposed FWM technique can be used to obtain a one-dimensional image of ethanol-thinned Coumarin 120 solution sandwiched between a hole-slide glass and a cover slip, and a two-dimensional image of a leaf of Camellia sinensis.

Simultaneous single-shot readout of multi-qubit circuits using a traveling-wave parametric amplifier

NASA Astrophysics Data System (ADS)

O'Brien, Kevin

Observing and controlling the state of ever larger quantum systems is critical for advancing quantum computation. Utilizing a Josephson traveling wave parametric amplifier (JTWPA), we demonstrate simultaneous multiplexed single shot readout of 10 transmon qubits in a planar architecture. We employ digital image sideband rejection to eliminate noise at the image frequencies. We quantify crosstalk and infidelity due to simultaneous readout and control of multiple qubits. Based on current amplifier technology, this approach can scale to simultaneous readout of at least 20 qubits. This work was supported by the Army Research Office.

Parametric binary dissection

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.; Crockett, Thomas W.; Nicol, David M.

1993-01-01

Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.

Short pulse generation from a passively mode-locked fiber optical parametric oscillator with optical time-stretch.

PubMed

Qiu, Yi; Wei, Xiaoming; Du, Shuxin; Wong, Kenneth K Y; Tsia, Kevin K; Xu, Yiqing

2018-04-16

We propose a passively mode-locked fiber optical parametric oscillator assisted with optical time-stretch. Thanks to the lately developed optical time-stretch technique, the onset oscillating spectral components can be temporally dispersed across the pump envelope and further compete for the parametric gain with the other parts of onset oscillating sidebands within the pump envelope. By matching the amount of dispersion in optical time-stretch with the pulse width of the quasi-CW pump and oscillating one of the parametric sidebands inside the fiber cavity, we numerically show that the fiber parametric oscillator can be operated in a single pulse regime. By varying the amount of the intracavity dispersion, we further verify that the origin of this single pulse mode-locking regime is due to the optical pulse stretching and compression.

Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Lin, Tong; Cerviño, Laura I.; Tang, Xiaoli; Vasconcelos, Nuno; Jiang, Steve B.

2009-02-01

Accurate lung tumor tracking in real time is a keystone to image-guided radiotherapy of lung cancers. Existing lung tumor tracking approaches can be roughly grouped into three categories: (1) deriving tumor position from external surrogates; (2) tracking implanted fiducial markers fluoroscopically or electromagnetically; (3) fluoroscopically tracking lung tumor without implanted fiducial markers. The first approach suffers from insufficient accuracy, while the second may not be widely accepted due to the risk of pneumothorax. Previous studies in fluoroscopic markerless tracking are mainly based on template matching methods, which may fail when the tumor boundary is unclear in fluoroscopic images. In this paper we propose a novel markerless tumor tracking algorithm, which employs the correlation between the tumor position and surrogate anatomic features in the image. The positions of the surrogate features are not directly tracked; instead, we use principal component analysis of regions of interest containing them to obtain parametric representations of their motion patterns. Then, the tumor position can be predicted from the parametric representations of surrogates through regression. Four regression methods were tested in this study: linear and two-degree polynomial regression, artificial neural network (ANN) and support vector machine (SVM). The experimental results based on fluoroscopic sequences of ten lung cancer patients demonstrate a mean tracking error of 2.1 pixels and a maximum error at a 95% confidence level of 4.6 pixels (pixel size is about 0.5 mm) for the proposed tracking algorithm.

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

Glucose Metabolic Profile by Visual Assessment Combined with Statistical Parametric Mapping Analysis in Pediatric Patients with Epilepsy.

PubMed

Zhu, Yuankai; Feng, Jianhua; Wu, Shuang; Hou, Haifeng; Ji, Jianfeng; Zhang, Kai; Chen, Qing; Chen, Lin; Cheng, Haiying; Gao, Liuyan; Chen, Zexin; Zhang, Hong; Tian, Mei

2017-08-01

PET with 18 F-FDG has been used for presurgical localization of epileptogenic foci; however, in nonsurgical patients, the correlation between cerebral glucose metabolism and clinical severity has not been fully understood. The aim of this study was to evaluate the glucose metabolic profile using 18 F-FDG PET/CT imaging in patients with epilepsy. Methods: One hundred pediatric epilepsy patients who underwent 18 F-FDG PET/CT, MRI, and electroencephalography examinations were included. Fifteen age-matched controls were also included. 18 F-FDG PET images were analyzed by visual assessment combined with statistical parametric mapping (SPM) analysis. The absolute asymmetry index (|AI|) was calculated in patients with regional abnormal glucose metabolism. Results: Visual assessment combined with SPM analysis of 18 F-FDG PET images detected more patients with abnormal glucose metabolism than visual assessment only. The |AI| significantly positively correlated with seizure frequency ( P < 0.01) but negatively correlated with the time since last seizure ( P < 0.01) in patients with abnormal glucose metabolism. The only significant contributing variable to the |AI| was the time since last seizure, in patients both with hypometabolism ( P = 0.001) and with hypermetabolism ( P = 0.005). For patients with either hypometabolism ( P < 0.01) or hypermetabolism ( P = 0.209), higher |AI| values were found in those with drug resistance than with seizure remission. In the post-1-y follow-up PET studies, a significant change of |AI| (%) was found in patients with clinical improvement compared with those with persistence or progression ( P < 0.01). Conclusion: 18 F-FDG PET imaging with visual assessment combined with SPM analysis could provide cerebral glucose metabolic profiles in nonsurgical epilepsy patients. |AI| might be used for evaluation of clinical severity and progress in these patients. Patients with a prolonged period of seizure freedom may have more subtle (or no) metabolic abnormalities on PET. The clinical value of PET might be enhanced by timing the scan closer to clinical seizures. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Brain Signal Variability is Parametrically Modifiable

PubMed Central

Garrett, Douglas D.; McIntosh, Anthony R.; Grady, Cheryl L.

2014-01-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. PMID:23749875

The Frontier Fields lens modelling comparison project

NASA Astrophysics Data System (ADS)

Meneghetti, M.; Natarajan, P.; Coe, D.; Contini, E.; De Lucia, G.; Giocoli, C.; Acebron, A.; Borgani, S.; Bradac, M.; Diego, J. M.; Hoag, A.; Ishigaki, M.; Johnson, T. L.; Jullo, E.; Kawamata, R.; Lam, D.; Limousin, M.; Liesenborgs, J.; Oguri, M.; Sebesta, K.; Sharon, K.; Williams, L. L. R.; Zitrin, A.

2017-12-01

Gravitational lensing by clusters of galaxies offers a powerful probe of their structure and mass distribution. Several research groups have developed techniques independently to achieve this goal. While these methods have all provided remarkably high-precision mass maps, particularly with exquisite imaging data from the Hubble Space Telescope (HST), the reconstructions themselves have never been directly compared. In this paper, we present for the first time a detailed comparison of methodologies for fidelity, accuracy and precision. For this collaborative exercise, the lens modelling community was provided simulated cluster images that mimic the depth and resolution of the ongoing HST Frontier Fields. The results of the submitted reconstructions with the un-blinded true mass profile of these two clusters are presented here. Parametric, free-form and hybrid techniques have been deployed by the participating groups and we detail the strengths and trade-offs in accuracy and systematics that arise for each methodology. We note in conclusion that several properties of the lensing clusters are recovered equally well by most of the lensing techniques compared in this study. For example, the reconstruction of azimuthally averaged density and mass profiles by both parametric and free-form methods matches the input models at the level of ∼10 per cent. Parametric techniques are generally better at recovering the 2D maps of the convergence and of the magnification. For the best-performing algorithms, the accuracy in the magnification estimate is ∼10 per cent at μtrue = 3 and it degrades to ∼30 per cent at μtrue ∼ 10.

A Review of Some Superconducting Technologies for AtLAST: Parametric Amplifiers, Kinetic Inductance Detectors, and On-Chip Spectrometers

NASA Astrophysics Data System (ADS)

Noroozian, Omid

2018-01-01

The current state of the art for some superconducting technologies will be reviewed in the context of a future single-dish submillimeter telescope called AtLAST. The technologies reviews include: 1) Kinetic Inductance Detectors (KIDs), which have now been demonstrated in large-format kilo-pixel arrays with photon background-limited sensitivity suitable for large field of view cameras for wide-field imaging. 2) Parametric amplifiers - specifically the Traveling-Wave Kinetic Inductance (TKIP) amplifier - which has enormous potential to increase sensitivity, bandwidth, and mapping speed of heterodyne receivers, and 3) On-chip spectrometers, which combined with sensitive direct detectors such as KIDs or TESs could be used as Multi-Object Spectrometers on the AtLAST focal plane, and could provide low-medium resolution spectroscopy of 100 objects at a time in each field of view.

Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series.

PubMed

Halliday, David M; Senik, Mohd Harizal; Stevenson, Carl W; Mason, Rob

2016-08-01

The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. However, the validity of using low order AR models for neurophysiological signals has been questioned. A recent article introduced a non-parametric approach to estimate directionality in bivariate data, non-parametric approaches are free from concerns over model validity. We extend the non-parametric framework to include measures of directed conditional independence, using scalar measures that decompose the overall partial correlation coefficient summatively by direction, and a set of functions that decompose the partial coherence summatively by direction. A time domain partial correlation function allows both time and frequency views of the data to be constructed. The conditional independence estimates are conditioned on a single predictor. The framework is applied to simulated cortical neuron networks and mixtures of Gaussian time series data with known interactions. It is applied to experimental data consisting of local field potential recordings from bilateral hippocampus in anaesthetised rats. The framework offers a non-parametric approach to estimation of directed interactions in multivariate neuronal recordings, and increased flexibility in dealing with both spike train and time series data. The framework offers a novel alternative non-parametric approach to estimate directed interactions in multivariate neuronal recordings, and is applicable to spike train and time series data. Copyright © 2016 Elsevier B.V. All rights reserved.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease. PMID:26023913

Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging.

PubMed

Agner, Shannon C; Xu, Jun; Madabhushi, Anant

2013-03-01

Segmentation of breast lesions on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is the first step in lesion diagnosis in a computer-aided diagnosis framework. Because manual segmentation of such lesions is both time consuming and highly susceptible to human error and issues of reproducibility, an automated lesion segmentation method is highly desirable. Traditional automated image segmentation methods such as boundary-based active contour (AC) models require a strong gradient at the lesion boundary. Even when region-based terms are introduced to an AC model, grayscale image intensities often do not allow for clear definition of foreground and background region statistics. Thus, there is a need to find alternative image representations that might provide (1) strong gradients at the margin of the object of interest (OOI); and (2) larger separation between intensity distributions and region statistics for the foreground and background, which are necessary to halt evolution of the AC model upon reaching the border of the OOI. In this paper, the authors introduce a spectral embedding (SE) based AC (SEAC) for lesion segmentation on breast DCE-MRI. SE, a nonlinear dimensionality reduction scheme, is applied to the DCE time series in a voxelwise fashion to reduce several time point images to a single parametric image where every voxel is characterized by the three dominant eigenvectors. This parametric eigenvector image (PrEIm) representation allows for better capture of image region statistics and stronger gradients for use with a hybrid AC model, which is driven by both boundary and region information. They compare SEAC to ACs that employ fuzzy c-means (FCM) and principal component analysis (PCA) as alternative image representations. Segmentation performance was evaluated by boundary and region metrics as well as comparing lesion classification using morphological features from SEAC, PCA+AC, and FCM+AC. On a cohort of 50 breast DCE-MRI studies, PrEIm yielded overall better region and boundary-based statistics compared to the original DCE-MR image, FCM, and PCA based image representations. Additionally, SEAC outperformed a hybrid AC applied to both PCA and FCM image representations. Mean dice similarity coefficient (DSC) for SEAC was significantly better (DSC = 0.74 ± 0.21) than FCM+AC (DSC = 0.50 ± 0.32) and similar to PCA+AC (DSC = 0.73 ± 0.22). Boundary-based metrics of mean absolute difference and Hausdorff distance followed the same trends. Of the automated segmentation methods, breast lesion classification based on morphologic features derived from SEAC segmentation using a support vector machine classifier also performed better (AUC = 0.67 ± 0.05; p < 0.05) than FCM+AC (AUC = 0.50 ± 0.07), and PCA+AC (AUC = 0.49 ± 0.07). In this work, we presented SEAC, an accurate, general purpose AC segmentation tool that could be applied to any imaging domain that employs time series data. SE allows for projection of time series data into a PrEIm representation so that every voxel is characterized by the dominant eigenvectors, capturing the global and local time-intensity curve similarities in the data. This PrEIm allows for the calculation of strong tensor gradients and better region statistics than the original image intensities or alternative image representations such as PCA and FCM. The PrEIm also allows for building a more accurate hybrid AC scheme.

Multiparametric, Longitudinal Optical Coherence Tomography Imaging Reveals Acute Injury and Chronic Recovery in Experimental Ischemic Stroke

PubMed Central

Srinivasan, Vivek J.; Mandeville, Emiri T.; Can, Anil; Blasi, Francesco; Climov, Mihail; Daneshmand, Ali; Lee, Jeong Hyun; Yu, Esther; Radhakrishnan, Harsha; Lo, Eng H.; Sakadžić, Sava; Eikermann-Haerter, Katharina; Ayata, Cenk

2013-01-01

Progress in experimental stroke and translational medicine could be accelerated by high-resolution in vivo imaging of disease progression in the mouse cortex. Here, we introduce optical microscopic methods that monitor brain injury progression using intrinsic optical scattering properties of cortical tissue. A multi-parametric Optical Coherence Tomography (OCT) platform for longitudinal imaging of ischemic stroke in mice, through thinned-skull, reinforced cranial window surgical preparations, is described. In the acute stages, the spatiotemporal interplay between hemodynamics and cell viability, a key determinant of pathogenesis, was imaged. In acute stroke, microscopic biomarkers for eventual infarction, including capillary non-perfusion, cerebral blood flow deficiency, altered cellular scattering, and impaired autoregulation of cerebral blood flow, were quantified and correlated with histology. Additionally, longitudinal microscopy revealed remodeling and flow recovery after one week of chronic stroke. Intrinsic scattering properties serve as reporters of acute cellular and vascular injury and recovery in experimental stroke. Multi-parametric OCT represents a robust in vivo imaging platform to comprehensively investigate these properties. PMID:23940761

Multi-parametric MRI findings of granulomatous prostatitis developing after intravesical bacillus calmette-guérin therapy.

PubMed

Gottlieb, Josh; Princenthal, Robert; Cohen, Martin I

2017-07-01

To evaluate the multi-parametric MRI (mpMRI) findings in patients with biopsy-proven granulomatous prostatitis and prior Bacillus Calmette-Guérin (BCG) exposure. MRI was performed in six patients with pathologically proven granulomatous prostatitis and a prior history of bladder cancer treated with intravesical BCG therapy. Multi-parametric prostate MRI images were recorded on a GE 750W or Philips Achieva 3.0 Tesla MRI scanner with high-resolution, small-field-of-view imaging consisting of axial T2, axial T1, coronal T2, sagittal T2, axial multiple b-value diffusion (multiple values up to 1200 or 1400), and dynamic contrast-enhanced 3D axial T1 with fat suppression sequence. Two different patterns of MR findings were observed. Five of the six patients had a low mean ADC value <1000 (decreased signal on ADC map images) and isointense signal on high-b-value imaging (b = 1200 or 1400), consistent with nonspecific granulomatous prostatitis. The other pattern seen in one of the six patients was decreased signal on the ADC map images with increased signal on the high-b-value sequence, revealing true restricted diffusion indistinguishable from aggressive prostate cancer. This patient had biopsy-confirmed acute BCG prostatitis. Our study suggests that patients with known BCG exposure and PI-RADS v2 scores ≤3, showing similar mpMRI findings as demonstrated, may not require prostate biopsy.

Parametric fMRI of paced motor responses uncovers novel whole-brain imaging biomarkers in spinocerebellar ataxia type 3.

PubMed

Duarte, João Valente; Faustino, Ricardo; Lobo, Mercês; Cunha, Gil; Nunes, César; Ferreira, Carlos; Januário, Cristina; Castelo-Branco, Miguel

2016-10-01

Machado-Joseph Disease, inherited type 3 spinocerebellar ataxia (SCA3), is the most common form worldwide. Neuroimaging and neuropathology have consistently demonstrated cerebellar alterations. Here we aimed to discover whole-brain functional biomarkers, based on parametric performance-level-dependent signals. We assessed 13 patients with early SCA3 and 14 healthy participants. We used a combined parametric behavioral/functional neuroimaging design to investigate disease fingerprints, as a function of performance levels, coupled with structural MRI and voxel-based morphometry. Functional magnetic resonance imaging (fMRI) was designed to parametrically analyze behavior and neural responses to audio-paced bilateral thumb movements at temporal frequencies of 1, 3, and 5 Hz. Our performance-level-based design probing neuronal correlates of motor coordination enabled the discovery that neural activation and behavior show critical loss of parametric modulation specifically in SCA3, associated with frequency-dependent cortico/subcortical activation/deactivation patterns. Cerebellar/cortical rate-dependent dissociation patterns could clearly differentiate between groups irrespective of grey matter loss. Our findings suggest functional reorganization of the motor network and indicate a possible role of fMRI as a tool to monitor disease progression in SCA3. Accordingly, fMRI patterns proved to be potential biomarkers in early SCA3, as tested by receiver operating characteristic analysis of both behavior and neural activation at different frequencies. Discrimination analysis based on BOLD signal in response to the applied parametric finger-tapping task significantly often reached >80% sensitivity and specificity in single regions-of-interest.Functional fingerprints based on cerebellar and cortical BOLD performance dependent signal modulation can thus be combined as diagnostic and/or therapeutic targets in hereditary ataxia. Hum Brain Mapp 37:3656-3668, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging.

PubMed

Gabr, Refaat E; Tefera, Getaneh B; Allen, William J; Pednekar, Amol S; Narayana, Ponnada A

2017-03-01

We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols. GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer. GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast. GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

Acoustic radiation force impulse (ARFI) imaging: Characterizing the mechanical properties of tissues using their transient response to localized force

NASA Astrophysics Data System (ADS)

Nightingale, Kathryn R.; Palmeri, Mark L.; Congdon, Amy N.; Frinkely, Kristin D.; Trahey, Gregg E.

2004-05-01

Acoustic radiation force impulse (ARFI) imaging utilizes brief, high energy, focused acoustic pulses to generate radiation force in tissue, and conventional diagnostic ultrasound methods to detect the resulting tissue displacements in order to image the relative mechanical properties of tissue. The magnitude and spatial extent of the applied force is dependent upon the transmit beam parameters and the tissue attenuation. Forcing volumes are on the order of 5 mm3, pulse durations are less than 1 ms, and tissue displacements are typically several microns. Images of tissue displacement reflect local tissue stiffness, with softer tissues (e.g., fat) displacing farther than stiffer tissues (e.g., muscle). Parametric images of maximum displacement, time to peak displacement, and recovery time provide information about tissue material properties and structure. In both in vivo and ex vivo data, structures shown in matched B-mode images are in good agreement with those shown in ARFI images, with comparable resolution. Potential clinical applications under investigation include soft tissue lesion characterization, assessment of focal atherosclerosis, and imaging of thermal lesion formation during tissue ablation procedures. Results from ongoing studies will be presented. [Work supported by NIH Grant R01 EB002132-03, and the Whitaker Foundation. System support from Siemens Medical Solutions USA, Inc.

The SIR-B science plan

NASA Technical Reports Server (NTRS)

1982-01-01

The Shuttle Imaging Radar-B (SIR-B) will be the third in a series of spaceborne SAR experiments conducted by NASA which began with the 1978 launch of SEASAT and continued with the 1981 launch of SIR-A. Like SEASAT and SIR-A, SIR-B will operate at L-band and will be horizontally polarized. However, SIR-B will allow digitally processed imagery to be acquired at selectable incidence angles between 15 and 60 deg, thereby permitting, for the first time, parametric studies of the effect of illumination geometry on SAR image information extraction. This document presents a science plan for SIR-B and serves as a reference for the types of geoscientific, sensor, and processing experiments which are possible.

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Shishir, Pandya; Chaderjian, Neal; Ahmad, Jsaim; Kwak, Dochan (Technical Monitor)

2001-01-01

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

An independent software system for the analysis of dynamic MR images.

PubMed

Torheim, G; Lombardi, M; Rinck, P A

1997-01-01

A computer system for the manual, semi-automatic, and automatic analysis of dynamic MR images was to be developed on UNIX and personal computer platforms. The system was to offer an integrated and standardized way of performing both image processing and analysis that was independent of the MR unit used. The system consists of modules that are easily adaptable to special needs. Data from MR units or other diagnostic imaging equipment in techniques such as CT, ultrasonography, or nuclear medicine can be processed through the ACR-NEMA/DICOM standard file formats. A full set of functions is available, among them cine-loop visual analysis, and generation of time-intensity curves. Parameters such as cross-correlation coefficients, area under the curve, peak/maximum intensity, wash-in and wash-out slopes, time to peak, and relative signal intensity/contrast enhancement can be calculated. Other parameters can be extracted by fitting functions like the gamma-variate function. Region-of-interest data and parametric values can easily be exported. The system has been successfully tested in animal and patient examinations.

Usefulness of myocardial parametric imaging to evaluate myocardial viability in experimental and in clinical studies.

PubMed

Korosoglou, G; Hansen, A; Bekeredjian, R; Filusch, A; Hardt, S; Wolf, D; Schellberg, D; Katus, H A; Kuecherer, H

2006-03-01

To evaluate whether myocardial parametric imaging (MPI) is superior to visual assessment for the evaluation of myocardial viability. Myocardial contrast echocardiography (MCE) was assessed in 11 pigs before, during, and after left anterior descending coronary artery occlusion and in 32 patients with ischaemic heart disease by using intravenous SonoVue administration. In experimental studies perfusion defect area assessment by MPI was compared with visually guided perfusion defect planimetry. Histological assessment of necrotic tissue was the standard reference. In clinical studies viability was assessed on a segmental level by (1) visual analysis of myocardial opacification; (2) quantitative estimation of myocardial blood flow in regions of interest; and (3) MPI. Functional recovery between three and six months after revascularisation was the standard reference. In experimental studies, compared with visually guided perfusion defect planimetry, planimetric assessment of infarct size by MPI correlated more significantly with histology (r2 = 0.92 versus r2 = 0.56) and had a lower intraobserver variability (4% v 15%, p < 0.05). In clinical studies, MPI had higher specificity (66% v 43%, p < 0.05) than visual MCE and good accuracy (81%) for viability detection. It was less time consuming (3.4 (1.6) v 9.2 (2.4) minutes per image, p < 0.05) than quantitative blood flow estimation by regions of interest and increased the agreement between observers interpreting myocardial perfusion (kappa = 0.87 v kappa = 0.75, p < 0.05). MPI is useful for the evaluation of myocardial viability both in animals and in patients. It is less time consuming than quantification analysis by regions of interest and less observer dependent than visual analysis. Thus, strategies incorporating this technique may be valuable for the evaluation of myocardial viability in clinical routine.

Polarization switch of four-wave mixing in a lawtunable fiber optical parametric oscillator.

PubMed

Yang, Kangwen; Ye, Pengbo; Zheng, Shikai; Jiang, Jieshi; Huang, Kun; Hao, Qiang; Zeng, Heping

2018-02-05

We reported the simultaneous generation and selective manipulation of scalar and cross-phase modulation instabilities in a fiber optical parametric oscillator. Numerical and experimental results show independent control of parametric gain by changing the input pump polarization state. The resonant cavity enables power enhancement of 45 dB for the spontaneous sidebands, generating laser pulses tunable from 783 to 791 nm and 896 to 1005 nm due to the combination of four-wave mixing, cascaded Raman scattering and other nonlinear effects. This gain controlled, wavelength tunable, fiber-based laser source may find applications in the fields of nonlinear biomedical imaging and stimulated Raman spectroscopy.

Effect of MRI acoustic noise on cerebral fludeoxyglucose uptake in simultaneous MR-PET imaging.

PubMed

Chonde, Daniel B; Abolmaali, Nasreddin; Arabasz, Grae; Guimaraes, Alexander R; Catana, Ciprian

2013-05-01

Integrated scanners capable of simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) data acquisition are now available for human use. Although the scanners' manufacturers have made substantial efforts to understand and minimize the mutual electromagnetic interference between the 2 modalities, the potential physiological inference has not been evaluated. In this study, we have studied the influence of the acoustic noise produced by the magnetic resonance (MR) gradients on brain fludeoxyglucose (FDG) uptake in the Siemens MR-BrainPET prototype. Although particular attention was paid to the primary auditory cortex (PAC), a brain-wide analysis was also performed. The effects of the MR on the PET count rate and image quantification were first investigated in phantoms. Next, 10 healthy volunteers underwent 2 simultaneous FDG-PET/MR scans in the supine position with the FDG injection occurring inside the MR-BrainPET, alternating between a "quiet" (control) environment in which no MR sequences were run during the FDG uptake phase (the first 40 minutes after radiotracer administration) and a "noisy" (test) environment in which MR sequences were run for the entire time. Cortical and subcortical regions of interest were derived from the high-resolution morphological MR data using FreeSurfer. The changes in the FDG uptake in the FreeSurfer-derived regions of interest between the 2 conditions were analyzed from parametric and static PET images, and on a voxel-by-voxel basis using SPM8 and FreeSurfer. Only minimal to no electromagnetic interference was observed for most of the MR sequences tested, with a maximum drop in count rate of 1.5% and a maximum change in the measured activity of 1.1% in the corresponding images. The region of interest-based analysis showed statistically significant increases in the right PAC in both the parametric (9.13% [4.73%]) and static (4.18% [2.87%]) images. The SPM8 analysis showed no statistically significant clusters in any images when a P < 0.05 (corrected) was used; however, a P < 0.001 (uncorrected) resolved bilateral statistically significant clusters of increased FDG uptake in the area of the PAC for the parametric image (left, 8.37% [1.55%]; right, 8.20% [1.17%]) but only unilateral increase in the static image (left, 8.68% [3.89%]). Although the operation of the BrainPET prototype is virtually unaffected by the MR scanner, the acoustic noise produced by the MR gradients causes a focal increase in the FDG uptake in the PAC, which could affect the interpretation of pathological (or brain-activation-related) changes in the FDG uptake in this region if the expected effects are of comparable amplitude.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

A Simulation Model Of A Picture Archival And Communication System

NASA Astrophysics Data System (ADS)

D'Silva, Vijay; Perros, Harry; Stockbridge, Chris

1988-06-01

A PACS architecture was simulated to quantify its performance. The model consisted of reading stations, acquisition nodes, communication links, a database management system, and a storage system consisting of magnetic and optical disks. Two levels of storage were simulated, a high-speed magnetic disk system for short term storage, and optical disk jukeboxes for long term storage. The communications link was a single bus via which image data were requested and delivered. Real input data to the simulation model were obtained from surveys of radiology procedures (Bowman Gray School of Medicine). From these the following inputs were calculated: - the size of short term storage necessary - the amount of long term storage required - the frequency of access of each store, and - the distribution of the number of films requested per diagnosis. The performance measures obtained were - the mean retrieval time for an image, - mean queue lengths, and - the utilization of each device. Parametric analysis was done for - the bus speed, - the packet size for the communications link, - the record size on the magnetic disk, - compression ratio, - influx of new images, - DBMS time, and - diagnosis think times. Plots give the optimum values for those values of input speed and device performance which are sufficient to achieve subsecond image retrieval times

A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data

NASA Astrophysics Data System (ADS)

Anees, Asim; Aryal, Jagannath; O'Reilly, Małgorzata M.; Gale, Timothy J.; Wardlaw, Tim

2016-12-01

A robust non-parametric framework, based on multiple Radial Basic Function (RBF) kernels, is proposed in this study, for detecting land/forest cover changes using Landsat 7 ETM+ images. One of the widely used frameworks is to find change vectors (difference image) and use a supervised classifier to differentiate between change and no-change. The Bayesian Classifiers e.g. Maximum Likelihood Classifier (MLC), Naive Bayes (NB), are widely used probabilistic classifiers which assume parametric models, e.g. Gaussian function, for the class conditional distributions. However, their performance can be limited if the data set deviates from the assumed model. The proposed framework exploits the useful properties of Least Squares Probabilistic Classifier (LSPC) formulation i.e. non-parametric and probabilistic nature, to model class posterior probabilities of the difference image using a linear combination of a large number of Gaussian kernels. To this end, a simple technique, based on 10-fold cross-validation is also proposed for tuning model parameters automatically instead of selecting a (possibly) suboptimal combination from pre-specified lists of values. The proposed framework has been tested and compared with Support Vector Machine (SVM) and NB for detection of defoliation, caused by leaf beetles (Paropsisterna spp.) in Eucalyptus nitens and Eucalyptus globulus plantations of two test areas, in Tasmania, Australia, using raw bands and band combination indices of Landsat 7 ETM+. It was observed that due to multi-kernel non-parametric formulation and probabilistic nature, the LSPC outperforms parametric NB with Gaussian assumption in change detection framework, with Overall Accuracy (OA) ranging from 93.6% (κ = 0.87) to 97.4% (κ = 0.94) against 85.3% (κ = 0.69) to 93.4% (κ = 0.85), and is more robust to changing data distributions. Its performance was comparable to SVM, with added advantages of being probabilistic and capable of handling multi-class problems naturally with its original formulation.

A Non-Parametric Approach for the Activation Detection of Block Design fMRI Simulated Data Using Self-Organizing Maps and Support Vector Machine.

PubMed

Bahrami, Sheyda; Shamsi, Mousa

2017-01-01

Functional magnetic resonance imaging (fMRI) is a popular method to probe the functional organization of the brain using hemodynamic responses. In this method, volume images of the entire brain are obtained with a very good spatial resolution and low temporal resolution. However, they always suffer from high dimensionality in the face of classification algorithms. In this work, we combine a support vector machine (SVM) with a self-organizing map (SOM) for having a feature-based classification by using SVM. Then, a linear kernel SVM is used for detecting the active areas. Here, we use SOM for feature extracting and labeling the datasets. SOM has two major advances: (i) it reduces dimension of data sets for having less computational complexity and (ii) it is useful for identifying brain regions with small onset differences in hemodynamic responses. Our non-parametric model is compared with parametric and non-parametric methods. We use simulated fMRI data sets and block design inputs in this paper and consider the contrast to noise ratio (CNR) value equal to 0.6 for simulated datasets. fMRI simulated dataset has contrast 1-4% in active areas. The accuracy of our proposed method is 93.63% and the error rate is 6.37%.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging.

PubMed

Ahmad, R; Ding, Y; Simonetti, O P

2015-05-01

In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications.

The degenerate parametric oscillator and Ince's equation

NASA Astrophysics Data System (ADS)

Cordero-Soto, Ricardo; Suslov, Sergei K.

2011-01-01

We construct Green's function for the quantum degenerate parametric oscillator in the coordinate representation in terms of standard solutions of Ince's equation in a framework of a general approach to variable quadratic Hamiltonians. Exact time-dependent wavefunctions and their connections with dynamical invariants and SU(1, 1) group are also discussed. An extension to the degenerate parametric oscillator with time-dependent amplitude and phase is also mentioned.

Tracer Kinetic Analysis of (S)-¹⁸F-THK5117 as a PET Tracer for Assessing Tau Pathology.

PubMed

Jonasson, My; Wall, Anders; Chiotis, Konstantinos; Saint-Aubert, Laure; Wilking, Helena; Sprycha, Margareta; Borg, Beatrice; Thibblin, Alf; Eriksson, Jonas; Sörensen, Jens; Antoni, Gunnar; Nordberg, Agneta; Lubberink, Mark

2016-04-01

Because a correlation between tau pathology and the clinical symptoms of Alzheimer disease (AD) has been hypothesized, there is increasing interest in developing PET tracers that bind specifically to tau protein. The aim of this study was to evaluate tracer kinetic models for quantitative analysis and generation of parametric images for the novel tau ligand (S)-(18)F-THK5117. Nine subjects (5 with AD, 4 with mild cognitive impairment) received a 90-min dynamic (S)-(18)F-THK5117 PET scan. Arterial blood was sampled for measurement of blood radioactivity and metabolite analysis. Volume-of-interest (VOI)-based analysis was performed using plasma-input models; single-tissue and 2-tissue (2TCM) compartment models and plasma-input Logan and reference tissue models; and simplified reference tissue model (SRTM), reference Logan, and SUV ratio (SUVr). Cerebellum gray matter was used as the reference region. Voxel-level analysis was performed using basis function implementations of SRTM, reference Logan, and SUVr. Regionally averaged voxel values were compared with VOI-based values from the optimal reference tissue model, and simulations were made to assess accuracy and precision. In addition to 90 min, initial 40- and 60-min data were analyzed. Plasma-input Logan distribution volume ratio (DVR)-1 values agreed well with 2TCM DVR-1 values (R(2)= 0.99, slope = 0.96). SRTM binding potential (BP(ND)) and reference Logan DVR-1 values were highly correlated with plasma-input Logan DVR-1 (R(2)= 1.00, slope ≈ 1.00) whereas SUVr(70-90)-1 values correlated less well and overestimated binding. Agreement between parametric methods and SRTM was best for reference Logan (R(2)= 0.99, slope = 1.03). SUVr(70-90)-1 values were almost 3 times higher than BP(ND) values in white matter and 1.5 times higher in gray matter. Simulations showed poorer accuracy and precision for SUVr(70-90)-1 values than for the other reference methods. SRTM BP(ND) and reference Logan DVR-1 values were not affected by a shorter scan duration of 60 min. SRTM BP(ND) and reference Logan DVR-1 values were highly correlated with plasma-input Logan DVR-1 values. VOI-based data analyses indicated robust results for scan durations of 60 min. Reference Logan generated quantitative (S)-(18)F-THK5117 DVR-1 parametric images with the greatest accuracy and precision and with a much lower white-matter signal than seen with SUVr(70-90)-1 images. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Realization of the purely spatial Einstein-Podolsky-Rosen paradox in full-field images of spontaneous parametric down-conversion

NASA Astrophysics Data System (ADS)

Moreau, Paul-Antoine; Mougin-Sisini, Joé; Devaux, Fabrice; Lantz, Eric

2012-07-01

We demonstrate Einstein-Podolsky-Rosen (EPR) entanglement by detecting purely spatial quantum correlations in the near and far fields of spontaneous parametric down-conversion generated in a type-2 beta barium borate crystal. Full-field imaging is performed in the photon-counting regime with an electron-multiplying CCD camera. The data are used without any postselection, and we obtain a violation of Heisenberg inequalities with inferred quantities taking into account all the biphoton pairs in both the near and far fields by integration on the entire two-dimensional transverse planes. This ensures a rigorous demonstration of the EPR paradox in its original position-momentum form.

Non-parametric diffeomorphic image registration with the demons algorithm.

PubMed

Vercauteren, Tom; Pennec, Xavier; Perchant, Aymeric; Ayache, Nicholas

2007-01-01

We propose a non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. The demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. The main idea of our algorithm is to adapt this procedure to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of free form deformations by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the true ones in terms of Jacobians.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

Task-based detectability comparison of exponential transformation of free-response operating characteristic (EFROC) curve and channelized Hotelling observer (CHO)

NASA Astrophysics Data System (ADS)

Khobragade, P.; Fan, Jiahua; Rupcich, Franco; Crotty, Dominic J.; Gilat Schmidt, Taly

2016-03-01

This study quantitatively evaluated the performance of the exponential transformation of the free-response operating characteristic curve (EFROC) metric, with the Channelized Hotelling Observer (CHO) as a reference. The CHO has been used for image quality assessment of reconstruction algorithms and imaging systems and often it is applied to study the signal-location-known cases. The CHO also requires a large set of images to estimate the covariance matrix. In terms of clinical applications, this assumption and requirement may be unrealistic. The newly developed location-unknown EFROC detectability metric is estimated from the confidence scores reported by a model observer. Unlike the CHO, EFROC does not require a channelization step and is a non-parametric detectability metric. There are few quantitative studies available on application of the EFROC metric, most of which are based on simulation data. This study investigated the EFROC metric using experimental CT data. A phantom with four low contrast objects: 3mm (14 HU), 5mm (7HU), 7mm (5 HU) and 10 mm (3 HU) was scanned at dose levels ranging from 25 mAs to 270 mAs and reconstructed using filtered backprojection. The area under the curve values for CHO (AUC) and EFROC (AFE) were plotted with respect to different dose levels. The number of images required to estimate the non-parametric AFE metric was calculated for varying tasks and found to be less than the number of images required for parametric CHO estimation. The AFE metric was found to be more sensitive to changes in dose than the CHO metric. This increased sensitivity and the assumption of unknown signal location may be useful for investigating and optimizing CT imaging methods. Future work is required to validate the AFE metric against human observers.

Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

NASA Technical Reports Server (NTRS)

Galland, Pierre A.; Wang, L.; Liang, X.; Ho, P. P.; Alfano, R. R.

2000-01-01

Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Integrated 68Gallium Labelled Prostate-Specific Membrane Antigen-11 Positron Emission Tomography/Magnetic Resonance Imaging Enhances Discriminatory Power of Multi-Parametric Prostate Magnetic Resonance Imaging.

PubMed

Al-Bayati, Mohammad; Grueneisen, Johannes; Lütje, Susanne; Sawicki, Lino M; Suntharalingam, Saravanabavaan; Tschirdewahn, Stephan; Forsting, Michael; Rübben, Herbert; Herrmann, Ken; Umutlu, Lale; Wetter, Axel

2018-01-01

To evaluate diagnostic accuracy of integrated 68Gallium labelled prostate-specific membrane antigen (68Ga-PSMA)-11 positron emission tomography (PET)/MRI in patients with primary prostate cancer (PCa) as compared to multi-parametric MRI. A total of 22 patients with recently diagnosed primary PCa underwent clinically indicated 68Ga-PSMA-11 PET/CT for initial staging followed by integrated 68Ga-PSMA-11 PET/MRI. Images of multi-parametric magnetic resonance imaging (mpMRI), PET and PET/MRI were evaluated separately by applying Prostate Imaging Reporting and Data System (PIRADSv2) for mpMRI and a 5-point Likert scale for PET and PET/MRI. Results were compared with pathology reports of biopsy or resection. Statistical analyses including receiver operating characteristics analysis were performed to compare the diagnostic performance of mpMRI, PET and PET/MRI. PET and integrated PET/MRI demonstrated a higher diagnostic accuracy than mpMRI (area under the curve: mpMRI: 0.679, PET and PET/MRI: 0.951). The proportion of equivocal results (PIRADS 3 and Likert 3) was considerably higher in mpMRI than in PET and PET/MRI. In a notable proportion of equivocal PIRADS results, PET led to a correct shift towards higher suspicion of malignancy and enabled correct lesion classification. Integrated 68Ga-PSMA-11 PET/MRI demonstrates higher diagnostic accuracy than mpMRI and is particularly valuable in tumours with equivocal results from PIRADS classification. © 2018 S. Karger AG, Basel.

Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia.

PubMed

Park, Hae-Jeong; Kwon, Jun Soo; Youn, Tak; Pae, Ji Soo; Kim, Jae-Jin; Kim, Myung-Sun; Ha, Kyoo-Seob

2002-11-01

We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG. Copyright 2002 Wiley-Liss, Inc.

Autonomous satellite navigation with the Global Positioning System

NASA Technical Reports Server (NTRS)

Fuchs, A. J.; Wooden, W. H., II; Long, A. C.

1977-01-01

This paper discusses the potential of using the Global Positioning System (GPS) to provide autonomous navigation capability to NASA satellites in the 1980 era. Some of the driving forces motivating autonomous navigation are presented. These include such factors as advances in attitude control systems, onboard science annotation, and onboard gridding of imaging data. Simulation results which demonstrate baseline orbit determination accuracies using GPS data on Seasat, Landsat-D, and the Solar Maximum Mission are presented. Emphasis is placed on identifying error sources such as GPS time, GPS ephemeris, user timing biases, and user orbit dynamics, and in a parametric sense on evaluating their contribution to the orbit determination accuracies.

Ultrasound window-modulated compounding Nakagami imaging: Resolution improvement and computational acceleration for liver characterization.

PubMed

Ma, Hsiang-Yang; Lin, Ying-Hsiu; Wang, Chiao-Yin; Chen, Chiung-Nien; Ho, Ming-Chih; Tsui, Po-Hsiang

2016-08-01

Ultrasound Nakagami imaging is an attractive method for visualizing changes in envelope statistics. Window-modulated compounding (WMC) Nakagami imaging was reported to improve image smoothness. The sliding window technique is typically used for constructing ultrasound parametric and Nakagami images. Using a large window overlap ratio may improve the WMC Nakagami image resolution but reduces computational efficiency. Therefore, the objectives of this study include: (i) exploring the effects of the window overlap ratio on the resolution and smoothness of WMC Nakagami images; (ii) proposing a fast algorithm that is based on the convolution operator (FACO) to accelerate WMC Nakagami imaging. Computer simulations and preliminary clinical tests on liver fibrosis samples (n=48) were performed to validate the FACO-based WMC Nakagami imaging. The results demonstrated that the width of the autocorrelation function and the parameter distribution of the WMC Nakagami image reduce with the increase in the window overlap ratio. One-pixel shifting (i.e., sliding the window on the image data in steps of one pixel for parametric imaging) as the maximum overlap ratio significantly improves the WMC Nakagami image quality. Concurrently, the proposed FACO method combined with a computational platform that optimizes the matrix computation can accelerate WMC Nakagami imaging, allowing the detection of liver fibrosis-induced changes in envelope statistics. FACO-accelerated WMC Nakagami imaging is a new-generation Nakagami imaging technique with an improved image quality and fast computation. Copyright © 2016 Elsevier B.V. All rights reserved.

Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems

NASA Astrophysics Data System (ADS)

Agapiou, Sergios; Burger, Martin; Dashti, Masoumeh; Helin, Tapio

2018-04-01

We consider the inverse problem of recovering an unknown functional parameter u in a separable Banach space, from a noisy observation vector y of its image through a known possibly non-linear map {{\\mathcal G}} . We adopt a Bayesian approach to the problem and consider Besov space priors (see Lassas et al (2009 Inverse Problems Imaging 3 87-122)), which are well-known for their edge-preserving and sparsity-promoting properties and have recently attracted wide attention especially in the medical imaging community. Our key result is to show that in this non-parametric setup the maximum a posteriori (MAP) estimates are characterized by the minimizers of a generalized Onsager-Machlup functional of the posterior. This is done independently for the so-called weak and strong MAP estimates, which as we show coincide in our context. In addition, we prove a form of weak consistency for the MAP estimators in the infinitely informative data limit. Our results are remarkable for two reasons: first, the prior distribution is non-Gaussian and does not meet the smoothness conditions required in previous research on non-parametric MAP estimates. Second, the result analytically justifies existing uses of the MAP estimate in finite but high dimensional discretizations of Bayesian inverse problems with the considered Besov priors.

Effect of MRI Acoustic Noise on Cerebral FDG Uptake in Simultaneous MR-PET Imaging

PubMed Central

Abolmaali, Nasreddin; Arabasz, Grae; Guimaraes, Alexander R.; Catana, Ciprian

2013-01-01

Integrated scanners capable of simultaneous PET and MRI data acquisition are now available for human use. Although the scanners’ manufacturers have made substantial efforts to understand and minimize the mutual electromagnetic interference between the two modalities, the potential physiological inference has not been evaluated. In this work, we have studied the influence of the acoustic noise produced by the MR gradients on brain FDG uptake in the Siemens MR-BrainPET prototype. While particular attention was paid to the primary auditory cortex (PAC), a brain-wide analysis was also performed. Methods The effects of the MR on the PET count rate and image quantification were first investigated in phantoms. Next, ten healthy volunteers underwent two simultaneous FDG-PET/MR scans in the supine position with the FDG injection occurring inside the MR-BrainPET, alternating between a “quiet” (control) environment in which no MR sequences were run during the FDG uptake phase (the first 40 minutes after radiotracer administration) and a “noisy” (test) case in which MR sequences were run for the entire time. Cortical and subcortical regions of interest (ROIs) were derived from the high-resolution morphological MR data using FreeSurfer. The changes in FDG uptake in the FreeSurfer-derived ROIs between the two conditions were analyzed from parametric and static PET images, and on a voxel-by-voxel basis using SPM8 and FreeSurfer. Results Only minimal to no electromagnetic interference was observed for most of the MR sequences tested, with a maximum drop in count rate of 1.5% and a maximum change in the measured activity of 1.1% in the corresponding images. The ROI-based analysis showed statistically significant increases in the right PAC in both the parametric (9.13±4.73%) and static (4.18±2.87%) images. SPM8 analysis showed no statistically significant clusters in any images when a p<0.05 (corrected) was used; however, a p<0.001 (uncorrected) resolved bilateral statistically significant clusters of increased FDG uptake in the area of the PAC for the parametric image (left: 8.37±1.55%, right: 8.20±1.17%), but only unilateral increase in the static image (left: 8.68±3.89%). Conclusion Although the operation of the BrainPET prototype is virtually unaffected by the MR scanner, the acoustic noise produced by the MR gradients causes a focal increase in FDG uptake in the PAC, which could affect the interpretation of pathological (or brain-activation related) changes in FDG uptake in this region, if the expected effects are of comparable amplitude. PMID:23462677

Monitoring tumor response of prostate cancer to radiation therapy by multi-parametric 1H and hyperpolarized 13C magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Zhang, Vickie Yi

Radiation therapy is one of the most common curative therapies for patients with localized prostate cancer, but despite excellent success rates, a significant number of patients suffer post- treatment cancer recurrence. The accurate characterization of early tumor response remains a major challenge for the clinical management of these patients. Multi-parametric MRI/1H MR spectroscopy imaging (MRSI) has been shown to increase the diagnostic performance in evaluating the effectiveness of radiation therapy. 1H MRSI can detect altered metabolic profiles in cancerous tissue. In this project, the concentrations of prostate metabolites from snap-frozen biopsies of recurrent cancer after failed radiation therapy were correlated with histopathological findings to identify quantitative biomarkers that predict for residual aggressive versus indolent cancer. The total choline to creatine ratio was significantly higher in recurrent aggressive versus indolent cancer, suggesting that use of a higher threshold tCho/Cr ratio in future in vivo 1H MRSI studies could improve the selection and therapeutic planning for patients after failed radiation therapy. Varying radiation doses may cause a diverse effect on prostate cancer micro-environment and metabolism, which could hold the key to improving treatment protocols for individual patients. The recent development and clinical translation of hyperpolarized 13C MRI have provided the ability to monitor both changes in the tumor micro-environment and its metabolism using a multi-probe approach, [1-13C]pyruvate and 13C urea, combined with 1H Multi-parametric MRI. In this thesis, hyperpolarized 13C MRI, 1H dynamic contrast enhancement, and diffusion weighted imaging were used to identify early radiation dose response in a transgenic prostate cancer model. Hyperpolarized pyruvate to lactate metabolism significantly decreased in a dose dependent fashion by 1 day after radiation therapy, prior to any changes observed using 1H DCE and diffusion weighted imaging. Hyperpolarized 13C urea and 1H DCE both show increase in perfusion/permeability by 4 days post-radiation. In tumor region treated with high dose radiation, ADC values significantly increased post-radiation, suggesting a decrease in cellular density. These dose dependent changes can be used as markers of early tumor response to the impact of increasing doses of radiation therapy. In addition, a spectral-spatial pulse sequence was developed for the 14T to dynamically observe kinetic information in a transgenic prostate cancer model before and after radiation therapy. A novel modeling approach was proposed to parameterize perfusion in the kinetic modeling of pyruvate to lactate conversion for better characterization of pyruvate metabolism. Unlike single time point HP 13C urea imaging, quantitative pharmacokinetic parameters such as blood flow and extracellular extravascular volume fraction can be extracted from dynamic acquisitions. Blood flow measured by hyperpolarized 13C urea was highly correlated with Ktrans measured by 1H DCE, suggesting hyperpolarized urea might be able to provide similar information as 1H DCE. The results of this thesis show that Multi-parametric MRI, including functional MRI, 1H MRSI, and hyperpolarized 13C, holds great potential for evaluating early tumor response to radiation therapy of prostate cancer. The findings of this thesis will be useful in designing future studies for using combined Multi-parametric 1H and hyperpolarized 13C MRI to improve planning and assessing radiation therapy in individual prostate cancer patients.

Brain responses to facial attractiveness induced by facial proportions: evidence from an fMRI study

PubMed Central

Shen, Hui; Chau, Desmond K. P.; Su, Jianpo; Zeng, Ling-Li; Jiang, Weixiong; He, Jufang; Fan, Jintu; Hu, Dewen

2016-01-01

Brain responses to facial attractiveness induced by facial proportions are investigated by using functional magnetic resonance imaging (fMRI), in 41 young adults (22 males and 19 females). The subjects underwent fMRI while they were presented with computer-generated, yet realistic face images, which had varying facial proportions, but the same neutral facial expression, baldhead and skin tone, as stimuli. Statistical parametric mapping with parametric modulation was used to explore the brain regions with the response modulated by facial attractiveness ratings (ARs). The results showed significant linear effects of the ARs in the caudate nucleus and the orbitofrontal cortex for all of the subjects, and a non-linear response profile in the right amygdala for only the male subjects. Furthermore, canonical correlation analysis was used to learn the most relevant facial ratios that were best correlated with facial attractiveness. A regression model on the fMRI-derived facial ratio components demonstrated a strong linear relationship between the visually assessed mean ARs and the predictive ARs. Overall, this study provided, for the first time, direct neurophysiologic evidence of the effects of facial ratios on facial attractiveness and suggested that there are notable gender differences in perceiving facial attractiveness as induced by facial proportions. PMID:27779211

Brain responses to facial attractiveness induced by facial proportions: evidence from an fMRI study.

PubMed

Shen, Hui; Chau, Desmond K P; Su, Jianpo; Zeng, Ling-Li; Jiang, Weixiong; He, Jufang; Fan, Jintu; Hu, Dewen

2016-10-25

Brain responses to facial attractiveness induced by facial proportions are investigated by using functional magnetic resonance imaging (fMRI), in 41 young adults (22 males and 19 females). The subjects underwent fMRI while they were presented with computer-generated, yet realistic face images, which had varying facial proportions, but the same neutral facial expression, baldhead and skin tone, as stimuli. Statistical parametric mapping with parametric modulation was used to explore the brain regions with the response modulated by facial attractiveness ratings (ARs). The results showed significant linear effects of the ARs in the caudate nucleus and the orbitofrontal cortex for all of the subjects, and a non-linear response profile in the right amygdala for only the male subjects. Furthermore, canonical correlation analysis was used to learn the most relevant facial ratios that were best correlated with facial attractiveness. A regression model on the fMRI-derived facial ratio components demonstrated a strong linear relationship between the visually assessed mean ARs and the predictive ARs. Overall, this study provided, for the first time, direct neurophysiologic evidence of the effects of facial ratios on facial attractiveness and suggested that there are notable gender differences in perceiving facial attractiveness as induced by facial proportions.

Elastic models: a comparative study applied to retinal images.

PubMed

Karali, E; Lambropoulou, S; Koutsouris, D

2011-01-01

In this work various methods of parametric elastic models are compared, namely the classical snake, the gradient vector field snake (GVF snake) and the topology-adaptive snake (t-snake), as well as the method of self-affine mapping system as an alternative to elastic models. We also give a brief overview of the methods used. The self-affine mapping system is implemented using an adapting scheme and minimum distance as optimization criterion, which is more suitable for weak edges detection. All methods are applied to glaucomatic retinal images with the purpose of segmenting the optical disk. The methods are compared in terms of segmentation accuracy and speed, as these are derived from cross-correlation coefficients between real and algorithm extracted contours and segmentation time, respectively. As a result, the method of self-affine mapping system presents adequate segmentation time and segmentation accuracy, and significant independence from initialization.

Probing kinematics and fate of the Universe with linearly time-varying deceleration parameter

NASA Astrophysics Data System (ADS)

Akarsu, Özgür; Dereli, Tekin; Kumar, Suresh; Xu, Lixin

2014-02-01

The parametrizations q = q 0+ q 1 z and q = q 0+ q 1(1 - a/ a 0) (Chevallier-Polarski-Linder parametrization) of the deceleration parameter, which are linear in cosmic redshift z and scale factor a , have been frequently utilized in the literature to study the kinematics of the Universe. In this paper, we follow a strategy that leads to these two well-known parametrizations of the deceleration parameter as well as an additional new parametrization, q = q 0+ q 1(1 - t/ t 0), which is linear in cosmic time t. We study the features of this linearly time-varying deceleration parameter in contrast with the other two linear parametrizations. We investigate in detail the kinematics of the Universe by confronting the three models with the latest observational data. We further study the dynamics of the Universe by considering the linearly time-varying deceleration parameter model in comparison with the standard ΛCDM model. We also discuss the future of the Universe in the context of the models under consideration.

18F-FLT uptake kinetics in head and neck squamous cell carcinoma: a PET imaging study.

PubMed

Liu, Dan; Chalkidou, Anastasia; Landau, David B; Marsden, Paul K; Fenwick, John D

2014-04-01

To analyze the kinetics of 3(')-deoxy-3(')-[F-18]-fluorothymidine (18F-FLT) uptake by head and neck squamous cell carcinomas and involved nodes imaged using positron emission tomography (PET). Two- and three-tissue compartment models were fitted to 12 tumor time-activity-curves (TACs) obtained for 6 structures (tumors or involved nodes) imaged in ten dynamic PET studies of 1 h duration, carried out for five patients. The ability of the models to describe the data was assessed using a runs test, the Akaike information criterion (AIC) and leave-one-out cross-validation. To generate parametric maps the models were also fitted to TACs of individual voxels. Correlations between maps of different parameters were characterized using Pearson'sr coefficient; in particular the phosphorylation rate-constants k3-2tiss and k5 of the two- and three-tissue models were studied alongside the flux parameters KFLT- 2tiss and KFLT of these models, and standardized uptake values (SUV). A methodology based on expectation-maximization clustering and the Bayesian information criterion ("EM-BIC clustering") was used to distil the information from noisy parametric images. Fits of two-tissue models 2C3K and 2C4K and three-tissue models 3C5K and 3C6K comprising three, four, five, and six rate-constants, respectively, pass the runs test for 4, 8, 10, and 11 of 12 tumor TACs. The three-tissue models have lower AIC and cross-validation scores for nine of the 12 tumors. Overall the 3C6K model has the lowest AIC and cross-validation scores and its fitted parameter values are of the same orders of magnitude as literature estimates. Maps of KFLT and KFLT- 2tiss are strongly correlated (r = 0.85) and also correlate closely with SUV maps (r = 0.72 for KFLT- 2tiss, 0.64 for KFLT). Phosphorylation rate-constant maps are moderately correlated with flux maps (r = 0.48 for k3-2tiss vs KFLT- 2tiss and r = 0.68 for k5 vs KFLT); however, neither phosphorylation rate-constant correlates significantly with SUV. EM-BIC clustering reduces the parametric maps to a small number of levels--on average 5.8, 3.5, 3.4, and 1.4 for KFLT- 2tiss, KFLT, k3-2tiss, and k5. This large simplification is potentially useful for radiotherapy dose-painting, but demonstrates the high noise in some maps. Statistical simulations show that voxel level noise degrades TACs generated from the 3C6K model sufficiently that the average AIC score, parameter bias, and total uncertainty of 2C4K model fits are similar to those of 3C6K fits, whereas at the whole tumor level the scores are lower for 3C6K fits. For the patients studied here, whole tumor FLT uptake time-courses are represented better overall by a three-tissue than by a two-tissue model. EM-BIC clustering simplifies noisy parametric maps, providing the best description of the underlying information they contain and is potentially useful for radiotherapy dose-painting. However, the clustering highlights the large degree of noise present in maps of the phosphorylation rate-constantsk5 and k3-2tiss, which are conceptually tightly linked to cellular proliferation. Methods must be found to make these maps more robust-either by constraining other model parameters or modifying dynamic imaging protocols. © 2014 American Association of Physicists in Medicine.

Extracting relevant information for cancer diagnosis from dynamic full field OCT through image processing and learning

NASA Astrophysics Data System (ADS)

Apelian, Clément; Gastaud, Clément; Boccara, A. Claude

2017-02-01

For a large number of cancer surgeries, the lack of reliable intraoperative diagnosis leads to reoperations or bad outcomes for the patients. To deliver better diagnosis, we developed Dynamic Full Field OCT (D-FFOCT) as a complement to FFOCT. FFOCT already presents interesting results for cancer diagnosis e.g. Mohs surgery and reaching 96% accuracy on prostate cancer. D-FFOCT accesses the dynamic processes of metabolism and gives new tools to diagnose the state of a tissue at the cellular level to complement FFOCT contrast. We developed a processing framework that intends to maximize the information provided by the FFOCT technology as well as D-FFOCT and synthetize this as a meaningful image. We use different time processing to generate metrics (standard deviation of time signals, decorrelation times and more) and spatial processing to sort out structures and the corresponding imaging modality, which is the most appropriate. Sorting was achieved through quadratic discriminant analysis in a N-dimension parametric space corresponding to our metrics. Combining the best imaging modalities for each structure leads to a rich morphology image. This image displaying the morphology is then colored to represent the dynamic behavior of these structures (slow or fast) and to be quickly analyzed by doctors. Therefore, we achieved a micron resolved image, rich of both FFOCT ability of imaging fixed and highly backscattering structures as well as D-FFOCT ability of imaging low level scattering cellular level details. We believe that this morphological contrast close to histology and the dynamic behavior contrast will push forward the limits of intraoperative diagnosis further on.

Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging.

PubMed

Wen, Qiuting; Kodiweera, Chandana; Dale, Brian M; Shivraman, Giri; Wu, Yu-Chien

2018-01-01

To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments. A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions. The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm 2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion. RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Improving carrier-envelope phase stability in optical parametric chirped-pulse amplifiers by control of timing jitter.

PubMed

Hädrich, S; Rothhardt, J; Krebs, M; Demmler, S; Limpert, J; Tünnermann, A

2012-12-01

It is shown that timing jitter in optical parametric chirped-pulse amplification induces spectral drifts that transfer to carrier-envelope phase (CEP) instabilities via dispersion. Reduction of this effect requires temporal synchronization, which is realized with feedback obtained from the angularly dispersed idler. Furthermore, a novel method to measure the CEP drifts by utilizing parasitic second harmonic generation within parametric amplifiers is presented. Stabilization of the timing allows the obtainment of a CEP stability of 86 mrad over 40 min at 150 kHz repetition rate.

Pulsed excitation terahertz tomography - multiparametric approach

NASA Astrophysics Data System (ADS)

Lopato, Przemyslaw

2018-04-01

This article deals with pulsed excitation terahertz computed tomography (THz CT). Opposite to x-ray CT, where just a single value (pixel) is obtained, in case of pulsed THz CT the time signal is acquired for each position. Recorded waveform can be parametrized - many features carrying various information about examined structure can be calculated. Based on this, multiparametric reconstruction algorithm was proposed: inverse Radon transform based reconstruction is applied for each parameter and then fusion of results is utilized. Performance of the proposed imaging scheme was experimentally verified using dielectric phantoms.

Can color-coded parametric maps improve dynamic enhancement pattern analysis in MR mammography?

PubMed

Baltzer, P A; Dietzel, M; Vag, T; Beger, S; Freiberg, C; Herzog, A B; Gajda, M; Camara, O; Kaiser, W A

2010-03-01

Post-contrast enhancement characteristics (PEC) are a major criterion for differential diagnosis in MR mammography (MRM). Manual placement of regions of interest (ROIs) to obtain time/signal intensity curves (TSIC) is the standard approach to assess dynamic enhancement data. Computers can automatically calculate the TSIC in every lesion voxel and combine this data to form one color-coded parametric map (CCPM). Thus, the TSIC of the whole lesion can be assessed. This investigation was conducted to compare the diagnostic accuracy (DA) of CCPM with TSIC for the assessment of PEC. 329 consecutive patients with 469 histologically verified lesions were examined. MRM was performed according to a standard protocol (1.5 T, 0.1 mmol/kgbw Gd-DTPA). ROIs were drawn manually within any lesion to calculate the TSIC. CCPMs were created in all patients using dedicated software (CAD Sciences). Both methods were rated by 2 observers in consensus on an ordinal scale. Receiver operating characteristics (ROC) analysis was used to compare both methods. The area under the curve (AUC) was significantly (p=0.026) higher for CCPM (0.829) than TSIC (0.749). The sensitivity was 88.5% (CCPM) vs. 82.8% (TSIC), whereas equal specificity levels were found (CCPM: 63.7%, TSIC: 63.0%). The color-coded parametric maps (CCPMs) showed a significantly higher DA compared to TSIC, in particular the sensitivity could be increased. Therefore, the CCPM method is a feasible approach to assessing dynamic data in MRM and condenses several imaging series into one parametric map. © Georg Thieme Verlag KG Stuttgart · New York.

Tri-band optical coherence tomography for lipid and vessel spectroscopic imaging

NASA Astrophysics Data System (ADS)

Yu, Luoqin; Kang, Jiqiang; Wang, Xie; Wei, Xiaoming; Chan, Kin-Tak; Lee, Nikki P.; Wong, Kenneth K. Y.

2016-03-01

Optical coherence tomography (OCT) has been utilized for various functional imaging applications. One of its highlights comes from spectroscopic imaging, which can simultaneously obtain both morphologic and spectroscopic information. Assisting diagnosis and therapeutic intervention of coronary artery disease is one of the major directions in spectroscopic OCT applications. Previously Tanaka et al. have developed a spectral domain OCT (SDOCT) to image lipid distribution within blood vessel [1]. In the meantime, Fleming et al. have demonstrated optical frequency domain imaging (OFDI) by a 1.3-μm swept source and quadratic discriminant analysis model [2]. However, these systems suffered from burdensome computation as the optical properties' variation was calculated from a single-band illumination that provided limited contrast. On the other hand, multi-band OCT facilitates contrast enhancement with separated wavelength bands, which further offers an easier way to distinguish different materials. Federici and Dubois [3] and Tsai and Chan [4] have demonstrated tri-band OCT systems to further enhance the image contrast. However, these previous work provided under-explored functional properties. Our group has reported a dual-band OCT system based on parametrically amplified Fourier domain mode-locked (FDML) laser with time multiplexing scheme [5] and a dual-band FDML laser OCT system with wavelength-division multiplexing [6]. Fiber optical parametric amplifier (OPA) can be ideally incorporated in multi-band spectroscopic OCT system as it has a broad amplification window and offers an additional output range at idler band, which is phase matched with the signal band. The sweeping ranges can thus overcome traditional wavelength bands that are limited by intra-cavity amplifiers in FDML lasers. Here, we combines the dual-band FDML laser together with fiber OPA, which consequently renders a simultaneous tri-band output at 1.3, 1.5, and 1.6 μm, for intravascular applications. Lipid and blood vessel distribution can be subsequently visualized with the tri-band OCT system by ex vivo experiments using porcine artery model with artificial lipid plaques.

On the sensitivity of teleseismic full-waveform inversion to earth parametrization, initial model and acquisition design

NASA Astrophysics Data System (ADS)

Beller, S.; Monteiller, V.; Combe, L.; Operto, S.; Nolet, G.

2018-02-01

Full-waveform inversion (FWI) is not yet a mature imaging technology for lithospheric imaging from teleseismic data. Therefore, its promise and pitfalls need to be assessed more accurately according to the specifications of teleseismic experiments. Three important issues are related to (1) the choice of the lithospheric parametrization for optimization and visualization, (2) the initial model and (3) the acquisition design, in particular in terms of receiver spread and sampling. These three issues are investigated with a realistic synthetic example inspired by the CIFALPS experiment in the Western Alps. Isotropic elastic FWI is implemented with an adjoint-state formalism and aims to update three parameter classes by minimization of a classical least-squares difference-based misfit function. Three different subsurface parametrizations, combining density (ρ) with P and S wave speeds (Vp and Vs) , P and S impedances (Ip and Is), or elastic moduli (λ and μ) are first discussed based on their radiation patterns before their assessment by FWI. We conclude that the (ρ, λ, μ) parametrization provides the FWI models that best correlate with the true ones after recombining a posteriori the (ρ, λ, μ) optimization parameters into Ip and Is. Owing to the low frequency content of teleseismic data, 1-D reference global models as PREM provide sufficiently accurate initial models for FWI after smoothing that is necessary to remove the imprint of the layering. Two kinds of station deployments are assessed: coarse areal geometry versus dense linear one. We unambiguously conclude that a coarse areal geometry should be favoured as it dramatically increases the penetration in depth of the imaging as well as the horizontal resolution. This results because the areal geometry significantly increases local wavenumber coverage, through a broader sampling of the scattering and dip angles, compared to a linear deployment.

Do presenting symptoms explain sex differences in emergency department delays among patients with acute stroke?

PubMed

Gargano, Julia Warner; Wehner, Susan; Reeves, Mathew J

2009-04-01

Previous studies report that women with stroke may experience longer delays in diagnostic workup than men after arriving at the emergency department. We hypothesized that presenting symptom differences could explain these delays. Data were collected on 1922 acute stroke cases who presented to 15 hospitals participating in a statewide stroke registry. We evaluated 2 in-hospital time intervals: emergency department arrival to physician examination ("door-to-doctor") and emergency department arrival to brain imaging ("door-to-image"). We used parametric survival models to estimate time ratios, which represent the ratio of average times comparing women to men, after adjusting for symptom presentation and other confounders. Women were significantly less likely than men to present with any stroke warning sign or suspected stroke (87.5% versus 91.4%) or to report trouble with walking, balance, or dizziness (9.5% versus 13.7%). Difficulty speaking and loss of consciousness were associated with shorter door-to-doctor times. Weakness, facial droop, difficulty speaking, and loss of consciousness were associated with shorter door-to-image times, whereas difficulty with walking/balance was associated with longer door-to-image times. In adjusted analyses, women had 11% longer door-to-doctor intervals (time ratio, 1.11; 95%, CI 1.02 to 1.22) and 15% longer door-to-image intervals (time ratio, 1.15; 95% CI, 1.08 to 1.25) after accounting for presenting symptoms, age, and other confounders. Furthermore, these sex differences remained evident after restricting to patients who arrived within 6 or within 2 hours of symptom onset. Women with acute stroke experienced greater emergency department delays than men, which were not attributable to differences in presenting symptoms, time of arrival, age, or other confounders.

Pixel-based parametric source depth map for Cerenkov luminescence imaging

NASA Astrophysics Data System (ADS)

Altabella, L.; Boschi, F.; Spinelli, A. E.

2016-01-01

Optical tomography represents a challenging problem in optical imaging because of the intrinsically ill-posed inverse problem due to photon diffusion. Cerenkov luminescence tomography (CLT) for optical photons produced in tissues by several radionuclides (i.e.: 32P, 18F, 90Y), has been investigated using both 3D multispectral approach and multiviews methods. Difficult in convergence of 3D algorithms can discourage to use this technique to have information of depth and intensity of source. For these reasons, we developed a faster 2D corrected approach based on multispectral acquisitions, to obtain source depth and its intensity using a pixel-based fitting of source intensity. Monte Carlo simulations and experimental data were used to develop and validate the method to obtain the parametric map of source depth. With this approach we obtain parametric source depth maps with a precision between 3% and 7% for MC simulation and 5-6% for experimental data. Using this method we are able to obtain reliable information about the source depth of Cerenkov luminescence with a simple and flexible procedure.

Image-rotating, 4-mirror, ring optical parametric oscillator

DOEpatents

Smith, Arlee V.; Armstrong, Darrell J.

2004-08-10

A device for optical parametric amplification utilizing four mirrors oriented in a nonplanar configuration where the optical plane formed by two of the mirrors is orthogonal to the optical plane formed by the other two mirrors and with the ratio of lengths of the laser beam paths approximately constant regardless of the scale of the device. With a cavity length of less than approximately 110 mm, a conversion efficiency of greater than 45% can be achieved.

Multi-mode of Four and Six Wave Parametric Amplified Process

NASA Astrophysics Data System (ADS)

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-01

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Multi-mode of Four and Six Wave Parametric Amplified Process.

PubMed

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-03

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Time-efficient high-resolution whole-brain three-dimensional macromolecular proton fraction mapping

PubMed Central

Yarnykh, Vasily L.

2015-01-01

Purpose Macromolecular proton fraction (MPF) mapping is a quantitative MRI method that reconstructs parametric maps of a relative amount of macromolecular protons causing the magnetization transfer (MT) effect and provides a biomarker of myelination in neural tissues. This study aimed to develop a high-resolution whole-brain MPF mapping technique utilizing a minimal possible number of source images for scan time reduction. Methods The described technique is based on replacement of an actually acquired reference image without MT saturation by a synthetic one reconstructed from R1 and proton density maps, thus requiring only three source images. This approach enabled whole-brain three-dimensional MPF mapping with isotropic 1.25×1.25×1.25 mm3 voxel size and scan time of 20 minutes. The synthetic reference method was validated against standard MPF mapping with acquired reference images based on data from 8 healthy subjects. Results Mean MPF values in segmented white and gray matter appeared in close agreement with no significant bias and small within-subject coefficients of variation (<2%). High-resolution MPF maps demonstrated sharp white-gray matter contrast and clear visualization of anatomical details including gray matter structures with high iron content. Conclusions Synthetic reference method improves resolution of MPF mapping and combines accurate MPF measurements with unique neuroanatomical contrast features. PMID:26102097

Sci-Thur PM - Colourful Interactions: Highlights 04: A Fast Quantitative MRI Acquisition and Processing Pipeline for Radiation Treatment Planning and Simulation

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

Jutras, Jean-David

MRI-only Radiation Treatment Planning (RTP) is becoming increasingly popular because of a simplified work-flow, and less inconvenience to the patient who avoids multiple scans. The advantages of MRI-based RTP over traditional CT-based RTP lie in its superior soft-tissue contrast, and absence of ionizing radiation dose. The lack of electron-density information in MRI can be addressed by automatic tissue classification. To distinguish bone from air, which both appear dark in MRI, an ultra-short echo time (UTE) pulse sequence may be used. Quantitative MRI parametric maps can provide improved tissue segmentation/classification and better sensitivity in monitoring disease progression and treatment outcome thanmore » standard weighted images. Superior tumor contrast can be achieved on pure T{sub 1} images compared to conventional T{sub 1}-weighted images acquired in the same scan duration and voxel resolution. In this study, we have developed a robust and fast quantitative MRI acquisition and post-processing work-flow that integrates these latest advances into the MRI-based RTP of brain lesions. Using 3D multi-echo FLASH images at two different optimized flip angles (both acquired in under 9 min, and 1mm isotropic resolution), parametric maps of T{sub 1}, proton-density (M{sub 0}), and T{sub 2}{sup *} are obtained with high contrast-to-noise ratio, and negligible geometrical distortions, water-fat shifts and susceptibility effects. An additional 3D UTE MRI dataset is acquired (in under 4 min) and post-processed to classify tissues for dose simulation. The pipeline was tested on four healthy volunteers and a clinical trial on brain cancer patients is underway.« less

18F-Alfatide II and 18F-FDG Dual Tracer Dynamic PET for Parametric, Early Prediction of Tumor Response to Therapy

PubMed Central

Guo, Jinxia; Guo, Ning; Lang, Lixin; Kiesewetter, Dale O.; Xie, Qingguo; Li, Quanzheng; Eden, Henry S.; Niu, Gang; Chen, Xiaoyuan

2014-01-01

A single dynamic PET acquisition using multiple tracers administered closely in time could provide valuable complementary information about a tumor’s status under quasi-constant conditions. This study aims to investigate the utility of dual-tracer dynamic PET imaging with 18F-Alfatide II (18F-AlF-NOTA-E[PEG4-c(RGDfk)]2) and 18F-FDG for parametric monitoring of tumor responses to therapy. Methods We administered doxorubicin to one group of athymic nude mice with U87MG tumors and Abraxane to another group of mice with MDA-MB-435 tumors. To monitor therapeutic responses, we performed dual-tracer dynamic imaging, in sessions that lasted 90 min, starting by injecting the mice via tail vein catheters with 18F-Alfatide II, followed 40 minutes later by 18F-FDG. To achieve signal separation of the two tracers, we fit a three-compartment reversible model to the time activity curve (TAC) of 18F-Alfatide II for the 40 min prior to 18F-FDG injection, and then extrapolated to 90 min. The 18F-FDG tumor TAC was isolated from the 90 min dual tracer tumor TAC by subtracting the fitted 18F-Alfatide II tumor TAC. With separated tumor TACs, the 18F-Alfatide II binding potential (Bp=k3/k4) and volume of distribution (VD), and 18F-FDG influx rate ((K1×k3)/(k2 + k3)) based on the Patlak method were calculated to validate the signal recovery in a comparison with 60-min single tracer imaging and to monitor therapeutic response. Results The transport and binding rate parameters K1-k3 of 18F-Alfatide II, calculated from the first 40 min of dual tracer dynamic scan, as well as Bp and VD, correlated well with the parameters from the 60 min single tracer scan (R2 > 0.95). Compared with the results of single tracer PET imaging, FDG tumor uptake and influx were recovered well from dual tracer imaging. Upon doxorubicin treatment, while no significant changes in static tracer uptake values of 18F-Alfatide II or 18F-FDG were observed, both 18F-Alfatide II Bp and 18F-FDG influx from kinetic analysis in tumors showed significant decreases. For Abraxane therapy of MDA-MB-435 tumors, significant decrease was only observed with 18F-Alfatide II Bp value from kinetic analysis but not 18F-FDG influx. Conclusion The parameters fitted with compartmental modeling from the dual tracer dynamic imaging are consistent with those from single tracer imaging, substantiating the feasibility of this methodology. Even though no significant differences in tumor size were found until 5 days after doxorubicin treatment started, at day 3 there were already substantial differences in 18F-Alfatide II Bp and 18F-FDG influx rate. Dual tracer imaging can measure 18F-Alfatide II Bp value and 18F-FDG influx simultaneously to evaluate tumor angiogenesis and metabolism. Such changes are known to precede anatomical changes, and thus parametric imaging may offer the promise of early prediction of therapy response. PMID:24232871

An indirect method of imaging the Stokes parameters of a submicron particle with sub-diffraction scattering

NASA Astrophysics Data System (ADS)

Ullah, Kaleem; Garcia-Camara, Braulio; Habib, Muhammad; Yadav, N. P.; Liu, Xuefeng

2018-07-01

In this work, we report an indirect way to image the Stokes parameters of a sample under test (SUT) with sub-diffraction scattering information. We apply our previously reported technique called parametric indirect microscopic imaging (PIMI) based on a fitting and filtration process to measure the Stokes parameters of a submicron particle. A comparison with a classical Stokes measurement is also shown. By modulating the incident field in a precise way, fitting and filtration process at each pixel of the detector in PIMI make us enable to resolve and sense the scattering information of SUT and map them in terms of the Stokes parameters. We believe that our finding can be very useful in fields like singular optics, optical nanoantenna, biomedicine and much more. The spatial signature of the Stokes parameters given by our method has been confirmed with finite difference time domain (FDTD) method.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method.

PubMed

Zou, Kelly H; Resnic, Frederic S; Talos, Ion-Florin; Goldberg-Zimring, Daniel; Bhagwat, Jui G; Haker, Steven J; Kikinis, Ron; Jolesz, Ferenc A; Ohno-Machado, Lucila

2005-10-01

Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported. In the interventional cardiology example, logit and Box-Cox transformations of the predictive probabilities led to satisfactory AUCs (AUC=0.888; p=0.78, and AUC=0.888; p=0.73, respectively), while in the brain tumor resection example, log and Box-Cox transformations of the tumor size also led to satisfactory AUCs (AUC=0.898; p=0.61, and AUC=0.899; p=0.42, respectively). In contrast, significant departures from GOF were observed without applying any transformation prior to assuming a binormal model (AUC=0.766; p=0.004, and AUC=0.831; p=0.03), respectively. In both studies the p values suggested that transformations were important to consider before applying any binormal model to estimate the AUC. Our analyses also demonstrated and confirmed the predictive values of different classifiers for determining the interventional complications following PCIs and resection outcomes in image-guided neurosurgery.

Backscatter absorption gas imaging systems and light sources therefore

DOEpatents

Kulp, Thomas Jan [Livermore, CA; Kliner, Dahv A. V. [San Ramon, CA; Sommers, Ricky [Oakley, CA; Goers, Uta-Barbara [Campbell, NY; Armstrong, Karla M [Livermore, CA

2006-12-19

The location of gases that are not visible to the unaided human eye can be determined using tuned light sources that spectroscopically probe the gases and cameras that can provide images corresponding to the absorption of the gases. The present invention is a light source for a backscatter absorption gas imaging (BAGI) system, and a light source incorporating the light source, that can be used to remotely detect and produce images of "invisible" gases. The inventive light source has a light producing element, an optical amplifier, and an optical parametric oscillator to generate wavelength tunable light in the IR. By using a multi-mode light source and an amplifier that operates using 915 nm pump sources, the power consumption of the light source is reduced to a level that can be operated by batteries for long periods of time. In addition, the light source is tunable over the absorption bands of many hydrocarbons, making it useful for detecting hazardous gases.

Discrete-time switching periodic adaptive control for time-varying parameters with unknown periodicity

NASA Astrophysics Data System (ADS)

Yu, Miao; Huang, Deqing; Yang, Wanqiu

2018-06-01

In this paper, we address the problem of unknown periodicity for a class of discrete-time nonlinear parametric systems without assuming any growth conditions on the nonlinearities. The unknown periodicity hides in the parametric uncertainties, which is difficult to estimate with existing techniques. By incorporating a logic-based switching mechanism, we identify the period and bound of unknown parameter simultaneously. Lyapunov-based analysis is given to demonstrate that a finite number of switchings can guarantee the asymptotic tracking for the nonlinear parametric systems. The simulation result also shows the efficacy of the proposed switching periodic adaptive control approach.

Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies

DTIC Science & Technology

2014-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The study investigates whether fusion PET/MRI imaging with 18F- choline PET/CT and...imaging with 18F- choline PET/CT and diffusion-weighted MRI can be successfully applied to target prostate cancer using image-guided prostate...Completed task. The 18F- choline synthesis was implemented and optimized for routine radiotracer production. RDRC committee approval as part of the IRB

Parametric number covariance in quantum chaotic spectra.

PubMed

Vinayak; Kumar, Sandeep; Pandey, Akhilesh

2016-03-01

We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.

A parametric study of rate of advance and area coverage rate performance of synthetic aperture radar.

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

Raynal, Ann Marie; William H. Hensley, Jr.; Burns, Bryan L.

2014-11-01

The linear ground distance per unit time and ground area covered per unit time of producing synthetic aperture radar (SAR) imagery, termed rate of advance (ROA) and area coverage rate (ACR), are important metrics for platform and radar performance in surveillance applications. These metrics depend on many parameters of a SAR system such as wavelength, aircraft velocity, resolution, antenna beamwidth, imaging mode, and geometry. Often the effects of these parameters on rate of advance and area coverage rate are non-linear. This report addresses the impact of different parameter spaces as they relate to rate of advance and area coverage ratemore » performance.« less

Automated detection of extended sources in radio maps: progress from the SCORPIO survey

NASA Astrophysics Data System (ADS)

Riggi, S.; Ingallinera, A.; Leto, P.; Cavallaro, F.; Bufano, F.; Schillirò, F.; Trigilio, C.; Umana, G.; Buemi, C. S.; Norris, R. P.

2016-08-01

Automated source extraction and parametrization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors. In this paper, we present a new algorithm, called CAESAR (Compact And Extended Source Automated Recognition), to detect and parametrize extended sources in radio interferometric maps. It is based on a pre-filtering stage, allowing image denoising, compact source suppression and enhancement of diffuse emission, followed by an adaptive superpixel clustering stage for final source segmentation. A parametrization stage provides source flux information and a wide range of morphology estimators for post-processing analysis. We developed CAESAR in a modular software library, also including different methods for local background estimation and image filtering, along with alternative algorithms for both compact and diffuse source extraction. The method was applied to real radio continuum data collected at the Australian Telescope Compact Array (ATCA) within the SCORPIO project, a pathfinder of the Evolutionary Map of the Universe (EMU) survey at the Australian Square Kilometre Array Pathfinder (ASKAP). The source reconstruction capabilities were studied over different test fields in the presence of compact sources, imaging artefacts and diffuse emission from the Galactic plane and compared with existing algorithms. When compared to a human-driven analysis, the designed algorithm was found capable of detecting known target sources and regions of diffuse emission, outperforming alternative approaches over the considered fields.

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Characteristics of stereo reproduction with parametric loudspeakers

NASA Astrophysics Data System (ADS)

Aoki, Shigeaki; Toba, Masayoshi; Tsujita, Norihisa

2012-05-01

A parametric loudspeaker utilizes nonlinearity of a medium and is known as a super-directivity loudspeaker. The parametric loudspeaker is one of the prominent applications of nonlinear ultrasonics. So far, the applications have been limited monaural reproduction sound system for public address in museum, station and street etc. In this paper, we discussed characteristics of stereo reproduction with two parametric loudspeakers by comparing with those with two ordinary dynamic loudspeakers. In subjective tests, three typical listening positions were selected to investigate the possibility of correct sound localization in a wide listening area. The binaural information was ILD (Interaural Level Difference) or ITD (Interaural Time Delay). The parametric loudspeaker was an equilateral hexagon. The inner and outer diameters were 99 and 112 mm, respectively. Signals were 500 Hz, 1 kHz, 2 kHz and 4 kHz pure tones and pink noise. Three young males listened to test signals 10 times in each listening condition. Subjective test results showed that listeners at the three typical listening positions perceived correct sound localization of all signals using the parametric loudspeakers. It was almost similar to those using the ordinary dynamic loudspeakers, however, except for the case of sinusoidal waves with ITD. It was determined the parametric loudspeaker could exclude the contradiction between the binaural information ILD and ITD that occurred in stereo reproduction with ordinary dynamic loudspeakers because the super directivity of parametric loudspeaker suppressed the cross talk components.

Machine vision extracted plant movement for early detection of plant water stress.

PubMed

Kacira, M; Ling, P P; Short, T H

2002-01-01

A methodology was established for early, non-contact, and quantitative detection of plant water stress with machine vision extracted plant features. Top-projected canopy area (TPCA) of the plants was extracted from plant images using image-processing techniques. Water stress induced plant movement was decoupled from plant diurnal movement and plant growth using coefficient of relative variation of TPCA (CRV[TPCA)] and was found to be an effective marker for water stress detection. Threshold value of CRV(TPCA) as an indicator of water stress was determined by a parametric approach. The effectiveness of the sensing technique was evaluated against the timing of stress detection by an operator. Results of this study suggested that plant water stress detection using projected canopy area based features of the plants was feasible.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

A Cartesian parametrization for the numerical analysis of material instability

DOE PAGES

Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.; ...

2016-02-25

We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, themore » performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.« less

A Cartesian parametrization for the numerical analysis of material instability

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

Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.

We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, themore » performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.« less

Choice of reconstructed tissue properties affects interpretation of lung EIT images.

PubMed

Grychtol, Bartłomiej; Adler, Andy

2014-06-01

Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization.

Simultaneous K-edge subtraction tomography for tracing strontium using parametric X-ray radiation

NASA Astrophysics Data System (ADS)

Hayakawa, Y.; Hayakawa, K.; Kaneda, T.; Nogami, K.; Sakae, T.; Sakai, T.; Sato, I.; Takahashi, Y.; Tanaka, T.

2017-07-01

The X-ray source based on parametric X-ray radiation (PXR) has been regularly providing a coherent X-ray beam for application studies at Nihon University. Recently, three dimensional (3D) computed tomography (CT) has become one of the most important applications of the PXR source. The methodology referred to as K-edge subtraction (KES) imaging is a particularly successful application utilizing the energy selectivity of PXR. In order to demonstrate the applicability of PXR-KES, a simultaneous KES experiment for a specimen containing strontium was performed using a PXR beam having an energy near the Sr K-edge of 16.1 keV. As a result, the 3D distribution of Sr was obtained by subtraction between the two simultaneously acquired tomographic images.

Stimulated echo diffusion tensor imaging (STEAM-DTI) with varying diffusion times as a probe of breast tissue.

PubMed

Teruel, Jose R; Cho, Gene Y; Moccaldi Rt, Melanie; Goa, Pål E; Bathen, Tone F; Feiweier, Thorsten; Kim, Sungheon G; Moy, Linda; Sigmund, Eric E

2017-01-01

To explore the application of diffusion tensor imaging (DTI) for breast tissue and breast pathologies using a stimulated-echo acquisition mode (STEAM) with variable diffusion times. In this Health Insurance Portability and Accountability Act-compliant study, approved by the local institutional review board, eight patients and six healthy volunteers underwent an MRI examination at 3 Tesla including STEAM-DTI with several diffusion times ranging from 68.5 to 902.5 ms. A DTI model was fitted to the data for each diffusion time, and parametric maps of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for healthy fibroglandular tissue (FGT) and lesions. The median value of radial diffusivity for FGT was fitted to a linear decay to obtain an estimation of the surface-to-volume ratio, from which the radial diameter was calculated. For healthy FGT, radial diffusivity presented a linear decay with the square root of the diffusion time resulting in a range of estimated radial diameters from 202 to 496 µm, while axial diffusivity presented a nearly time-independent diffusion. Residual fat signal was reduced at longer diffusion times due to the shorter T1 of fat. Residual fat signal to the overall signal in the healthy volunteers' FGT was found to range from 2.39% to 2.55% (shortest mixing time), and from 0.40% to 0.51% (longest mixing time) for the b500 images. The use of variable diffusion times may provide an in vivo noninvasive tool to probe diffusion lengths in breast tissue and breast pathology, and might aid by improving fat suppression at longer diffusion times. 2 J. Magn. Reson. Imaging 2017;45:84-93. © 2016 International Society for Magnetic Resonance in Medicine.

Seamline Determination Based on PKGC Segmentation for Remote Sensing Image Mosaicking

PubMed Central

Dong, Qiang; Liu, Jinghong

2017-01-01

This paper presents a novel method of seamline determination for remote sensing image mosaicking. A two-level optimization strategy is applied to determine the seamline. Object-level optimization is executed firstly. Background regions (BRs) and obvious regions (ORs) are extracted based on the results of parametric kernel graph cuts (PKGC) segmentation. The global cost map which consists of color difference, a multi-scale morphological gradient (MSMG) constraint, and texture difference is weighted by BRs. Finally, the seamline is determined in the weighted cost from the start point to the end point. Dijkstra’s shortest path algorithm is adopted for pixel-level optimization to determine the positions of seamline. Meanwhile, a new seamline optimization strategy is proposed for image mosaicking with multi-image overlapping regions. The experimental results show the better performance than the conventional method based on mean-shift segmentation. Seamlines based on the proposed method bypass the obvious objects and take less time in execution. This new method is efficient and superior for seamline determination in remote sensing image mosaicking. PMID:28749446

Reflectance Estimation from Urban Terrestrial Images: Validation of a Symbolic Ray-Tracing Method on Synthetic Data

NASA Astrophysics Data System (ADS)

Coubard, F.; Brédif, M.; Paparoditis, N.; Briottet, X.

2011-04-01

Terrestrial geolocalized images are nowadays widely used on the Internet, mainly in urban areas, through immersion services such as Google Street View. On the long run, we seek to enhance the visualization of these images; for that purpose, radiometric corrections must be performed to free them from illumination conditions at the time of acquisition. Given the simultaneously acquired 3D geometric model of the scene with LIDAR or vision techniques, we face an inverse problem where the illumination and the geometry of the scene are known and the reflectance of the scene is to be estimated. Our main contribution is the introduction of a symbolic ray-tracing rendering to generate parametric images, for quick evaluation and comparison with the acquired images. The proposed approach is then based on an iterative estimation of the reflectance parameters of the materials, using a single rendering pre-processing. We validate the method on synthetic data with linear BRDF models and discuss the limitations of the proposed approach with more general non-linear BRDF models.

Brain signal variability is parametrically modifiable.

PubMed

Garrett, Douglas D; McIntosh, Anthony R; Grady, Cheryl L

2014-11-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The influence of a time-varying least squares parametric model when estimating SFOAEs evoked with swept-frequency tones

NASA Astrophysics Data System (ADS)

Hajicek, Joshua J.; Selesnick, Ivan W.; Henin, Simon; Talmadge, Carrick L.; Long, Glenis R.

2018-05-01

Stimulus frequency otoacoustic emissions (SFOAEs) were evoked and estimated using swept-frequency tones with and without the use of swept suppressor tones. SFOAEs were estimated using a least-squares fitting procedure. The estimated SFOAEs for the two paradigms (with- and without-suppression) were similar in amplitude and phase. The fitting procedure minimizes the square error between a parametric model of total ear-canal pressure (with unknown amplitudes and phases) and ear-canal pressure acquired during each paradigm. Modifying the parametric model to allow SFOAE amplitude and phase to vary over time revealed additional amplitude and phase fine structure in the without-suppressor, but not the with-suppressor paradigm. The use of a time-varying parametric model to estimate SFOAEs without-suppression may provide additional information about cochlear mechanics not available when using a with-suppressor paradigm.

The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data

NASA Astrophysics Data System (ADS)

Peres, Leonardo de Faria; Lucena, Andrews José de; Rotunno Filho, Otto Corrêa; França, José Ricardo de Almeida

2018-02-01

The aim of this work is to study urban heat island (UHI) in Metropolitan Area of Rio de Janeiro (MARJ) based on the analysis of land-surface temperature (LST) and land-use patterns retrieved from Landsat-5/Thematic Mapper (TM), Landsat-7/Enhanced Thematic Mapper Plus (ETM+) and Landsat-8/Operational Land Imager (OLI) and Thermal Infrared Sensors (TIRS) data covering a 32-year period between 1984 and 2015. LST temporal evolution is assessed by comparing the average LST composites for 1984-1999 and 2000-2015 where the parametric Student t-test was conducted at 5% significance level to map the pixels where LST for the more recent period is statistically significantly greater than the previous one. The non-parametric Mann-Whitney-Wilcoxon rank sum test has also confirmed at the same 5% significance level that the more recent period (2000-2015) has higher LST values. UHI intensity between ;urban; and ;rural/urban low density; (;vegetation;) areas for 1984-1999 and 2000-2015 was established and confirmed by both parametric and non-parametric tests at 1% significance level as 3.3 °C (5.1 °C) and 4.4 °C (7.1 °C), respectively. LST has statistically significantly (p-value < 0.01) increased over time in two of three land cover classes (;urban; and ;urban low density;), respectively by 1.9 °C and 0.9 °C, except in ;vegetation; class. A spatial analysis was also performed to identify the urban pixels within MARJ where UHI is more intense by subtracting the LST of these pixels from the LST mean value of ;vegetation; land-use class.

Analyzing and Improving Image Quality in Reflective Ghost Imaging

DTIC Science & Technology

2011-02-01

photon quantum entanglement ," Phys. Rev. A 52, 3429 (1995). [2] A. Valencia, G. Scarcelli. M. D. Angelo, and Y. Shih. "Two- photon imaging with thermal...and reference fields, which were generated by spontaneous parametric downconversion (SPDC) and post- selection [1]. Because biphotons are entangled ...envelopes about center frequency we of linearly-polarized light fields normalized to have V/ photons /m 2s units as functions of their transverse

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

PubMed

Zheng, Xiujuan; Wei, Wentao; Huang, Qiu; Song, Shaoli; Wan, Jieqing; Huang, Gang

2017-01-01

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

Parametric spectro-temporal analyzer (PASTA) for ultrafast optical performance monitoring

NASA Astrophysics Data System (ADS)

Zhang, Chi; Wong, Kenneth K. Y.

2013-12-01

Ultrafast optical spectrum monitoring is one of the most challenging tasks in observing ultrafast phenomena, such as the spectroscopy, dynamic observation of the laser cavity, and spectral encoded imaging systems. However, conventional method such as optical spectrum analyzer (OSA) spatially disperses the spectrum, but the space-to-time mapping is realized by mechanical rotation of a grating, so are incapable of operating at high speed. Besides the spatial dispersion, temporal dispersion provided by dispersive fiber can also stretches the spectrum in time domain in an ultrafast manner, but is primarily confined in measuring short pulses. In view of these constraints, here we present a real-time spectrum analyzer called parametric spectro-temporal analyzer (PASTA), which is based on the time-lens focusing mechanism. It achieves a 100-MHz frame rate and can measure arbitrary waveforms. For the first time, we observe the dynamic spectrum of an ultrafast swept-source: Fourier domain mode-locked (FDML) laser, and the spectrum evolution of a laser cavity during its stabilizing process. In addition to the basic single-lens structure, the multi-lens configurations (e.g. telescope or wide-angle scope) will provide a versatile operating condition, which can zoom in to achieve 0.05-nm resolution and zoom out to achieve 10-nm observation range, namely 17 times zoom in/out ratio. In view of the goal of achieving spectrum analysis with fine accuracy, PASTA provides a promising path to study the real-time spectrum of some dynamic phenomena and non-repetitive events, with orders of magnitude enhancement in the frame rate over conventional OSAs.

Prevalence Incidence Mixture Models

Cancer.gov

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

[Detection of cerebral hypoperfusion using single photon emission computed tomography image analysis and statistical parametric mapping in patients with Parkinson's disease or progressive supranuclear palsy].

PubMed

Harada, Kengo; Saeki, Hiroshi; Matsuya, Eiji; Okita, Izumi

2013-11-01

We carried out differential diagnosis of brain blood flow images using single-photon emission computed tomography (SPECT) for patients with Parkinson's disease (PD) or progressive supranuclear paralysis (PSP) using statistical parametric mapping (SPM) and to whom we had applied anatomical standardization. We studied two groups and compared brain blood flow images using SPECT (N-isopropyl-4-iodoamphetamine [(123)I] hydrochloride injection, 222 MGq dosage i.v.). A total of 27 patients were studied using SPM: 18 with PD and 9 with PSP; humming bird sign on MRI was from moderate to medium. The decline of brain bloodstream in the PSP group was more notable in the midbrain, near the domain where the humming bird sign was observable, than in the PD group. The observable differences in brain bloodstream decline in the midbrain of PSP and PD patients suggest the potential usefulness of this technique's clinical application to distinction diagnosis.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Usefulness of myocardial parametric imaging to evaluate myocardial viability in experimental and in clinical studies

PubMed Central

Korosoglou, G; Hansen, A; Bekeredjian, R; Filusch, A; Hardt, S; Wolf, D; Schellberg, D; Katus, H A; Kuecherer, H

2006-01-01

Objective To evaluate whether myocardial parametric imaging (MPI) is superior to visual assessment for the evaluation of myocardial viability. Methods and results Myocardial contrast echocardiography (MCE) was assessed in 11 pigs before, during, and after left anterior descending coronary artery occlusion and in 32 patients with ischaemic heart disease by using intravenous SonoVue administration. In experimental studies perfusion defect area assessment by MPI was compared with visually guided perfusion defect planimetry. Histological assessment of necrotic tissue was the standard reference. In clinical studies viability was assessed on a segmental level by (1) visual analysis of myocardial opacification; (2) quantitative estimation of myocardial blood flow in regions of interest; and (3) MPI. Functional recovery between three and six months after revascularisation was the standard reference. In experimental studies, compared with visually guided perfusion defect planimetry, planimetric assessment of infarct size by MPI correlated more significantly with histology (r2  =  0.92 versus r2  =  0.56) and had a lower intraobserver variability (4% v 15%, p < 0.05). In clinical studies, MPI had higher specificity (66% v 43%, p < 0.05) than visual MCE and good accuracy (81%) for viability detection. It was less time consuming (3.4 (1.6) v 9.2 (2.4) minutes per image, p < 0.05) than quantitative blood flow estimation by regions of interest and increased the agreement between observers interpreting myocardial perfusion (κ  =  0.87 v κ  =  0.75, p < 0.05). Conclusion MPI is useful for the evaluation of myocardial viability both in animals and in patients. It is less time consuming than quantification analysis by regions of interest and less observer dependent than visual analysis. Thus, strategies incorporating this technique may be valuable for the evaluation of myocardial viability in clinical routine. PMID:15939722

OPCPA front end and contrast optimization for the OMEGA EP kilojoule, picosecond laser

DOE PAGES

Dorrer, C.; Consentino, A.; Irwin, D.; ...

2015-09-01

OMEGA EP is a large-scale laser system that combines optical parametric amplification and solid-state laser amplification on two beamlines to deliver high-intensity, high-energy optical pulses. The temporal contrast of the output pulse is limited by the front-end parametric fluorescence and other features that are specific to parametric amplification. The impact of the two-crystal parametric preamplifier, pump-intensity noise, and pump-signal timing is experimentally studied. The implementation of a parametric amplifier pumped by a short pump pulse before stretching, further amplification, and recompression to enhance the temporal contrast of the high-energy short pulse is described.

New cancer-treatment model of photodynamic therapy combined with a type I topoisomerase inhibitor, CPT-11, against HeLa cell tumors in nude mice used by OPO parametric tunable laser

NASA Astrophysics Data System (ADS)

Yoshida, Takato O.; Matsuzawa, Eiji; Matsuo, Tetsumichi; Koide, Yukio; Terakawa, Susumu; Yokokura, Teruo; Hirano, Toru

1995-03-01

A new cancer-treatment model, photodynamic therapy (PDT) combined with a type I topoisomerase inhibitor, camptothecin derivative (CPT-11), against HeLa cell tumors in BALB/c nude mice has been developed using a wide-band tunable coherent light source operated on optical parametric oscillation (OPO parametric tunable laser). The Photosan-3 PDT and CPT-11 combined therapy was remarkably effective, that is the inhibition rate (I.R.) 40 - 80%, as compared to PDT only in vivo. The analysis of HpD (Photosan-3) and CPT-11 effects on cultured HeLa cells in vitro has been studied by a video-enhanced contrast differential interference contrast microscope (VEC-DIC). Photosan-3 with 600 nm light killed cells by mitochondrial damage within 50 min, but not with 700 nm light. CPT-11 with 700 - 400 nm light killed cells within 50 min after nucleolus damage appeared after around 30 min. The localization of CPT-11 in cells was observed as fluorescence images in the nucleus, particularly the nucleoral area produced clear images using an Argus 100.

Bounded Parametric Model Checking for Elementary Net Systems

NASA Astrophysics Data System (ADS)

Knapik, Michał; Szreter, Maciej; Penczek, Wojciech

Bounded Model Checking (BMC) is an efficient verification method for reactive systems. BMC has been applied so far to verification of properties expressed in (timed) modal logics, but never to their parametric extensions. In this paper we show, for the first time that BMC can be extended to PRTECTL - a parametric extension of the existential version of CTL. To this aim we define a bounded semantics and a translation from PRTECTL to SAT. The implementation of the algorithm for Elementary Net Systems is presented, together with some experimental results.

Parametric modeling of the intervertebral disc space in 3D: application to CT images of the lumbar spine.

PubMed

Korez, Robert; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

2014-10-01

Gradual degeneration of intervertebral discs of the lumbar spine is one of the most common causes of low back pain. Although conservative treatment for low back pain may provide relief to most individuals, surgical intervention may be required for individuals with significant continuing symptoms, which is usually performed by replacing the degenerated intervertebral disc with an artificial implant. For designing implants with good bone contact and continuous force distribution, the morphology of the intervertebral disc space and vertebral body endplates is of considerable importance. In this study, we propose a method for parametric modeling of the intervertebral disc space in three dimensions (3D) and show its application to computed tomography (CT) images of the lumbar spine. The initial 3D model of the intervertebral disc space is generated according to the superquadric approach and therefore represented by a truncated elliptical cone, which is initialized by parameters obtained from 3D models of adjacent vertebral bodies. In an optimization procedure, the 3D model of the intervertebral disc space is incrementally deformed by adding parameters that provide a more detailed morphometric description of the observed shape, and aligned to the observed intervertebral disc space in the 3D image. By applying the proposed method to CT images of 20 lumbar spines, the shape and pose of each of the 100 intervertebral disc spaces were represented by a 3D parametric model. The resulting mean (±standard deviation) accuracy of modeling was 1.06±0.98mm in terms of radial Euclidean distance against manually defined ground truth points, with the corresponding success rate of 93% (i.e. 93 out of 100 intervertebral disc spaces were modeled successfully). As the resulting 3D models provide a description of the shape of intervertebral disc spaces in a complete parametric form, morphometric analysis was straightforwardly enabled and allowed the computation of the corresponding heights, widths and volumes, as well as of other geometric features that in detail describe the shape of intervertebral disc spaces. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Quantum optical measurement with tripartite entangled photons generated by triple parametric down-conversion

NASA Astrophysics Data System (ADS)

Cho, Minhaeng

2018-05-01

Parametric down-conversion is a second-order nonlinear optical process annihilating a pump photon and creating a pair of photons in the signal and idler modes. Then, by using two parametric down-converters and introducing a path indistinguishability for the two generated idler modes, a quantum coherence between two conjugate signal beams can be induced. Such a double spontaneous or stimulated parametric down-conversion scheme has been used to demonstrate quantum spectroscopy and imaging with undetected idler photons via measuring one-photon interference between their correlated signal beams. Recently, we considered another quantum optical measurement scheme utilizing W-type tripartite entangled signal photons that can be generated by employing three spontaneous parametric down-conversion crystals and by inducing coherences or path-indistinguishabilities between their correlated idler beams and between quantum vacuum fields. Here, we consider an extended triple stimulated parametric down-conversion scheme for quantum optical measurement of sample properties with undetected idler and photons. Noting the real effect of vacuum field indistinguishability on the fringe visibility as well as the role of zero-point field energy in the interferometry, we show that this scheme is an ideal and efficient way to create a coherent state of W-type entangled signal photons. We anticipate that this scheme would be of critical use in further developing quantum optical measurements in spectroscopy and microscopy with undetected photons.

Quantum optical measurement with tripartite entangled photons generated by triple parametric down-conversion.

PubMed

Cho, Minhaeng

2018-05-14

Parametric down-conversion is a second-order nonlinear optical process annihilating a pump photon and creating a pair of photons in the signal and idler modes. Then, by using two parametric down-converters and introducing a path indistinguishability for the two generated idler modes, a quantum coherence between two conjugate signal beams can be induced. Such a double spontaneous or stimulated parametric down-conversion scheme has been used to demonstrate quantum spectroscopy and imaging with undetected idler photons via measuring one-photon interference between their correlated signal beams. Recently, we considered another quantum optical measurement scheme utilizing W-type tripartite entangled signal photons that can be generated by employing three spontaneous parametric down-conversion crystals and by inducing coherences or path-indistinguishabilities between their correlated idler beams and between quantum vacuum fields. Here, we consider an extended triple stimulated parametric down-conversion scheme for quantum optical measurement of sample properties with undetected idler and photons. Noting the real effect of vacuum field indistinguishability on the fringe visibility as well as the role of zero-point field energy in the interferometry, we show that this scheme is an ideal and efficient way to create a coherent state of W-type entangled signal photons. We anticipate that this scheme would be of critical use in further developing quantum optical measurements in spectroscopy and microscopy with undetected photons.

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation.

PubMed

Ghaffari, Mahsa; Tangen, Kevin; Alaraj, Ali; Du, Xinjian; Charbel, Fady T; Linninger, Andreas A

2017-12-01

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

NASA Astrophysics Data System (ADS)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

The linear transformation model with frailties for the analysis of item response times.

PubMed

Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey A

2013-02-01

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested. © 2012 The British Psychological Society.

Verification of endocrinological functions at a short distance between parametric speakers and the human body.

PubMed

Lee, Soomin; Katsuura, Tetsuo; Shimomura, Yoshihiro

2011-01-01

In recent years, a new type of speaker called the parametric speaker has been used to generate highly directional sound, and these speakers are now commercially available. In our previous study, we verified that the burden of the parametric speaker was lower than that of the general speaker for endocrine functions. However, nothing has yet been demonstrated about the effects of the shorter distance than 2.6 m between parametric speakers and the human body. Therefore, we investigated the distance effect on endocrinological function and subjective evaluation. Nine male subjects participated in this study. They completed three consecutive sessions: a 20-min quiet period as a baseline, a 30-min mental task period with general speakers or parametric speakers, and a 20-min recovery period. We measured salivary cortisol and chromogranin A (CgA) concentrations. Furthermore, subjects took the Kwansei-gakuin Sleepiness Scale (KSS) test before and after the task and also a sound quality evaluation test after it. Four experiments, one with a speaker condition (general speaker and parametric speaker), the other with a distance condition (0.3 m and 1.0 m), were conducted, respectively, at the same time of day on separate days. We used three-way repeated measures ANOVA (speaker factor × distance factor × time factor) to examine the effects of the parametric speaker. We found that the endocrinological functions were not significantly different between the speaker condition and the distance condition. The results also showed that the physiological burdens increased with progress in time independent of the speaker condition and distance condition.

Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting.

PubMed

Cao, Xiaozhi; Liao, Congyu; Wang, Zhixing; Chen, Ying; Ye, Huihui; He, Hongjian; Zhong, Jianhui

2017-10-01

To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes. A sliding-window (SW) strategy was applied to MRF, in which signal and dictionary matching was conducted between fingerprints consisting of mixed-contrast image series reconstructed from consecutive data frames segmented by a sliding window, and a precalculated mixed-contrast dictionary. The effectiveness and performance of this new method, dubbed SW-MRF, was evaluated in both phantom and in vivo. Error quantifications were conducted on results obtained with various settings of SW reconstruction parameters. Compared with the original MRF strategy, the results of both phantom and in vivo experiments demonstrate that the proposed SW-MRF strategy either provided similar accuracy with reduced acquisition time, or improved accuracy with equal acquisition time. Parametric maps of T 1 , T 2 , and proton density of comparable quality could be achieved with a two-fold or more reduction in acquisition time. The effect of sliding-window width on dictionary sensitivity was also estimated. The novel SW-MRF recovers high quality image frames from highly undersampled MRF data, which enables more robust dictionary matching with reduced numbers of data frames. This time efficiency may facilitate MRF applications in time-critical clinical settings. Magn Reson Med 78:1579-1588, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Controlling the Display of Capsule Endoscopy Video for Diagnostic Assistance

NASA Astrophysics Data System (ADS)

Vu, Hai; Echigo, Tomio; Sagawa, Ryusuke; Yagi, Keiko; Shiba, Masatsugu; Higuchi, Kazuhide; Arakawa, Tetsuo; Yagi, Yasushi

Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5 ± minutes per full sequence while the number of abnormalities found was similar. As well, physicians needed less effort because of the systems efficient operability. The results of the evaluations should convince physicians that they can safely use this method and obtain reduced diagnostic times.

Parametric and non-parametric species delimitation methods result in the recognition of two new Neotropical woody bamboo species.

PubMed

Ruiz-Sanchez, Eduardo

2015-12-01

The Neotropical woody bamboo genus Otatea is one of five genera in the subtribe Guaduinae. Of the eight described Otatea species, seven are endemic to Mexico and one is also distributed in Central and South America. Otatea acuminata has the widest geographical distribution of the eight species, and two of its recently collected populations do not match the known species morphologically. Parametric and non-parametric methods were used to delimit the species in Otatea using five chloroplast markers, one nuclear marker, and morphological characters. The parametric coalescent method and the non-parametric analysis supported the recognition of two distinct evolutionary lineages. Molecular clock estimates were used to estimate divergence times in Otatea. The results for divergence time in Otatea estimated the origin of the speciation events from the Late Miocene to Late Pleistocene. The species delimitation analyses (parametric and non-parametric) identified that the two populations of O. acuminata from Chiapas and Hidalgo are from two separate evolutionary lineages and these new species have morphological characters that separate them from O. acuminata s.s. The geological activity of the Trans-Mexican Volcanic Belt and the Isthmus of Tehuantepec may have isolated populations and limited the gene flow between Otatea species, driving speciation. Based on the results found here, I describe Otatea rzedowskiorum and Otatea victoriae as two new species, morphologically different from O. acuminata. Copyright © 2015 Elsevier Inc. All rights reserved.

Characterization and modelling of the spatially- and spectrally-varying point-spread function in hyperspectral imaging systems for computational correction of axial optical aberrations

NASA Astrophysics Data System (ADS)

Špiclin, Žiga; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2012-03-01

Spatial resolution of hyperspectral imaging systems can vary significantly due to axial optical aberrations that originate from wavelength-induced index-of-refraction variations of the imaging optics. For systems that have a broad spectral range, the spatial resolution will vary significantly both with respect to the acquisition wavelength and with respect to the spatial position within each spectral image. Variations of the spatial resolution can be effectively characterized as part of the calibration procedure by a local image-based estimation of the pointspread function (PSF) of the hyperspectral imaging system. The estimated PSF can then be used in the image deconvolution methods to improve the spatial resolution of the spectral images. We estimated the PSFs from the spectral images of a line grid geometric caliber. From individual line segments of the line grid, the PSF was obtained by a non-parametric estimation procedure that used an orthogonal series representation of the PSF. By using the non-parametric estimation procedure, the PSFs were estimated at different spatial positions and at different wavelengths. The variations of the spatial resolution were characterized by the radius and the fullwidth half-maximum of each PSF and by the modulation transfer function, computed from images of USAF1951 resolution target. The estimation and characterization of the PSFs and the image deconvolution based spatial resolution enhancement were tested on images obtained by a hyperspectral imaging system with an acousto-optic tunable filter in the visible spectral range. The results demonstrate that the spatial resolution of the acquired spectral images can be significantly improved using the estimated PSFs and image deconvolution methods.

Filtering high resolution hyperspectral imagery and analyzing it for quantification of water quality parameters and aquatic vegetation

NASA Astrophysics Data System (ADS)

Pande-Chhetri, Roshan

High resolution hyperspectral imagery (airborne or ground-based) is gaining momentum as a useful analytical tool in various fields including agriculture and aquatic systems. These images are often contaminated with stripes and noise resulting in lower signal-to-noise ratio, especially in aquatic regions where signal is naturally low. This research investigates effective methods for filtering high spatial resolution hyperspectral imagery and use of the imagery in water quality parameter estimation and aquatic vegetation classification. The striping pattern of the hyperspectral imagery is non-parametric and difficult to filter. In this research, a de-striping algorithm based on wavelet analysis and adaptive Fourier domain normalization was examined. The result of this algorithm was found superior to other available algorithms and yielded highest Peak Signal to Noise Ratio improvement. The algorithm was implemented on individual image bands and on selected bands of the Maximum Noise Fraction (MNF) transformed images. The results showed that image filtering in the MNF domain was efficient and produced best results. The study investigated methods of analyzing hyperspectral imagery to estimate water quality parameters and to map aquatic vegetation in case-2 waters. Ground-based hyperspectral imagery was analyzed to determine chlorophyll-a (Chl-a) concentrations in aquaculture ponds. Two-band and three-band indices were implemented and the effect of using submerged reflectance targets was evaluated. Laboratory measured values were found to be in strong correlation with two-band and three-band spectral indices computed from the hyperspectral image. Coefficients of determination (R2) values were found to be 0.833 and 0.862 without submerged targets and stronger values of 0.975 and 0.982 were obtained using submerged targets. Airborne hyperspectral images were used to detect and classify aquatic vegetation in a black river estuarine system. Image normalization for water surface reflectance and water depths was conducted and non-parametric classifiers such as ANN, SVM and SAM were tested and compared. Quality assessment indicated better classification and detection when non-parametric classifiers were applied to normalized or depth invariant transform images. Best classification accuracy of 73% was achieved when ANN is applied on normalized image and best detection accuracy of around 92% was obtained when SVM or SAM was applied on depth invariant images.

Parametric estimation for reinforced concrete relief shelter for Aceh cases

NASA Astrophysics Data System (ADS)

Atthaillah; Saputra, Eri; Iqbal, Muhammad

2018-05-01

This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

Sub-cycle light transients for attosecond, X-ray, four-dimensional imaging

NASA Astrophysics Data System (ADS)

Fattahi, Hanieh

2016-10-01

This paper reviews the revolutionary development of ultra-short, multi-TW laser pulse generation made possible by current laser technology. The design of the unified laser architecture discussed in this paper, based on the synthesis of ultrabroadband optical parametric chirped-pulse amplifiers, promises to provide powerful light transients with electromagnetic forces engineerable on the electron time scale. By coherent combination of multiple amplifiers operating in different wavelength ranges, pulses with wavelength spectra extending from less than 1 ?m to more than 10 ?m, with sub-cycle duration at unprecedented peak and average power levels can be generated. It is shown theoretically that these light transients enable the efficient generation of attosecond X-ray pulses with photon flux sufficient to image, for the first time, picometre-attosecond trajectories of electrons, by means of X-ray diffraction and record the electron dynamics by attosecond spectroscopy. The proposed system leads to a tool with sub-atomic spatio-temporal resolution for studying different processes deep inside matter.

Temporal evolution of the spin-wave intensity and phase in a local parametric amplifier

NASA Astrophysics Data System (ADS)

Brächer, T.; Heussner, F.; Meyer, T.; Fischer, T.; Geilen, M.; Heinz, B.; Lägel, B.; Hillebrands, B.; Pirro, P.

2018-03-01

We present a time-resolved study of the evolution of the spin-wave intensity and phase in a local parametric spin-wave amplifier at pumping powers close to the threshold of parametric generation. We show that the phase of the amplified spin waves is determined by the phase of the incoming signal-carrying spin waves and that it can be preserved on long time scales as long as the energy input by the input spin waves is provided. In contrast, the phase-information is lost in such a local spin-wave amplifier as soon as the input spin-wave is switched off. These findings are an important benchmark for the use of parametric amplifiers in logic circuits relying on the spin-wave phase as information carrier.

Histological correlation of 7 T multi-parametric MRI performed in ex-vivo Achilles tendon.

PubMed

Juras, Vladimir; Apprich, Sebastian; Pressl, Christina; Zbyn, Stefan; Szomolanyi, Pavol; Domayer, Stephan; Hofstaetter, Jochen G; Trattnig, Siegfried

2013-05-01

The goal of this in vitro validation study was to investigate the feasibility of biochemical MRI techniques, such as sodium imaging, T₂ mapping, fast imaging with steady state precession (FISP), and reversed FISP (PSIF), as potential markers for collagen, glycosaminoglycan and water content in the Achilles tendon. Five fresh cadaver ankles acquired from a local anatomy department were used in the study. To acquire a sodium signal from the Achilles tendon, a 3D-gradient-echo sequence, optimized for sodium imaging, was used with TE=7.71 ms and TR=17 ms. The T₂ relaxation times were obtained using a multi-echo, spin-echo technique with a repetition time (TR) of 1200 ms and six echo times. A 3D, partially balanced, steady-state gradient echo pulse sequence was used to acquire FISP and PSIF images, with TR/TE=6.96/2.46 ms. MRI parameters were correlated with each other, as well as with histologically assessed glycosaminoglycan and water content in cadaver Achilles tendons. The highest relevant Pearson correlation coefficient was found between sodium SNR and glycosaminoglycan content (r=0.71, p=0.007). Relatively high correlation was found between the PSIF signal and T2 values (r=0.51, p=0.036), and between the FISP signal and T₂ values (r=0.56, p=0.047). Other correlations were found to be below the moderate level. This study demonstrated the feasibility of progressive biochemical MRI methods for the imaging of the AT. A GAG-specific, contrast-free method (sodium imaging), as well as collagen- and water-sensitive methods (T₂ mapping, FISP, PSIF), may be used in fast-relaxing tissues, such as tendons, in reasonable scan times. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Imaging and Analytics: The changing face of Medical Imaging

NASA Astrophysics Data System (ADS)

Foo, Thomas

There have been significant technological advances in imaging capability over the past 40 years. Medical imaging capabilities have developed rapidly, along with technology development in computational processing speed and miniaturization. Moving to all-digital, the number of images that are acquired in a routine clinical examination has increased dramatically from under 50 images in the early days of CT and MRI to more than 500-1000 images today. The staggering number of images that are routinely acquired poses significant challenges for clinicians to interpret the data and to correctly identify the clinical problem. Although the time provided to render a clinical finding has not substantially changed, the amount of data available for interpretation has grown exponentially. In addition, the image quality (spatial resolution) and information content (physiologically-dependent image contrast) has also increased significantly with advances in medical imaging technology. On its current trajectory, medical imaging in the traditional sense is unsustainable. To assist in filtering and extracting the most relevant data elements from medical imaging, image analytics will have a much larger role. Automated image segmentation, generation of parametric image maps, and clinical decision support tools will be needed and developed apace to allow the clinician to manage, extract and utilize only the information that will help improve diagnostic accuracy and sensitivity. As medical imaging devices continue to improve in spatial resolution, functional and anatomical information content, image/data analytics will be more ubiquitous and integral to medical imaging capability.

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

PubMed

Citak-Er, Fusun; Firat, Zeynep; Kovanlikaya, Ilhami; Ture, Ugur; Ozturk-Isik, Esin

2018-06-15

The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach. Forty-three patients who were newly diagnosed as having a glioma were included in this study. The patients were scanned prior to any therapy using a standard brain tumor magnetic resonance (MR) imaging protocol that included T1 and T2-weighted, diffusion-weighted, diffusion tensor, MR perfusion and MR spectroscopic imaging. Three different regions-of-interest were drawn for each subject to encompass tumor, immediate tumor periphery, and distant peritumoral edema/normal. The normalized mp-MRI features were used to build machine-learning models for differentiating low-grade gliomas (WHO grades I and II) from high grades (WHO grades III and IV). In order to assess the contribution of regional mp-MRI quantitative features to the classification models, a support vector machine-based recursive feature elimination method was applied prior to classification. A machine-learning model based on support vector machine algorithm with linear kernel achieved an accuracy of 93.0%, a specificity of 86.7%, and a sensitivity of 96.4% for the grading of gliomas using ten-fold cross validation based on the proposed subset of the mp-MRI features. In this study, machine-learning based on multiregional and multi-parametric MRI data has proven to be an important tool in grading glial tumors accurately even in this limited patient population. Future studies are needed to investigate the use of machine learning algorithms for brain tumor classification in a larger patient cohort. Copyright © 2018. Published by Elsevier Ltd.

Simultaneous measurement and modulation of multiple physiological parameters in the isolated heart using optical techniques

PubMed Central

Lee, Peter; Yan, Ping; Ewart, Paul; Kohl, Peter

2012-01-01

Whole-heart multi-parametric optical mapping has provided valuable insight into the interplay of electro-physiological parameters, and this technology will continue to thrive as dyes are improved and technical solutions for imaging become simpler and cheaper. Here, we show the advantage of using improved 2nd-generation voltage dyes, provide a simple solution to panoramic multi-parametric mapping, and illustrate the application of flash photolysis of caged compounds for studies in the whole heart. For proof of principle, we used the isolated rat whole-heart model. After characterising the blue and green isosbestic points of di-4-ANBDQBS and di-4-ANBDQPQ, respectively, two voltage and calcium mapping systems are described. With two newly custom-made multi-band optical filters, (1) di-4-ANBDQBS and fluo-4 and (2) di-4-ANBDQPQ and rhod-2 mapping are demonstrated. Furthermore, we demonstrate three-parameter mapping using di-4-ANBDQPQ, rhod-2 and NADH. Using off-the-shelf optics and the di-4-ANBDQPQ and rhod-2 combination, we demonstrate panoramic multi-parametric mapping, affording a 360° spatiotemporal record of activity. Finally, local optical perturbation of calcium dynamics in the whole heart is demonstrated using the caged compound, o-nitrophenyl ethylene glycol tetraacetic acid (NP-EGTA), with an ultraviolet light-emitting diode (LED). Calcium maps (heart loaded with di-4-ANBDQPQ and rhod-2) demonstrate successful NP-EGTA loading and local flash photolysis. All imaging systems were built using only a single camera. In conclusion, using novel 2nd-generation voltage dyes, we developed scalable techniques for multi-parametric optical mapping of the whole heart from one point of view and panoramically. In addition to these parameter imaging approaches, we show that it is possible to use caged compounds and ultraviolet LEDs to locally perturb electrophysiological parameters in the whole heart. PMID:22886365

Ultraino: An Open Phased-Array System for Narrowband Airborne Ultrasound Transmission.

PubMed

Marzo, Asier; Corkett, Tom; Drinkwater, Bruce W

2018-01-01

Modern ultrasonic phased-array controllers are electronic systems capable of delaying the transmitted or received signals of multiple transducers. Configurable transmit-receive array systems, capable of electronic steering and shaping of the beam in near real-time, are available commercially, for example, for medical imaging. However, emerging applications, such as ultrasonic haptics, parametric audio, or ultrasonic levitation, require only a small subset of the capabilities provided by the existing controllers. To meet this need, we present Ultraino, a modular, inexpensive, and open platform that provides hardware, software, and example applications specifically aimed at controlling the transmission of narrowband airborne ultrasound. Our system is composed of software, driver boards, and arrays that enable users to quickly and efficiently perform research in various emerging applications. The software can be used to define array geometries, simulate the acoustic field in real time, and control the connected driver boards. The driver board design is based on an Arduino Mega and can control 64 channels with a square wave of up to 17 Vpp and /5 phase resolution. Multiple boards can be chained together to increase the number of channels. The 40-kHz arrays with flat and spherical geometries are demonstrated for parametric audio generation, acoustic levitation, and haptic feedback.

Harmonic generation and parametric decay in the ion cyclotron frequency range

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

Skiff, F.N.; Wong, K.L.; Ono, M.

1984-06-01

Harmonic generation and parametric decay are examined in a toroidal ACT-I plasma using electrostatic plate antennas. The harmonic generation, which is consistent with sheath rectification, is sufficiently strong that the nonlinearly generated harmonic modes themselves decay parametrically. Resonant and nonresonant parametric decay of the second harmonic are observed and compared with uniform pump theory. Resonant decay of lower hybrid waves into lower hybrid waves and slow ion cyclotron waves is seen for the first time. Surprisingly, the decay processes are nonlinearly saturated, indicating absolute instability.

Research on simplified parametric finite element model of automobile frontal crash

NASA Astrophysics Data System (ADS)

Wu, Linan; Zhang, Xin; Yang, Changhai

2018-05-01

The modeling method and key technologies of the automobile frontal crash simplified parametric finite element model is studied in this paper. By establishing the auto body topological structure, extracting and parameterizing the stiffness properties of substructures, choosing appropriate material models for substructures, the simplified parametric FE model of M6 car is built. The comparison of the results indicates that the simplified parametric FE model can accurately calculate the automobile crash responses and the deformation of the key substructures, and the simulation time is reduced from 6 hours to 2 minutes.

Dynamic-contrast-enhanced-MRI with extravasating contrast reagent: Rat cerebral glioma blood volume determination

NASA Astrophysics Data System (ADS)

Li, Xin; Rooney, William D.; Várallyay, Csanád G.; Gahramanov, Seymur; Muldoon, Leslie L.; Goodman, James A.; Tagge, Ian J.; Selzer, Audrey H.; Pike, Martin M.; Neuwelt, Edward A.; Springer, Charles S.

2010-10-01

The accurate mapping of the tumor blood volume (TBV) fraction ( vb) is a highly desired imaging biometric goal. It is commonly thought that achieving this is difficult, if not impossible, when small molecule contrast reagents (CRs) are used for the T1-weighted (Dynamic-Contrast-Enhanced) DCE-MRI technique. This is because angiogenic malignant tumor vessels allow facile CR extravasation. Here, a three-site equilibrium water exchange model is applied to DCE-MRI data from the cerebrally-implanted rat brain U87 glioma, a tumor exhibiting rapid CR extravasation. Analyses of segments of the (and the entire) DCE data time-course with this "shutter-speed" pharmacokinetic model, which admits finite water exchange kinetics, allow TBV estimation from the first-pass segment. Pairwise parameter determinances were tested with grid searches of 2D parametric error surfaces. Tumor blood volume ( vb), as well as ve (the extracellular, extravascular space volume fraction), and Ktrans (a CR extravasation rate measure) parametric maps are presented. The role of the Patlak Plot in DCE-MRI is also considered.

3-D Quantitative Dynamic Contrast Ultrasound for Prostate Cancer Localization.

PubMed

Schalk, Stefan G; Huang, Jing; Li, Jia; Demi, Libertario; Wijkstra, Hessel; Huang, Pintong; Mischi, Massimo

2018-04-01

To investigate quantitative 3-D dynamic contrast-enhanced ultrasound (DCE-US) and, in particular 3-D contrast-ultrasound dispersion imaging (CUDI), for prostate cancer detection and localization, 43 patients referred for 10-12-core systematic biopsy underwent 3-D DCE-US. For each 3-D DCE-US recording, parametric maps of CUDI-based and perfusion-based parameters were computed. The parametric maps were divided in regions, each corresponding to a biopsy core. The obtained parameters were validated per biopsy location and after combining two or more adjacent regions. For CUDI by correlation (r) and for the wash-in time (WIT), a significant difference in parameter values between benign and malignant biopsy cores was found (p < 0.001). In a per-prostate analysis, sensitivity and specificity were 94% and 50% for r, and 53% and 81% for WIT. Based on these results, it can be concluded that quantitative 3-D DCE-US could aid in localizing prostate cancer. Therefore, we recommend follow-up studies to investigate its value for targeting biopsies. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Comparison of Kasai Autocorrelation and Maximum Likelihood Estimators for Doppler Optical Coherence Tomography

PubMed Central

Chan, Aaron C.; Srinivasan, Vivek J.

2013-01-01

In optical coherence tomography (OCT) and ultrasound, unbiased Doppler frequency estimators with low variance are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible, which should also, in principle, improve estimation performance. Paradoxically, however, the widely used Kasai autocorrelation estimator’s performance worsens with increasing acquisition rate. We propose that parametric estimators based on accurate models of noise statistics can offer better performance. We derive a maximum likelihood estimator (MLE) based on a simple additive white Gaussian noise model, and show that it can outperform the Kasai autocorrelation estimator. In addition, we also derive the Cramer Rao lower bound (CRLB), and show that the variance of the MLE approaches the CRLB for moderate data lengths and noise levels. We note that the MLE performance improves with longer acquisition time, and remains constant or improves with higher acquisition rates. These qualities may make it a preferred technique as OCT imaging speed continues to improve. Finally, our work motivates the development of more general parametric estimators based on statistical models of decorrelation noise. PMID:23446044

Electrical Evaluation of RCA MWS5501D Random Access Memory, Volume 2, Appendix a

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. The address access time, address readout time, the data hold time, and the data setup time are some of the results surveyed.

Correlation-based perfusion mapping using time-resolved MR angiography: A feasibility study for patients with suspicions of steno-occlusive craniocervical arteries.

PubMed

Nam, Yoonho; Jang, Jinhee; Park, Sonya Youngju; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2018-05-22

To explore the feasibility of using correlation-based time-delay (CTD) maps produced from time-resolved MR angiography (TRMRA) to diagnose perfusion abnormalities in patients suspected to have steno-occlusive lesions in the craniocervical arteries. Twenty-seven patients who were suspected to have steno-occlusive lesions in the craniocervical arteries underwent both TRMRA and brain single-photon emission computed tomography (SPECT). TRMRA was performed on the supra-aortic area after intravenous injection of a 0.03 mmol/kg gadolinium-based contrast agent. Time-to-peak (TTP) maps and CTD maps of the brain were automatically generated from TRMRA data, and their quality was assessed. Detection of perfusion abnormalities was compared between CTD maps and the time-series maximal intensity projection (MIP) images from TRMRA and TTP maps. Correlation coefficients between quantitative changes in SPECT and parametric maps for the abnormal perfusion areas were calculated. The CTD maps were of significantly superior quality than TTP maps (p < 0.01). For perfusion abnormality detection, CTD maps (kappa 0.84, 95% confidence interval [CI] 0.67-1.00) showed better agreement with SPECT than TTP maps (0.66, 0.46-0.85). For perfusion deficit detection, CTD maps showed higher accuracy (85.2%, 95% CI 66.3-95.8) than MIP images (66.7%, 46-83.5), with marginal significance (p = 0.07). In abnormal perfusion areas, correlation coefficients between SPECT and CTD (r = 0.74, 95% CI 0.34-0.91) were higher than those between SPECT and TTP (r = 0.66, 0.20-0.88). CTD maps generated from TRMRA were of high quality and offered good diagnostic performance for detecting perfusion abnormalities associated with steno-occlusive arterial lesions in the craniocervical area. • Generation of perfusion parametric maps from time-resolved MR angiography is clinically useful. • Correlation-based delay maps can be used to detect perfusion abnormalities associated with steno-occlusive craniocervical arteries. • Estimation of correlation-based delay is robust for low signal-to-noise 4D MR data.

Real-time solution of linear computational problems using databases of parametric reduced-order models with arbitrary underlying meshes

NASA Astrophysics Data System (ADS)

Amsallem, David; Tezaur, Radek; Farhat, Charbel

2016-12-01

A comprehensive approach for real-time computations using a database of parametric, linear, projection-based reduced-order models (ROMs) based on arbitrary underlying meshes is proposed. In the offline phase of this approach, the parameter space is sampled and linear ROMs defined by linear reduced operators are pre-computed at the sampled parameter points and stored. Then, these operators and associated ROMs are transformed into counterparts that satisfy a certain notion of consistency. In the online phase of this approach, a linear ROM is constructed in real-time at a queried but unsampled parameter point by interpolating the pre-computed linear reduced operators on matrix manifolds and therefore computing an interpolated linear ROM. The proposed overall model reduction framework is illustrated with two applications: a parametric inverse acoustic scattering problem associated with a mockup submarine, and a parametric flutter prediction problem associated with a wing-tank system. The second application is implemented on a mobile device, illustrating the capability of the proposed computational framework to operate in real-time.

An Acoustic Charge Transport Imager for High Definition Television Applications: Reliability Modeling and Parametric Yield Prediction of GaAs Multiple Quantum Well Avalanche Photodiodes. Degree awarded Oct. 1997

NASA Technical Reports Server (NTRS)

Hunt, W. D.; Brennan, K. F.; Summers, C. J.; Yun, Ilgu

1994-01-01

Reliability modeling and parametric yield prediction of GaAs/AlGaAs multiple quantum well (MQW) avalanche photodiodes (APDs), which are of interest as an ultra-low noise image capture mechanism for high definition systems, have been investigated. First, the effect of various doping methods on the reliability of GaAs/AlGaAs multiple quantum well (MQW) avalanche photodiode (APD) structures fabricated by molecular beam epitaxy is investigated. Reliability is examined by accelerated life tests by monitoring dark current and breakdown voltage. Median device lifetime and the activation energy of the degradation mechanism are computed for undoped, doped-barrier, and doped-well APD structures. Lifetimes for each device structure are examined via a statistically designed experiment. Analysis of variance shows that dark-current is affected primarily by device diameter, temperature and stressing time, and breakdown voltage depends on the diameter, stressing time and APD type. It is concluded that the undoped APD has the highest reliability, followed by the doped well and doped barrier devices, respectively. To determine the source of the degradation mechanism for each device structure, failure analysis using the electron-beam induced current method is performed. This analysis reveals some degree of device degradation caused by ionic impurities in the passivation layer, and energy-dispersive spectrometry subsequently verified the presence of ionic sodium as the primary contaminant. However, since all device structures are similarly passivated, sodium contamination alone does not account for the observed variation between the differently doped APDs. This effect is explained by the dopant migration during stressing, which is verified by free carrier concentration measurements using the capacitance-voltage technique.

Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data.

PubMed

Weiskopf, Nikolaus; Veit, Ralf; Erb, Michael; Mathiak, Klaus; Grodd, Wolfgang; Goebel, Rainer; Birbaumer, Niels

2003-07-01

A brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI) is presented which allows human subjects to observe and control changes of their own blood oxygen level-dependent (BOLD) response. This BCI performs data preprocessing (including linear trend removal, 3D motion correction) and statistical analysis on-line. Local BOLD signals are continuously fed back to the subject in the magnetic resonance scanner with a delay of less than 2 s from image acquisition. The mean signal of a region of interest is plotted as a time-series superimposed on color-coded stripes which indicate the task, i.e., to increase or decrease the BOLD signal. We exemplify the presented BCI with one volunteer intending to control the signal of the rostral-ventral and dorsal part of the anterior cingulate cortex (ACC). The subject achieved significant changes of local BOLD responses as revealed by region of interest analysis and statistical parametric maps. The percent signal change increased across fMRI-feedback sessions suggesting a learning effect with training. This methodology of fMRI-feedback can assess voluntary control of circumscribed brain areas. As a further extension, behavioral effects of local self-regulation become accessible as a new field of research.

Raman-noise-induced noise-figure limit for chi (3) parametric amplifiers

NASA Astrophysics Data System (ADS)

Voss, Paul L.; Kumar, Prem

2004-03-01

The nonzero response time of the Kerr [chi (3)] nonlinearity determines the quantum-limited noise figure of c3 parametric amplifiers. This nonzero response time of the nonlinearity requires coupling of the parametric amplification process to a molecular-vibration phonon bath, causing the addition of excess noise through Raman gain or loss at temperatures above 0 K. The effect of this excess noise on the noise figure can be surprisingly significant. We derive analytical expressions for this quantum-limited noise figure for phase-insensitive operation of a chi (3) amplifier and show good agreement with published noise-figure measurements.

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

PubMed

Mofid, Omid; Mobayen, Saleh

2018-01-01

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Quantitative evaluation of microvascular blood flow by contrast-enhanced ultrasound (CEUS).

PubMed

Greis, Christian

2011-01-01

Ultrasound contrast agents consist of tiny gas-filled microbubbles the size of red blood cells. Due to their size distribution, they are purely intravascular tracers which do not extravasate into the interstitial fluid, and thus they are perfect agents for imaging blood distribution and flow. Using ultrasound scanners with contrast-specific software, the specific microbubble-derived echo signals can be separated from tissue signals in realtime, allowing selective imaging of the contrast agent. The signal intensity obtained lies in a linear relationship to the amount of microbubbles in the target organ, which allows easy and reliable assessment of relative blood volume. Imaging of the contrast wash-in and wash-out after bolus injection, or more precisely using the flash-replenishment technique, allows assessment of regional blood flow velocity. Commercially available quantification software packages can calculate time-related intensity values from the contrast wash-in and wash-out phase for each image pixel from stored video clips. After fitting of a mathematical model curve according to the respective kinetic model (bolus or flash-replenishment kinetics), time/intensity curves (TIC) can be calculated from single pixels or user-defined regions of interest (ROI). Characteristic parameters of these TICs (e.g. peak intensity, area under the curve, wash-in rate, etc.) can be displayed as color-coded parametric maps on top of the anatomical image, to identify cold and hot spots with abnormal perfusion.

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

PubMed Central

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration (High Freq) performed similarly to non-parametric methods, but had the highest recall values, suggesting that this method could be employed for automatic tremor detection. PMID:27258018

SDSS J2222+2745: A GRAVITATIONALLY LENSED SEXTUPLE QUASAR WITH A MAXIMUM IMAGE SEPARATION OF 15.''1 DISCOVERED IN THE SLOAN GIANT ARCS SURVEY

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

Dahle, H.; Groeneboom, N.; Gladders, M. D.

2013-08-20

We report the discovery of a unique gravitational lens system, SDSS J2222+2745, producing five spectroscopically confirmed images of a z{sub s} = 2.82 quasar lensed by a foreground galaxy cluster at z{sub l} = 0.49. We also present photometric and spectroscopic evidence for a sixth lensed image of the same quasar. The maximum separation between the quasar images is 15.''1. Both the large image separations and the high image multiplicity are in themselves rare among known lensed quasars, and observing the combination of these two factors is an exceptionally unlikely occurrence in present data sets. This is only the thirdmore » known case of a quasar lensed by a cluster, and the only one with six images. The lens system was discovered in the course of the Sloan Giant Arcs Survey, in which we identify candidate lenses in the Sloan Digital Sky Survey and target these for follow-up and verification with the 2.56 m Nordic Optical Telescope. Multi-band photometry obtained over multiple epochs from 2011 September to 2012 September reveals significant variability at the {approx}10%-30% level in some of the quasar images, indicating that measurements of the relative time delay between quasar images will be feasible. In this lens system, we also identify a bright (g = 21.5) giant arc corresponding to a strongly lensed background galaxy at z{sub s} = 2.30. We fit parametric models of the lens system, constrained by the redshift and positions of the quasar images and the redshift and position of the giant arc. The predicted time delays between different pairs of quasar images range from {approx}100 days to {approx}6 yr.« less

Wavelength-agile near-IR optical parametric oscillator using a deposited silicon waveguide.

PubMed

Wang, Ke-Yao; Foster, Mark A; Foster, Amy C

2015-06-15

Using a deposited hydrogenated amorphous silicon (a-Si:H) waveguide, we demonstrate ultra-broad bandwidth (60 THz) parametric amplification via four-wave mixing (FWM), and subsequently achieve the first silicon optical parametric oscillator (OPO) at near-IR wavelengths. Utilization of the time-dispersion-tuned technique provides an optical source with active wavelength tuning over 42 THz with a fixed pump wave.

Comparison of interpolation functions to improve a rebinning-free CT-reconstruction algorithm.

PubMed

de las Heras, Hugo; Tischenko, Oleg; Xu, Yuan; Hoeschen, Christoph

2008-01-01

The robust algorithm OPED for the reconstruction of images from Radon data has been recently developed. This reconstructs an image from parallel data within a special scanning geometry that does not need rebinning but only a simple re-ordering, so that the acquired fan data can be used directly for the reconstruction. However, if the number of rays per fan view is increased, there appear empty cells in the sinogram. These cells need to be filled by interpolation before the reconstruction can be carried out. The present paper analyzes linear interpolation, cubic splines and parametric (or "damped") splines for the interpolation task. The reconstruction accuracy in the resulting images was measured by the Normalized Mean Square Error (NMSE), the Hilbert Angle, and the Mean Relative Error. The spatial resolution was measured by the Modulation Transfer Function (MTF). Cubic splines were confirmed to be the most recommendable method. The reconstructed images resulting from cubic spline interpolation show a significantly lower NMSE than the ones from linear interpolation and have the largest MTF for all frequencies. Parametric splines proved to be advantageous only for small sinograms (below 50 fan views).

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

Evaluation of the maximum-likelihood adaptive neural system (MLANS) applications to noncooperative IFF

NASA Astrophysics Data System (ADS)

Chernick, Julian A.; Perlovsky, Leonid I.; Tye, David M.

1994-06-01

This paper describes applications of maximum likelihood adaptive neural system (MLANS) to the characterization of clutter in IR images and to the identification of targets. The characterization of image clutter is needed to improve target detection and to enhance the ability to compare performance of different algorithms using diverse imagery data. Enhanced unambiguous IFF is important for fratricide reduction while automatic cueing and targeting is becoming an ever increasing part of operations. We utilized MLANS which is a parametric neural network that combines optimal statistical techniques with a model-based approach. This paper shows that MLANS outperforms classical classifiers, the quadratic classifier and the nearest neighbor classifier, because on the one hand it is not limited to the usual Gaussian distribution assumption and can adapt in real time to the image clutter distribution; on the other hand MLANS learns from fewer samples and is more robust than the nearest neighbor classifiers. Future research will address uncooperative IFF using fused IR and MMW data.

Assessment of Renal Hemodynamics and Oxygenation by Simultaneous Magnetic Resonance Imaging (MRI) and Quantitative Invasive Physiological Measurements.

PubMed

Cantow, Kathleen; Arakelyan, Karen; Seeliger, Erdmann; Niendorf, Thoralf; Pohlmann, Andreas

2016-01-01

In vivo assessment of renal perfusion and oxygenation under (patho)physiological conditions by means of noninvasive diagnostic imaging is conceptually appealing. Blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) and quantitative parametric mapping of the magnetic resonance (MR) relaxation times T 2* and T 2 are thought to provide surrogates of renal tissue oxygenation. The validity and efficacy of this technique for quantitative characterization of local tissue oxygenation and its changes under different functional conditions have not been systematically examined yet and remain to be established. For this purpose, the development of an integrative multimodality approaches is essential. Here we describe an integrated hybrid approach (MR-PHYSIOL) that combines established quantitative physiological measurements with T 2* (T 2) mapping and MR-based kidney size measurements. Standardized reversible (patho)physiologically relevant interventions, such as brief periods of aortic occlusion, hypoxia, and hyperoxia, are used for detailing the relation between the MR-PHYSIOL parameters, in particular between renal T 2* and tissue oxygenation.

Computer-Aided Detection of Prostate Cancer with MRI: Technology and Applications

PubMed Central

Liu, Lizhi; Tian, Zhiqiang; Zhang, Zhenfeng; Fei, Baowei

2016-01-01

One in six men will develop prostate cancer in his life time. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multi-parametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and MR spectroscopy imaging. Due to the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In order to improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:27133005

Case study of supply induced demand: the case of provision of imaging scans (computed tomography and magnetic resonance) at Unimed-Manaus.

PubMed

Andrade, Edson de Oliveira; Andrade, Elizabeth Nogueira de; Gallo, José Hiran

2011-01-01

To present the experience of a health plan operator (Unimed-Manaus) in Manaus, Amazonas, Brazil, with the accreditation of imaging services and the demand induced by the supply of new services (Roemer's Law). This is a retrospective work studying a time series covering the period from January 1998 to June 2004, in which the computed tomography and the magnetic resonance imaging services were implemented as part of the services offered by that health plan operator. Statistical analysis consisted of a descriptive and an inferential part, with the latter using a mean parametric test (Student T-test and ANOVA) and the Pearson correlation test. A 5% alpha and a 95% confidence interval were adopted. At Unimed-Manaus, the supply of new imaging services, by itself, was identified as capable of generating an increased service demand, thus characterizing the phenomenon described by Roemer. The results underscore the need to be aware of the fact that the supply of new health services could bring about their increased use without a real demand.

Ghost imaging with paired x-ray photons

NASA Astrophysics Data System (ADS)

Schori, A.; Borodin, D.; Tamasaku, K.; Shwartz, S.

2018-06-01

We report the experimental observation of ghost imaging with paired x-ray photons, which are generated by parametric downconversion. We use the one-to-one relation between the photon energies and the emission angles and the anticorrelation between the k -vectors of the signal and the idler photons to reconstruct the images of slits with nominally zero background levels. Further extension of our procedure can be used for the observation of various quantum phenomena at x-ray wavelengths.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Dynamical Modeling of NGC 6397: Simulated HST Imaging

NASA Astrophysics Data System (ADS)

Dull, J. D.; Cohn, H. N.; Lugger, P. M.; Slavin, S. D.; Murphy, B. W.

1994-12-01

The proximity of NGC 6397 (2.2 kpc) provides an ideal opportunity to test current dynamical models for globular clusters with the HST Wide-Field/Planetary Camera (WFPC2)\\@. We have used a Monte Carlo algorithm to generate ensembles of simulated Planetary Camera (PC) U-band images of NGC 6397 from evolving, multi-mass Fokker-Planck models. These images, which are based on the post-repair HST-PC point-spread function, are used to develop and test analysis methods for recovering structural information from actual HST imaging. We have considered a range of exposure times up to 2.4times 10(4) s, based on our proposed HST Cycle 5 observations. Our Fokker-Planck models include energy input from dynamically-formed binaries. We have adopted a 20-group mass spectrum extending from 0.16 to 1.4 M_sun. We use theoretical luminosity functions for red giants and main sequence stars. Horizontal branch stars, blue stragglers, white dwarfs, and cataclysmic variables are also included. Simulated images are generated for cluster models at both maximal core collapse and at a post-collapse bounce. We are carrying out stellar photometry on these images using ``DAOPHOT-assisted aperture photometry'' software that we have developed. We are testing several techniques for analyzing the resulting star counts, to determine the underlying cluster structure, including parametric model fits and the nonparametric density estimation methods. Our simulated images also allow us to investigate the accuracy and completeness of methods for carrying out stellar photometry in HST Planetary Camera images of dense cluster cores.

CuBe: parametric modeling of 3D foveal shape using cubic Bézier

PubMed Central

Yadav, Sunil Kumar; Motamedi, Seyedamirhosein; Oberwahrenbrock, Timm; Oertel, Frederike Cosima; Polthier, Konrad; Paul, Friedemann; Kadas, Ella Maria; Brandt, Alexander U.

2017-01-01

Optical coherence tomography (OCT) allows three-dimensional (3D) imaging of the retina, and is commonly used for assessing pathological changes of fovea and macula in many diseases. Many neuroinflammatory conditions are known to cause modifications to the fovea shape. In this paper, we propose a method for parametric modeling of the foveal shape. Our method exploits invariant features of the macula from OCT data and applies a cubic Bézier polynomial along with a least square optimization to produce a best fit parametric model of the fovea. Additionally, we provide several parameters of the foveal shape based on the proposed 3D parametric modeling. Our quantitative and visual results show that the proposed model is not only able to reconstruct important features from the foveal shape, but also produces less error compared to the state-of-the-art methods. Finally, we apply the model in a comparison of healthy control eyes and eyes from patients with neuroinflammatory central nervous system disorders and optic neuritis, and show that several derived model parameters show significant differences between the two groups. PMID:28966857

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 4, Appendix C

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. Statistical analysis data is supplied along with write pulse width, read cycle time, write cycle time, and chip enable time data.

Parametric dense stereovision implementation on a system-on chip (SoC).

PubMed

Gardel, Alfredo; Montejo, Pablo; García, Jorge; Bravo, Ignacio; Lázaro, José L

2012-01-01

This paper proposes a novel hardware implementation of a dense recovery of stereovision 3D measurements. Traditionally 3D stereo systems have imposed the maximum number of stereo correspondences, introducing a large restriction on artificial vision algorithms. The proposed system-on-chip (SoC) provides great performance and efficiency, with a scalable architecture available for many different situations, addressing real time processing of stereo image flow. Using double buffering techniques properly combined with pipelined processing, the use of reconfigurable hardware achieves a parametrisable SoC which gives the designer the opportunity to decide its right dimension and features. The proposed architecture does not need any external memory because the processing is done as image flow arrives. Our SoC provides 3D data directly without the storage of whole stereo images. Our goal is to obtain high processing speed while maintaining the accuracy of 3D data using minimum resources. Configurable parameters may be controlled by later/parallel stages of the vision algorithm executed on an embedded processor. Considering hardware FPGA clock of 100 MHz, image flows up to 50 frames per second (fps) of dense stereo maps of more than 30,000 depth points could be obtained considering 2 Mpix images, with a minimum initial latency. The implementation of computer vision algorithms on reconfigurable hardware, explicitly low level processing, opens up the prospect of its use in autonomous systems, and they can act as a coprocessor to reconstruct 3D images with high density information in real time.

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

Larche, Michael R.; Prowant, Matthew S.; Bruillard, Paul J.

This study compares different approaches for imaging the internal architecture of graphite/epoxy composites using backscattered ultrasound. Two cases are studied. In the first, near-surface defects in a thin graphite/epoxy plates are imaged. The same backscattered waveforms were used to produce peak-to-peak, logarithm of signal energy, as well as entropy images of different types. All of the entropy images exhibit better border delineation and defect contrast than the either peak-to-peak or logarithm of signal energy. The best results are obtained using the joint entropy of the backscattered waveforms with a reference function. Two different references are examined. The first is amore » reflection of the insonifying pulse from a stainless steel reflector. The second is an approximate optimum obtained from an iterative parametric search. The joint entropy images produced using this reference exhibit three times the contrast obtained in previous studies. These plates were later destructively analyzed to determine size and location of near-surface defects and the results found to agree with the defect location and shape as indicated by the entropy images. In the second study, images of long carbon graphite fibers (50% by weight) in polypropylene thermoplastic are obtained as a first step toward ultrasonic determination of the distributions of fiber position and orientation.« less

Sex differences in amphetamine-induced displacement of [(18)F]fallypride in striatal and extrastriatal regions: a PET study.

PubMed

Riccardi, Patrizia; Zald, David; Li, Rui; Park, Sohee; Ansari, M Sib; Dawant, Benoit; Anderson, Sharlet; Woodward, Neil; Schmidt, Dennis; Baldwin, Ronald; Kessler, Robert

2006-09-01

The authors examined gender differences in d-amphetamine-induced displacements of [(18)F]fallypride in the striatal and extrastriatal brain regions and the correlations of these displacements with cognition and sensation seeking. Six women and seven men underwent positron emission tomography (PET) with [(18)F]fallypride before and after an oral dose of d-amphetamine. Percent displacements were calculated using regions of interest and parametric images of dopamine 2 (D(2)) receptor binding potential. Parametric images of dopamine release suggest that the female subjects had greater dopamine release than the male subjects in the right globus pallidus and right inferior frontal gyrus. Gender differences were observed in correlations of changes in cognition and sensation seeking with regional dopamine release. Findings revealed a greater dopamine release in women as well as gender differences in the relationship between regional dopamine release and sensation seeking and cognition.

Dynamic Human Body Modeling Using a Single RGB Camera.

PubMed

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-03-18

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.

Dynamic Human Body Modeling Using a Single RGB Camera

PubMed Central

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-01-01

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones. PMID:26999159

Generic distortion model for metrology under optical microscopes

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Li, Zhongwei; Zhong, Kai; Chao, YuhJin; Miraldo, Pedro; Shi, Yusheng

2018-04-01

For metrology under optical microscopes, lens distortion is the dominant source of error. Previous distortion models and correction methods mostly rely on the assumption that parametric distortion models require a priori knowledge of the microscopes' lens systems. However, because of the numerous optical elements in a microscope, distortions can be hardly represented by a simple parametric model. In this paper, a generic distortion model considering both symmetric and asymmetric distortions is developed. Such a model is obtained by using radial basis functions (RBFs) to interpolate the radius and distortion values of symmetric distortions (image coordinates and distortion rays for asymmetric distortions). An accurate and easy to implement distortion correction method is presented. With the proposed approach, quantitative measurement with better accuracy can be achieved, such as in Digital Image Correlation for deformation measurement when used with an optical microscope. The proposed technique is verified by both synthetic and real data experiments.

Evaluation of Second-Level Inference in fMRI Analysis

PubMed Central

Roels, Sanne P.; Loeys, Tom; Moerkerke, Beatrijs

2016-01-01

We investigate the impact of decisions in the second-level (i.e., over subjects) inferential process in functional magnetic resonance imaging on (1) the balance between false positives and false negatives and on (2) the data-analytical stability, both proxies for the reproducibility of results. Second-level analysis based on a mass univariate approach typically consists of 3 phases. First, one proceeds via a general linear model for a test image that consists of pooled information from different subjects. We evaluate models that take into account first-level (within-subjects) variability and models that do not take into account this variability. Second, one proceeds via inference based on parametrical assumptions or via permutation-based inference. Third, we evaluate 3 commonly used procedures to address the multiple testing problem: familywise error rate correction, False Discovery Rate (FDR) correction, and a two-step procedure with minimal cluster size. Based on a simulation study and real data we find that the two-step procedure with minimal cluster size results in most stable results, followed by the familywise error rate correction. The FDR results in most variable results, for both permutation-based inference and parametrical inference. Modeling the subject-specific variability yields a better balance between false positives and false negatives when using parametric inference. PMID:26819578

Parametric fMRI analysis of visual encoding in the human medial temporal lobe.

PubMed

Rombouts, S A; Scheltens, P; Machielson, W C; Barkhof, F; Hoogenraad, F G; Veltman, D J; Valk, J; Witter, M P

1999-01-01

A number of functional brain imaging studies indicate that the medial temporal lobe system is crucially involved in encoding new information into memory. However, most studies were based on differences in brain activity between encoding of familiar vs. novel stimuli. To further study the underlying cognitive processes, we applied a parametric design of encoding. Seven healthy subjects were instructed to encode complex color pictures into memory. Stimuli were presented in a parametric fashion at different rates, thus representing different loads of encoding. Functional magnetic resonance imaging (fMRI) was used to assess changes in brain activation. To determine the number of pictures successfully stored into memory, recognition scores were determined afterwards. During encoding, brain activation occurred in the medial temporal lobe, comparable to the results obtained by others. Increasing the encoding load resulted in an increase in the number of successfully stored items. This was reflected in a significant increase in brain activation in the left lingual gyrus, in the left and right parahippocampal gyrus, and in the right inferior frontal gyrus. This study shows that fMRI can detect changes in brain activation during variation of one aspect of higher cognitive tasks. Further, it strongly supports the notion that the human medial temporal lobe is involved in encoding novel visual information into memory.

Clinical application of 3D arterial spin-labeled brain perfusion imaging for Alzheimer disease: comparison with brain perfusion SPECT.

PubMed

Takahashi, H; Ishii, K; Hosokawa, C; Hyodo, T; Kashiwagi, N; Matsuki, M; Ashikaga, R; Murakami, T

2014-05-01

Alzheimer disease is the most common neurodegenerative disorder with dementia, and a practical and economic biomarker for diagnosis of Alzheimer disease is needed. Three-dimensional arterial spin-labeling, with its high signal-to-noise ratio, enables measurement of cerebral blood flow precisely without any extrinsic tracers. We evaluated the performance of 3D arterial spin-labeling compared with SPECT, and demonstrated the 3D arterial spin-labeled imaging characteristics in the diagnosis of Alzheimer disease. This study included 68 patients with clinically suspected Alzheimer disease who underwent both 3D arterial spin-labeling and SPECT imaging. Two readers independently assessed both images. Kendall W coefficients of concordance (K) were computed, and receiver operating characteristic analyses were performed for each reader. The differences between the images in regional perfusion distribution were evaluated by means of statistical parametric mapping, and the incidence of hypoperfusion of the cerebral watershed area, referred to as "borderzone sign" in the 3D arterial spin-labeled images, was determined. Readers showed K = 0.82/0.73 for SPECT/3D arterial spin-labeled imaging, and the respective areas under the receiver operating characteristic curve were 0.82/0.69 for reader 1 and 0.80/0.69 for reader 2. Statistical parametric mapping showed that the perisylvian and medial parieto-occipital perfusion in the arterial spin-labeled images was significantly higher than that in the SPECT images. Borderzone sign was observed on 3D arterial spin-labeling in 70% of patients misdiagnosed with Alzheimer disease. The diagnostic performance of 3D arterial spin-labeling and SPECT for Alzheimer disease was almost equivalent. Three-dimensional arterial spin-labeled imaging was more influenced by hemodynamic factors than was SPECT imaging. © 2014 by American Journal of Neuroradiology.

Predicting pulsar scintillation from refractive plasma sheets

NASA Astrophysics Data System (ADS)

Simard, Dana; Pen, Ue-Li

2018-07-01

The dynamic and secondary spectra of many pulsars show evidence for long-lived, aligned images of the pulsar that are stationary on a thin scattering sheet. One explanation for this phenomenon considers the effects of wave crests along sheets in the ionized interstellar medium, such as those due to Alfvén waves propagating along current sheets. If these sheets are closely aligned to our line of sight to the pulsar, high bending angles arise at the wave crests and a selection effect causes alignment of images produced at different crests, similar to grazing reflection off of a lake. Using geometric optics, we develop a simple parametrized model of these corrugated sheets that can be constrained with a single observation and that makes observable predictions for variations in the scintillation of the pulsar over time and frequency. This model reveals qualitative differences between lensing from overdense and underdense corrugated sheets: only if the sheet is overdense compared to the surrounding interstellar medium can the lensed images be brighter than the line-of-sight image to the pulsar, and the faint lensed images are closer to the pulsar at higher frequencies if the sheet is underdense, but at lower frequencies if the sheet is overdense.

Cloud GPU-based simulations for SQUAREMR.

PubMed

Kantasis, George; Xanthis, Christos G; Haris, Kostas; Heiberg, Einar; Aletras, Anthony H

2017-01-01

Quantitative Magnetic Resonance Imaging (MRI) is a research tool, used more and more in clinical practice, as it provides objective information with respect to the tissues being imaged. Pixel-wise T 1 quantification (T 1 mapping) of the myocardium is one such application with diagnostic significance. A number of mapping sequences have been developed for myocardial T 1 mapping with a wide range in terms of measurement accuracy and precision. Furthermore, measurement results obtained with these pulse sequences are affected by errors introduced by the particular acquisition parameters used. SQUAREMR is a new method which has the potential of improving the accuracy of these mapping sequences through the use of massively parallel simulations on Graphical Processing Units (GPUs) by taking into account different acquisition parameter sets. This method has been shown to be effective in myocardial T 1 mapping; however, execution times may exceed 30min which is prohibitively long for clinical applications. The purpose of this study was to accelerate the construction of SQUAREMR's multi-parametric database to more clinically acceptable levels. The aim of this study was to develop a cloud-based cluster in order to distribute the computational load to several GPU-enabled nodes and accelerate SQUAREMR. This would accommodate high demands for computational resources without the need for major upfront equipment investment. Moreover, the parameter space explored by the simulations was optimized in order to reduce the computational load without compromising the T 1 estimates compared to a non-optimized parameter space approach. A cloud-based cluster with 16 nodes resulted in a speedup of up to 13.5 times compared to a single-node execution. Finally, the optimized parameter set approach allowed for an execution time of 28s using the 16-node cluster, without compromising the T 1 estimates by more than 10ms. The developed cloud-based cluster and optimization of the parameter set reduced the execution time of the simulations involved in constructing the SQUAREMR multi-parametric database thus bringing SQUAREMR's applicability within time frames that would be likely acceptable in the clinic. Copyright © 2016 Elsevier Inc. All rights reserved.

Long-Term RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Greece in the Period 2004-2013

NASA Astrophysics Data System (ADS)

Eleftheriou, Alexander; Filizzola, Carolina; Genzano, Nicola; Lacava, Teodosio; Lisi, Mariano; Paciello, Rossana; Pergola, Nicola; Vallianatos, Filippos; Tramutoli, Valerio

2016-01-01

Real-time integration of multi-parametric observations is expected to accelerate the process toward improved, and operationally more effective, systems for time-Dependent Assessment of Seismic Hazard (t-DASH) and earthquake short-term (from days to weeks) forecast. However, a very preliminary step in this direction is the identification of those parameters (chemical, physical, biological, etc.) whose anomalous variations can be, to some extent, associated with the complex process of preparation for major earthquakes. In this paper one of these parameters (the Earth's emitted radiation in the Thermal InfraRed spectral region) is considered for its possible correlation with M ≥ 4 earthquakes occurred in Greece in between 2004 and 2013. The Robust Satellite Technique (RST) data analysis approach and Robust Estimator of TIR Anomalies (RETIRA) index were used to preliminarily define, and then to identify, significant sequences of TIR anomalies (SSTAs) in 10 years (2004-2013) of daily TIR images acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation satellite. Taking into account the physical models proposed for justifying the existence of a correlation among TIR anomalies and earthquake occurrences, specific validation rules (in line with the ones used by the Collaboratory for the Study of Earthquake Predictability—CSEP—Project) have been defined to drive a retrospective correlation analysis process. The analysis shows that more than 93 % of all identified SSTAs occur in the prefixed space-time window around ( M ≥ 4) earthquake's time and location of occurrence with a false positive rate smaller than 7 %. Molchan error diagram analysis shows that such a correlation is far to be achievable by chance notwithstanding the huge amount of missed events due to frequent space/time data gaps produced by the presence of clouds over the scene. Achieved results, and particularly the very low rate of false positives registered on a so long testing period, seems already sufficient (at least) to qualify TIR anomalies (identified by RST approach and RETIRA index) among the parameters to be considered in the framework of a multi-parametric approach to t-DASH.

{sup 18}F-FLT uptake kinetics in head and neck squamous cell carcinoma: A PET imaging study

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

Liu, Dan, E-mail: dan.liu@oncology.ox.ac.uk; Fenwick, John D.; Chalkidou, Anastasia

2014-04-15

Purpose: To analyze the kinetics of 3{sup ′}-deoxy-3{sup ′}-[F-18]-fluorothymidine (18F-FLT) uptake by head and neck squamous cell carcinomas and involved nodes imaged using positron emission tomography (PET). Methods: Two- and three-tissue compartment models were fitted to 12 tumor time-activity-curves (TACs) obtained for 6 structures (tumors or involved nodes) imaged in ten dynamic PET studies of 1 h duration, carried out for five patients. The ability of the models to describe the data was assessed using a runs test, the Akaike information criterion (AIC) and leave-one-out cross-validation. To generate parametric maps the models were also fitted to TACs of individual voxels.more » Correlations between maps of different parameters were characterized using Pearson'sr coefficient; in particular the phosphorylation rate-constants k{sub 3-2tiss} and k{sub 5} of the two- and three-tissue models were studied alongside the flux parameters K{sub FLT-2tiss} and K{sub FLT} of these models, and standardized uptake values (SUV). A methodology based on expectation-maximization clustering and the Bayesian information criterion (“EM-BIC clustering”) was used to distil the information from noisy parametric images. Results: Fits of two-tissue models 2C3K and 2C4K and three-tissue models 3C5K and 3C6K comprising three, four, five, and six rate-constants, respectively, pass the runs test for 4, 8, 10, and 11 of 12 tumor TACs. The three-tissue models have lower AIC and cross-validation scores for nine of the 12 tumors. Overall the 3C6K model has the lowest AIC and cross-validation scores and its fitted parameter values are of the same orders of magnitude as literature estimates. Maps ofK{sub FLT} and K{sub FLT-2tiss} are strongly correlated (r = 0.85) and also correlate closely with SUV maps (r = 0.72 for K{sub FLT-2tiss}, 0.64 for K{sub FLT}). Phosphorylation rate-constant maps are moderately correlated with flux maps (r = 0.48 for k{sub 3-2tiss} vs K{sub FLT-2tiss} and r = 0.68 for k{sub 5} vs K{sub FLT}); however, neither phosphorylation rate-constant correlates significantly with SUV. EM-BIC clustering reduces the parametric maps to a small number of levels—on average 5.8, 3.5, 3.4, and 1.4 for K{sub FLT-2tiss}, K{sub FLT}, k{sub 3-2tiss}, and k{sub 5.} This large simplification is potentially useful for radiotherapy dose-painting, but demonstrates the high noise in some maps. Statistical simulations show that voxel level noise degrades TACs generated from the 3C6K model sufficiently that the average AIC score, parameter bias, and total uncertainty of 2C4K model fits are similar to those of 3C6K fits, whereas at the whole tumor level the scores are lower for 3C6K fits. Conclusions: For the patients studied here, whole tumor FLT uptake time-courses are represented better overall by a three-tissue than by a two-tissue model. EM-BIC clustering simplifies noisy parametric maps, providing the best description of the underlying information they contain and is potentially useful for radiotherapy dose-painting. However, the clustering highlights the large degree of noise present in maps of the phosphorylation rate-constantsk{sub 5} and k{sub 3-2tiss}, which are conceptually tightly linked to cellular proliferation. Methods must be found to make these maps more robust—either by constraining other model parameters or modifying dynamic imaging protocols.« less

DCEUS-based focal parametric perfusion imaging of microvessel with single-pixel resolution and high contrast.

PubMed

Wang, Diya; Xiao, Mengnan; Hu, Hong; Zhang, Yu; Su, Zhe; Xu, Shanshan; Zong, Yujin; Wan, Mingxi

2018-03-01

This study aimed to develop a focal microvascular contrast-enhanced ultrasonic parametric perfusion imaging (PPI) scheme to overcome the tradeoff between the resolution, contrast, and accuracy of focal PPI in the tumor. Its resolution was limited by the low signal-to-clutter ratio (SCR) of time-intensity-curves (TICs) induced by multiple limitations, which deteriorated the accuracy and contrast of focal PPI. The scheme was verified by the in-vivo perfusion experiments. Single-pixel TICs were first extracted to ensure PPI with the highest resolution. The SCR of focal TICs in the tumor was improved using respiratory motion compensation combined with detrended fluctuation analysis. The entire and focal PPIs of six perfusion parameters were then accurately created after filtrating the valid TICs and targeted perfusion parameters. Compared with those of the conventional PPIs, the axial and lateral resolutions of focal PPIs were improved by 30.29% (p < .05) and 32.77% (p < .05), respectively; the average contrast and accuracy evaluated by SCR improved by 7.24 ± 4.90 dB (p < .05) and 5.18 ± 1.28 dB (p < .05), respectively. The edge, morphostructure, inhomogeneous hyper-enhanced distribution, and ring-like perfusion features in intratumoral microvessel were accurately distinguished and highlighted by the focal PPIs. The developed focal PPI can assist clinicians in making confirmed diagnoses and in providing appropriate therapeutic strategies for liver tumor. Copyright © 2017 Elsevier B.V. All rights reserved.

fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series.

PubMed

Chavarrías, Cristina; García-Vázquez, Verónica; Alemán-Gómez, Yasser; Montesinos, Paula; Pascau, Javier; Desco, Manuel

2016-05-01

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks(®)) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat .

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms I: Revisiting Cluster-Based Inferences.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Sathian, K

2018-02-01

In a recent study, Eklund et al. employed resting-state functional magnetic resonance imaging data as a surrogate for null functional magnetic resonance imaging (fMRI) datasets and posited that cluster-wise family-wise error (FWE) rate-corrected inferences made by using parametric statistical methods in fMRI studies over the past two decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; this was principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggested otherwise. Here, we show that accounting for non-Gaussian signal components such as those arising from resting-state neural activity as well as physiological responses and motion artifacts in the null fMRI datasets yields first- and second-level general linear model analysis residuals with nearly uniform and Gaussian sACF. Further comparison with nonparametric permutation tests indicates that cluster-based FWE corrected inferences made with Gaussian spatial noise approximations are valid.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Coupled oscillators in identification of nonlinear damping of a real parametric pendulum

NASA Astrophysics Data System (ADS)

Olejnik, Paweł; Awrejcewicz, Jan

2018-01-01

A damped parametric pendulum with friction is identified twice by means of its precise and imprecise mathematical model. A laboratory test stand designed for experimental investigations of nonlinear effects determined by a viscous resistance and the stick-slip phenomenon serves as the model mechanical system. An influence of accurateness of mathematical modeling on the time variability of the nonlinear damping coefficient of the oscillator is proved. A free decay response of a precisely and imprecisely modeled physical pendulum is dependent on two different time-varying coefficients of damping. The coefficients of the analyzed parametric oscillator are identified with the use of a new semi-empirical method based on a coupled oscillators approach, utilizing the fractional order derivative of the discrete measurement series treated as an input to the numerical model. Results of application of the proposed method of identification of the nonlinear coefficients of the damped parametric oscillator have been illustrated and extensively discussed.

Raman-noise-induced quantum limits for χ(3) nondegenerate phase-sensitive amplification and quadrature squeezing

NASA Astrophysics Data System (ADS)

Voss, Paul L.; Köprülü, Kahraman G.; Kumar, Prem

2006-04-01

We present a quantum theory of nondegenerate phase-sensitive parametric amplification in a χ(3) nonlinear medium. The nonzero response time of the Kerr (χ(3)) nonlinearity determines the quantum-limited noise figure of χ(3) parametric amplification, as well as the limit on quadrature squeezing. This nonzero response time of the nonlinearity requires coupling of the parametric process to a molecular vibration phonon bath, causing the addition of excess noise through spontaneous Raman scattering. We present analytical expressions for the quantum-limited noise figure of frequency nondegenerate and frequency degenerate χ(3) parametric amplifiers operated as phase-sensitive amplifiers. We also present results for frequency nondegenerate quadrature squeezing. We show that our nondegenerate squeezing theory agrees with the degenerate squeezing theory of Boivin and Shapiro as degeneracy is approached. We have also included the effect of linear loss on the phase-sensitive process.

Unsteady wind loads for TMT: replacing parametric models with CFD

NASA Astrophysics Data System (ADS)

MacMartin, Douglas G.; Vogiatzis, Konstantinos

2014-08-01

Unsteady wind loads due to turbulence inside the telescope enclosure result in image jitter and higher-order image degradation due to M1 segment motion. Advances in computational fluid dynamics (CFD) allow unsteady simulations of the flow around realistic telescope geometry, in order to compute the unsteady forces due to wind turbulence. These simulations can then be used to understand the characteristics of the wind loads. Previous estimates used a parametric model based on a number of assumptions about the wind characteristics, such as a von Karman spectrum and frozen-flow turbulence across M1, and relied on CFD only to estimate parameters such as mean wind speed and turbulent kinetic energy. Using the CFD-computed forces avoids the need for assumptions regarding the flow. We discuss here both the loads on the telescope that lead to image jitter, and the spatially-varying force distribution across the primary mirror, using simulations with the Thirty Meter Telescope (TMT) geometry. The amplitude, temporal spectrum, and spatial distribution of wind disturbances are all estimated; these are then used to compute the resulting image motion and degradation. There are several key differences relative to our earlier parametric model. First, the TMT enclosure provides sufficient wind reduction at the top end (near M2) to render the larger cross-sectional structural areas further inside the enclosure (including M1) significant in determining the overall image jitter. Second, the temporal spectrum is not von Karman as the turbulence is not fully developed; this applies both in predicting image jitter and M1 segment motion. And third, for loads on M1, the spatial characteristics are not consistent with propagating a frozen-flow turbulence screen across the mirror: Frozen flow would result in a relationship between temporal frequency content and spatial frequency content that does not hold in the CFD predictions. Incorporating the new estimates of wind load characteristics into TMT response predictions leads to revised estimates of the response of TMT to wind turbulence, and validates the aerodynamic design of the enclosure.

In vivo multiphoton microscopy beyond 1 mm in the brain

NASA Astrophysics Data System (ADS)

Miller, David R.; Medina, Flor A.; Hassan, Ahmed; Perillo, Evan P.; Hagan, Kristen; Kazmi, S. M. Shams; Zemelman, Boris V.; Dunn, Andrew K.

2017-02-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. We demonstrate an imaging depth of 1,200 μm in vasculature and 1,160 μm in neurons. We also demonstrate deep-tissue imaging using Indocyanine Green (ICG), which is FDA approved and a promising route to translate multiphoton microscopy to human applications.

Multi-parametric monitoring of high intensity focused ultrasound (HIFU) treatment using harmonic motion imaging for focused ultrasound (HMIFU)

NASA Astrophysics Data System (ADS)

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa

2012-11-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and relative phase-shift during high energy HIFU where tissue boiling occurs. Forty three (n=18) thermal lesions were formed in ex vivo canine liver specimens. Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-, 20-and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W. For the 10-, 20-, and 30-s treatment cases, a steady decrease in the displacement (-8.67±4.80, -14.44±7.77, 24.03±12.11μm), compressive strain -0.16±0.06, -0.71±0.30, -0.68±0.36 %, and phase shift +1.80±6.80, -15.80±9.44, -18.62±13.14 ° were obtained, respectively, indicating overall increase of relative stiffness and decrease of the viscosity-to-stiffness ratio during heating. After treatment, 2D HMI displacement images of the thermal lesions showed an increased lesion-to-background contrast of 1.34±0.19, 1.98±0.30, 2.26±0.80 and lesion size of 40.95±8.06, 47.6±4.87, and 52.23±2.19 mm2, respectively, which was validated again with pathology 25.17±6.99, 42.17±1.77, 47.17±3.10 mm2. Additionally, studies also investigated the performance of mutli-parametric monitoring under the influence of boiling and attenuation change due to tissue boiling, where discrepancies were found such as deteriorated displacement SNR and reversed lesion-to-background displacement contrast with indication on possible increase in attenuation and tissue gelatification or pulverization. Despite the challenge of the boiling mechanism, the relative phase shift served as consist biomechanical tissue response independent of changes in acoustic properties throughout the HIFU treatment. In addition, the 2D HMI displacement images were able to confirm and quantify the change in dimensions of the thermal lesion site. Therefore, the multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU treatment.

Magnetic Resonance Imaging Allows the Evaluation of Tissue Damage and Regeneration in a Mouse Model of Critical Limb Ischemia.

PubMed

Zaccagnini, Germana; Palmisano, Anna; Canu, Tamara; Maimone, Biagina; Lo Russo, Francesco M; Ambrogi, Federico; Gaetano, Carlo; De Cobelli, Francesco; Del Maschio, Alessandro; Esposito, Antonio; Martelli, Fabio

2015-01-01

Magnetic resonance imaging (MRI) provides non-invasive, repetitive measures in the same individual, allowing the study of a physio-pathological event over time. In this study, we tested the performance of 7 Tesla multi-parametric MRI to monitor the dynamic changes of mouse skeletal muscle injury and regeneration upon acute ischemia induced by femoral artery dissection. T2-mapping (T2 relaxation time), diffusion-tensor imaging (Fractional Anisotropy) and perfusion by Dynamic Contrast-Enhanced MRI (K-trans) were measured and imaging results were correlated with histological morphometric analysis in both Gastrocnemius and Tibialis anterior muscles. We found that tissue damage positively correlated with T2-relaxation time, while myofiber regeneration and capillary density positively correlated with Fractional Anisotropy. Interestingly, K-trans positively correlated with capillary density. Accordingly, repeated MRI measurements between day 1 and day 28 after surgery in ischemic muscles showed that: 1) T2-relaxation time rapidly increased upon ischemia and then gradually declined, returning almost to basal level in the last phases of the regeneration process; 2) Fractional Anisotropy dropped upon ischemic damage induction and then recovered along with muscle regeneration and neoangiogenesis; 3) K-trans reached a minimum upon ischemia, then progressively recovered. Overall, Gastrocnemius and Tibialis anterior muscles displayed similar patterns of MRI parameters dynamic, with more marked responses and less variability in Tibialis anterior. We conclude that MRI provides quantitative information about both tissue damage after ischemia and the subsequent vascular and muscle regeneration, accounting for the differences between subjects and, within the same individual, between different muscles.

Deriving the Coronal Magnetic Field Using Parametric Transformation Analysis

NASA Technical Reports Server (NTRS)

Gary, G. Allen; Rose, M. Franklin (Technical Monitor)

2001-01-01

When plasma-beta greater than 1 then the gas pressure dominates over the magnetic pressure. This ratio as a function along the coronal magnetic field lines varies from beta greater than 1 in the photosphere at the base of the field lines, to beta much less than 1 in the mid-corona, to beta greater than 1 in the upper corona. Almost all magnetic field extrapolations do not or cannot take into account the full range of beta. They essentially assume beta much less than 1, since the full boundary conditions do not exist in the beta greater than 1 regions. We use a basic parametric representation of the magnetic field lines such that the field lines can be manipulated to match linear features in the EUV and SXR coronal images in a least squares sense. This research employs free-form deformation mathematics to generate the associated coronal magnetic field. In our research program, the complex magnetic field topology uses Parametric Transformation Analysis (PTA) which is a new and innovative method to describe the coronal fields that we are developing. In this technique the field lines can be viewed as being embedded in a plastic medium, the frozen-in-field-line concept. As the medium is deformed the field lines are similarly deformed. However the advantage of the PTA method is that the field line movement represents a transformation of one magnetic field solution into another magnetic field solution. When fully implemented, this method will allow the resulting magnetic field solution to fully match the magnetic field lines with EUV/SXR coronal loops by minimizing the differences in direction and dispersion of a collection of PTA magnetic field lines and observed field lines. The derived magnetic field will then allow beta greater than 1 regions to be included, the electric currents to be calculated, and the Lorentz force to be determined. The advantage of this technique is that the solution is: (1) independent of the upper and side boundary conditions, (2) allows non-vanishing magnetic forces, and (3) provides a global magnetic field solution, which contains high- and low-beta regimes and maximizes the similarity between the field lines structure and all the coronal images of the region. The coronal image analysis is crucial to the investigation and for the first time these images can be exploited to derive the coronal magnetic field in a well-posed mathematical formulation. This program is an outgrowth of an investigation in which an extrapolated potential field was required to be "inflated" in order to have the field lines match the Yohkoh/SXT images. The field lines were radially stretched resulting in a better match to the coronal loops of an active region. The PTA method of radial and non-radial deformations of field lines to provide a match to the EUV/SXR images will be presented.

Automated movement correction for dynamic PET/CT images: evaluation with phantom and patient data.

PubMed

Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R; Nelson, Linda D; Small, Gary W; Huang, Sung-Cheng

2014-01-01

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers.

Automated Movement Correction for Dynamic PET/CT Images: Evaluation with Phantom and Patient Data

PubMed Central

Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R.; Nelson, Linda D.; Small, Gary W.; Huang, Sung-Cheng

2014-01-01

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers. PMID:25111700

Parametric techniques for characterizing myocardial tissue by magnetic resonance imaging (part 1): T1 mapping.

PubMed

Perea Palazón, R J; Ortiz Pérez, J T; Prat González, S; de Caralt Robira, T M; Cibeira López, M T; Solé Arqués, M

2016-01-01

The development of myocardial fibrosis is a common process in the appearance of ventricular dysfunction in many heart diseases. Magnetic resonance imaging makes it possible to accurately evaluate the structure and function of the heart, and its role in the macroscopic characterization of myocardial fibrosis by late enhancement techniques has been widely validated clinically. Recent studies have demonstrated that T1-mapping techniques can quantify diffuse myocardial fibrosis and the expansion of the myocardial extracellular space in absolute terms. However, further studies are necessary to validate the usefulness of this technique in the early detection of tissue remodeling at a time when implementing early treatment would improve a patient's prognosis. This article reviews the state of the art for T1 mapping of the myocardium, its clinical applications, and its limitations. Copyright © 2016 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

Complex Geometric Models of Diffusion and Relaxation in Healthy and Damaged White Matter

PubMed Central

Farrell, Jonathan A.D.; Smith, Seth A.; Reich, Daniel S.; Calabresi, Peter A.; van Zijl, Peter C.M.

2010-01-01

Which aspects of tissue microstructure affect diffusion weighted MRI signals? Prior models, many of which use Monte-Carlo simulations, have focused on relatively simple models of the cellular microenvironment and have not considered important anatomic details. With the advent of higher-order analysis models for diffusion imaging, such as high-angular-resolution diffusion imaging (HARDI), more realistic models are necessary. This paper presents and evaluates the reproducibility of simulations of diffusion in complex geometries. Our framework is quantitative, does not require specialized hardware, is easily implemented with little programming experience, and is freely available as open-source software. Models may include compartments with different diffusivities, permeabilities, and T2 time constants using both parametric (e.g., spheres and cylinders) and arbitrary (e.g., mesh-based) geometries. Three-dimensional diffusion displacement-probability functions are mapped with high reproducibility, and thus can be readily used to assess reproducibility of diffusion-derived contrasts. PMID:19739233

A numerical study on piezoelectric energy harvesting by combining transverse galloping and parametric instability phenomena

NASA Astrophysics Data System (ADS)

Franzini, Guilherme Rosa; Santos, Rebeca Caramêz Saraiva; Pesce, Celso Pupo

2017-12-01

This paper aims to numerically investigate the effects of parametric instability on piezoelectric energy harvesting from the transverse galloping of a square prism. A two degrees-of-freedom reduced-order model for this problem is proposed and numerically integrated. A usual quasi-steady galloping model is applied, where the transverse force coefficient is adopted as a cubic polynomial function with respect to the angle of attack. Time-histories of nondimensional prism displacement, electric voltage and power dissipated at both the dashpot and the electrical resistance are obtained as functions of the reduced velocity. Both, oscillation amplitude and electric voltage, increased with the reduced velocity for all parametric excitation conditions tested. For low values of reduced velocity, 2:1 parametric excitation enhances the electric voltage. On the other hand, for higher reduced velocities, a 1:1 parametric excitation (i.e., the same as the natural frequency) enhances both oscillation amplitude and electric voltage. It has been also found that, depending on the parametric excitation frequency, the harvested electrical power can be amplified in 70% when compared to the case under no parametric excitation.

Correlation time and diffusion coefficient imaging: application to a granular flow system.

PubMed

Caprihan, A; Seymour, J D

2000-05-01

A parametric method for spatially resolved measurements for velocity autocorrelation functions, R(u)(tau) = , expressed as a sum of exponentials, is presented. The method is applied to a granular flow system of 2-mm oil-filled spheres rotated in a half-filled horizontal cylinder, which is an Ornstein-Uhlenbeck process with velocity autocorrelation function R(u)(tau) = e(- ||tau ||/tau(c)), where tau(c) is the correlation time and D = tau(c) is the diffusion coefficient. The pulsed-field-gradient NMR method consists of applying three different gradient pulse sequences of varying motion sensitivity to distinguish the range of correlation times present for particle motion. Time-dependent apparent diffusion coefficients are measured for these three sequences and tau(c) and D are then calculated from the apparent diffusion coefficient images. For the cylinder rotation rate of 2.3 rad/s, the axial diffusion coefficient at the top center of the free surface was 5.5 x 10(-6) m(2)/s, the correlation time was 3 ms, and the velocity fluctuation or granular temperature was 1.8 x 10(-3) m(2)/s(2). This method is also applicable to study transport in systems involving turbulence and porous media flows. Copyright 2000 Academic Press.

Kinetic evaluation and test-retest reproducibility of [11C]UCB-J, a novel radioligand for positron emission tomography imaging of synaptic vesicle glycoprotein 2A in humans.

PubMed

Finnema, Sjoerd J; Nabulsi, Nabeel B; Mercier, Joël; Lin, Shu-Fei; Chen, Ming-Kai; Matuskey, David; Gallezot, Jean-Dominique; Henry, Shannan; Hannestad, Jonas; Huang, Yiyun; Carson, Richard E

2017-01-01

Synaptic vesicle glycoprotein 2A (SV2A) is ubiquitously present in presynaptic terminals. Here we report kinetic modeling and test-retest reproducibility assessment of the SV2A positron emission tomography (PET) radioligand [ 11 C]UCB-J in humans. Five volunteers were examined twice on the HRRT after bolus injection of [ 11 C]UCB-J. Arterial blood samples were collected for measurements of radiometabolites and free fraction. Regional time-activity curves were analyzed with 1-tissue (1T) and 2-tissue (2T) compartment models to estimate volumes of distribution ( V T ). Parametric maps were generated using the 1T model. [ 11 C]UCB-J metabolized fairly quickly, with parent fraction of 36 ± 13% at 15 min after injection. Plasma free fraction was 32 ± 1%. Regional time-activity curves displayed rapid kinetics and were well described by the 1T model, except for the cerebellum and hippocampus. V T values estimated with the 2T model were similar to 1T values. Parametric maps were of high quality and V T values correlated well with time activity curve (TAC)-based estimates. Shortening of acquisition time from 120 min to 60 min had a negligible effect on V T values. The mean absolute test-retest reproducibility for V T was 3-9% across regions. In conclusion, [ 11 C]UCB-J exhibited excellent PET tracer characteristics and has potential as a general purpose tool for measuring synaptic density in neurodegenerative disorders.

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

NASA Astrophysics Data System (ADS)

Yang, Yang; Peng, Zhike; Dong, Xingjian; Zhang, Wenming; Clifton, David A.

2018-03-01

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components.

Using Multivariate Adaptive Regression Spline and Artificial Neural Network to Simulate Urbanization in Mumbai, India

NASA Astrophysics Data System (ADS)

Ahmadlou, M.; Delavar, M. R.; Tayyebi, A.; Shafizadeh-Moghadam, H.

2015-12-01

Land use change (LUC) models used for modelling urban growth are different in structure and performance. Local models divide the data into separate subsets and fit distinct models on each of the subsets. Non-parametric models are data driven and usually do not have a fixed model structure or model structure is unknown before the modelling process. On the other hand, global models perform modelling using all the available data. In addition, parametric models have a fixed structure before the modelling process and they are model driven. Since few studies have compared local non-parametric models with global parametric models, this study compares a local non-parametric model called multivariate adaptive regression spline (MARS), and a global parametric model called artificial neural network (ANN) to simulate urbanization in Mumbai, India. Both models determine the relationship between a dependent variable and multiple independent variables. We used receiver operating characteristic (ROC) to compare the power of the both models for simulating urbanization. Landsat images of 1991 (TM) and 2010 (ETM+) were used for modelling the urbanization process. The drivers considered for urbanization in this area were distance to urban areas, urban density, distance to roads, distance to water, distance to forest, distance to railway, distance to central business district, number of agricultural cells in a 7 by 7 neighbourhoods, and slope in 1991. The results showed that the area under the ROC curve for MARS and ANN was 94.77% and 95.36%, respectively. Thus, ANN performed slightly better than MARS to simulate urban areas in Mumbai, India.

Statistical parametric mapping of stimuli-evoked changes in quantitative blood flow using extended-focus optical coherence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo

2016-03-01

Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.

An augmented parametric response map with consideration of image registration error: towards guidance of locally adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Lausch, Anthony; Chen, Jeff; Ward, Aaron D.; Gaede, Stewart; Lee, Ting-Yim; Wong, Eugene

2014-11-01

Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient’s unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data

Treesearch

Ronald E. McRoberts; Steen Magnussen; Erkki O. Tomppo; Gherardo Chirici

2011-01-01

Nearest neighbors techniques have been shown to be useful for estimating forest attributes, particularly when used with forest inventory and satellite image data. Published reports of positive results have been truly international in scope. However, for these techniques to be more useful, they must be able to contribute to scientific inference which, for sample-based...

A generalized Benford's law for JPEG coefficients and its applications in image forensics

NASA Astrophysics Data System (ADS)

Fu, Dongdong; Shi, Yun Q.; Su, Wei

2007-02-01

In this paper, a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients is presented. A parametric logarithmic law, i.e., the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics are discussed in this paper, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Qfactor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. The results of our extensive experiments demonstrate the effectiveness of the proposed statistical model.

Rainbow correlation imaging with macroscopic twin beam

NASA Astrophysics Data System (ADS)

Allevi, Alessia; Bondani, Maria

2017-06-01

We present the implementation of a correlation-imaging protocol that exploits both the spatial and spectral correlations of macroscopic twin-beam states generated by parametric downconversion. In particular, the spectral resolution of an imaging spectrometer coupled to an EMCCD camera is used in a proof-of-principle experiment to encrypt and decrypt a simple code to be transmitted between two parties. In order to optimize the trade-off between visibility and resolution, we provide the characterization of the correlation images as a function of the spatio-spectral properties of twin beams generated at different pump power values.

A theoretical investigation on the parametric instability excited by X-mode polarized electromagnetic wave at Tromsø

NASA Astrophysics Data System (ADS)

Wang, Xiang; Cannon, Patrick; Zhou, Chen; Honary, Farideh; Ni, Binbin; Zhao, Zhengyu

2016-04-01

Recent ionospheric modification experiments performed at Tromsø, Norway, have indicated that X-mode pump wave is capable of stimulating high-frequency enhanced plasma lines, which manifests the excitation of parametric instability. This paper investigates theoretically how the observation can be explained by the excitation of parametric instability driven by X-mode pump wave. The threshold of the parametric instability has been calculated for several recent experimental observations at Tromsø, illustrating that our derived equations for the excitation of parametric instability for X-mode heating can explain the experimental observations. According to our theoretical calculation, a minimum fraction of pump wave electric field needs to be directed along the geomagnetic field direction in order for the parametric instability threshold to be met. A full-wave finite difference time domain simulation has been performed to demonstrate that a small parallel component of pump wave electric field can be achieved during X-mode heating in the presence of inhomogeneous plasma.

Robust autofocus algorithm for ISAR imaging of moving targets

NASA Astrophysics Data System (ADS)

Li, Jian; Wu, Renbiao; Chen, Victor C.

2000-08-01

A robust autofocus approach, referred to as AUTOCLEAN (AUTOfocus via CLEAN), is proposed for the motion compensation in ISAR (inverse synthetic aperture radar) imaging of moving targets. It is a parametric algorithm based on a very flexible data model which takes into account arbitrary range migration and arbitrary phase errors across the synthetic aperture that may be induced by unwanted radial motion of the target as well as propagation or system instability. AUTOCLEAN can be classified as a multiple scatterer algorithm (MSA), but it differs considerably from other existing MSAs in several aspects: (1) dominant scatterers are selected automatically in the two-dimensional (2-D) image domain; (2) scatterers may not be well-isolated or very dominant; (3) phase and RCS (radar cross section) information from each selected scatterer are combined in an optimal way; (4) the troublesome phase unwrapping step is avoided. AUTOCLEAN is computationally efficient and involves only a sequence of FFTs (fast Fourier Transforms). Another good feature associated with AUTOCLEAN is that its performance can be progressively improved by assuming a larger number of dominant scatterers for the target. Hence it can be easily configured for real-time applications including, for example, ATR (automatic target recognition) of non-cooperative moving targets, and for some other applications where the image quality is of the major concern but not the computational time including, for example, for the development and maintenance of low observable aircrafts. Numerical and experimental results have shown that AUTOCLEAN is a very robust autofocus tool for ISAR imaging.

flexsurv: A Platform for Parametric Survival Modeling in R

PubMed Central

Jackson, Christopher H.

2018-01-01

flexsurv is an R package for fully-parametric modeling of survival data. Any parametric time-to-event distribution may be fitted if the user supplies a probability density or hazard function, and ideally also their cumulative versions. Standard survival distributions are built in, including the three and four-parameter generalized gamma and F distributions. Any parameter of any distribution can be modeled as a linear or log-linear function of covariates. The package also includes the spline model of Royston and Parmar (2002), in which both baseline survival and covariate effects can be arbitrarily flexible parametric functions of time. The main model-fitting function, flexsurvreg, uses the familiar syntax of survreg from the standard survival package (Therneau 2016). Censoring or left-truncation are specified in ‘Surv’ objects. The models are fitted by maximizing the full log-likelihood, and estimates and confidence intervals for any function of the model parameters can be printed or plotted. flexsurv also provides functions for fitting and predicting from fully-parametric multi-state models, and connects with the mstate package (de Wreede, Fiocco, and Putter 2011). This article explains the methods and design principles of the package, giving several worked examples of its use. PMID:29593450

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

NASA Astrophysics Data System (ADS)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

Activation of the Parieto-Premotor Network Is Associated with Vivid Motor Imagery—A Parametric fMRI Study

PubMed Central

Lorey, Britta; Pilgramm, Sebastian; Bischoff, Matthias; Stark, Rudolf; Vaitl, Dieter; Kindermann, Stefan; Munzert, Jörn; Zentgraf, Karen

2011-01-01

The present study examined the neural basis of vivid motor imagery with parametrical functional magnetic resonance imaging. 22 participants performed motor imagery (MI) of six different right-hand movements that differed in terms of pointing accuracy needs and object involvement, i.e., either none, two big or two small squares had to be pointed at in alternation either with or without an object grasped with the fingers. After each imagery trial, they rated the perceived vividness of motor imagery on a 7-point scale. Results showed that increased perceived imagery vividness was parametrically associated with increasing neural activation within the left putamen, the left premotor cortex (PMC), the posterior parietal cortex of the left hemisphere, the left primary motor cortex, the left somatosensory cortex, and the left cerebellum. Within the right hemisphere, activation was found within the right cerebellum, the right putamen, and the right PMC. It is concluded that the perceived vividness of MI is parametrically associated with neural activity within sensorimotor areas. The results corroborate the hypothesis that MI is an outcome of neural computations based on movement representations located within motor areas. PMID:21655298

Sgr A* Emission Parametrizations from GRMHD Simulations

NASA Astrophysics Data System (ADS)

Anantua, Richard; Ressler, Sean; Quataert, Eliot

2018-06-01

Galactic Center emission near the vicinity of the central black hole, Sagittarius (Sgr) A*, is modeled using parametrizations involving the electron temperature, which is found from general relativistic magnetohydrodynamic (GRMHD) simulations to be highest in the disk-outflow corona. Jet-motivated prescriptions generalizing equipartition of particle and magnetic energies, e.g., by scaling relativistic electron energy density to powers of the magnetic field strength, are also introduced. GRMHD jet (or outflow)/accretion disk/black hole (JAB) simulation postprocessing codes IBOTHROS and GRMONTY are employed in the calculation of images and spectra. Various parametric models reproduce spectral and morphological features, such as the sub-mm spectral bump in electron temperature models and asymmetric photon rings in equipartition-based models. The Event Horizon Telescope (EHT) will provide unprecedentedly high-resolution 230+ GHz observations of the "shadow" around Sgr A*'s supermassive black hole, which the synthetic models presented here will reverse-engineer. Both electron temperature and equipartition-based models can be constructed to be compatible with EHT size constraints for the emitting region of Sgr A*. This program sets the groundwork for devising a unified emission parametrization flexible enough to model disk, corona and outflow/jet regions with a small set of parameters including electron heating fraction and plasma beta.

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

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

Coolens, Catherine, E-mail: catherine.coolens@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario

2015-01-01

Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from amore » 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150.5) %. Conclusions: Parametric voxel-based analysis of 4D DCE CT data resulted in greater accuracy and reliability in measuring changes in perfusion CT-based kinetic metrics, which have the potential to be used as biomarkers in patients with metastatic brain cancer.« less

Influence of signal intensity non-uniformity on brain volumetry using an atlas-based method.

PubMed

Goto, Masami; Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.

Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

PubMed Central

Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Objective Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. PMID:22778560

Chain Rule Approach for Calculating the Time-Derivative of Flux

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

Langenbrunner, James R.; Booker, Jane M.

The reaction history (gamma-flux observable) is mathematically studied by using the chain rule for taking the total-time derivatives. That is, the total time-derivative of flux is written as the product of the ion temperature derivative with respect to time and the derivative of the flux with respect to ion temperature. Some equations are derived using the further simplification that the fusion reactivity is a parametrized function of ion temperature, T. Deuterium-tritium (D-T) fusion is used as the application with reactivity calculations from three established reactivity parametrizations.

Depth-resolved imaging of colon tumor using optical coherence tomography and fluorescence laminar optical tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tang, Qinggong; Frank, Aaron; Wang, Jianting; Chen, Chao-wei; Jin, Lily; Lin, Jon; Chan, Joanne M.; Chen, Yu

2016-03-01

Early detection of neoplastic changes remains a critical challenge in clinical cancer diagnosis and treatment. Many cancers arise from epithelial layers such as those of the gastrointestinal (GI) tract. Current standard endoscopic technology is unable to detect those subsurface lesions. Since cancer development is associated with both morphological and molecular alterations, imaging technologies that can quantitative image tissue's morphological and molecular biomarkers and assess the depth extent of a lesion in real time, without the need for tissue excision, would be a major advance in GI cancer diagnostics and therapy. In this research, we investigated the feasibility of multi-modal optical imaging including high-resolution optical coherence tomography (OCT) and depth-resolved high-sensitivity fluorescence laminar optical tomography (FLOT) for structural and molecular imaging. APC (adenomatous polyposis coli) mice model were imaged using OCT and FLOT and the correlated histopathological diagnosis was obtained. Quantitative structural (the scattering coefficient) and molecular imaging parameters (fluorescence intensity) from OCT and FLOT images were developed for multi-parametric analysis. This multi-modal imaging method has demonstrated the feasibility for more accurate diagnosis with 87.4% (87.3%) for sensitivity (specificity) which gives the most optimal diagnosis (the largest area under receiver operating characteristic (ROC) curve). This project results in a new non-invasive multi-modal imaging platform for improved GI cancer detection, which is expected to have a major impact on detection, diagnosis, and characterization of GI cancers, as well as a wide range of epithelial cancers.

Towards an acoustic model-based poroelastic imaging method: I. Theoretical foundation.

PubMed

Berry, Gearóid P; Bamber, Jeffrey C; Armstrong, Cecil G; Miller, Naomi R; Barbone, Paul E

2006-04-01

The ultrasonic measurement and imaging of tissue elasticity is currently under wide investigation and development as a clinical tool for the assessment of a broad range of diseases, but little account in this field has yet been taken of the fact that soft tissue is porous and contains mobile fluid. The ability to squeeze fluid out of tissue may have implications for conventional elasticity imaging, and may present opportunities for new investigative tools. When a homogeneous, isotropic, fluid-saturated poroelastic material with a linearly elastic solid phase and incompressible solid and fluid constituents is subjected to stress, the behaviour of the induced internal strain field is influenced by three material constants: the Young's modulus (E(s)) and Poisson's ratio (nu(s)) of the solid matrix and the permeability (k) of the solid matrix to the pore fluid. New analytical expressions were derived and used to model the time-dependent behaviour of the strain field inside simulated homogeneous cylindrical samples of such a poroelastic material undergoing sustained unconfined compression. A model-based reconstruction technique was developed to produce images of parameters related to the poroelastic material constants (E(s), nu(s), k) from a comparison of the measured and predicted time-dependent spatially varying radial strain. Tests of the method using simulated noisy strain data showed that it is capable of producing three unique parametric images: an image of the Poisson's ratio of the solid matrix, an image of the axial strain (which was not time-dependent subsequent to the application of the compression) and an image representing the product of the aggregate modulus E(s)(1-nu(s))/(1+nu(s))(1-2nu(s)) of the solid matrix and the permeability of the solid matrix to the pore fluid. The analytical expressions were further used to numerically validate a finite element model and to clarify previous work on poroelastography.

Stick balancing with reflex delay in case of parametric forcing

NASA Astrophysics Data System (ADS)

Insperger, Tamas

2011-04-01

The effect of parametric forcing on a PD control of an inverted pendulum is analyzed in the presence of feedback delay. The stability of the time-periodic and time-delayed system is determined numerically using the first-order semi-discretization method in the 5-dimensional parameter space of the pendulum's length, the forcing frequency, the forcing amplitude, the proportional and the differential gains. It is shown that the critical length of the pendulum (that can just be balanced against the time-delay) can significantly be decreased by parametric forcing even if the maximum forcing acceleration is limited. The numerical analysis showed that the critical stick length about 30 cm corresponding to the unforced system with reflex delay 0.1 s can be decreased to 18 cm with keeping maximum acceleration below the gravitational acceleration.

Parametric Characterization of Flow Inside Cererbal Aneurysms Treated with Flow-Diverting Stents

NASA Astrophysics Data System (ADS)

Barbour, Michael; Levitt, Michael; Geindreau, Christian; Johnson, Luke; Chivukula, Keshav; Aliseda, Alberto

2017-11-01

Cerebral aneurysms are often treated with a flow-diverting stent (FDS) to reduce blood flow into the aneurysm sac, promoting the development of a stable thrombus. Successful treatment is highly dependent on the degree of flow reduction and the altered hemodynamics inside the aneurysm sac following treatment. Establishing a causal connection between hemodynamic metrics of FDS-treated CAs and long-term clinical outcomes requires a rigorous parametric characterization of this flow environment. We use 3D particle image velocimetry (PIV) to measure the flow inside idealized aneurysm models treated with FDS. Physiologically realistic Reynolds numbers and increasing levels of parent vessel curvature are analyzed to understand the effect of inertia on flow development. The flow velocity into the aneurysm and the topology of the flow inside the sac is shown to be highly dependent on parent vessel Dean number (De). The role of flow pulsatility is then added to the study via time-dependent waveforms. Velocity measurements at 2 values of parent vessel Womersley number (Wo) allow us to parameterize flow inside of CAs treated with FDS as a function of De, Re and Wo, improving the fundamental understanding of how FDS alter CA hemodynamics and aiding in the development of new treatments.

2D Unstructured Grid Based Constrained Inversion of Magnetic Data Using Fuzzy C Means Clustering and Lithology Classification

NASA Astrophysics Data System (ADS)

Kumar, V.; Singh, A.; Sharma, S. P.

2016-12-01

Regular grid discretization is often utilized to define complex geological models. However, this subdivision strategy performs at lower precision to represent the topographical observation surface. We have developed a new 2D unstructured grid based inversion for magnetic data for models including topography. It will consolidate prior parametric information into a deterministic inversion system to enhance the boundary between the different lithology based on recovered magnetic susceptibility distribution from the inversion. The presented susceptibility model will satisfy both the observed magnetic data and parametric information and therefore can represent the earth better than geophysical inversion models that only honor the observed magnetic data. Geophysical inversion and lithology classification are generally treated as two autonomous methodologies and connected in a serial way. The presented inversion strategy integrates these two parts into a unified scheme. To reduce the storage space and computation time, the conjugate gradient method is used. It results in feasible and practical imaging inversion of magnetic data to deal with large number of triangular grids. The efficacy of the presented inversion is demonstrated using two synthetic examples and one field data example.

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

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

Ren, S; Tianjin University, Tianjin; Hara, W

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2)more » electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.« less

Nondestructive and Real-time Measurement of Moisture in Plant

NASA Astrophysics Data System (ADS)

Ogawa, Yuichi; Kawase, Kodo; Mizuno, Maya; Yamashita, Masatsugu; Otani, Chiko

We constructed a THz transillumination system for water content monitoring, and we succeeded in measuring the moisture level in plants. Our measurement system uses a widely tunable coherent THz parametric oscillator source. As target we chose for this experiment a leaf of Japanese basil. The time variation of the water content in the leaf was monitored in two situations: a leaf freshly cut which is left to dry out, and the leaf of a water stressed plant. We found by real-time measurements that the water content of a cut leaf does not decrease uniformly in time. Also, the response to water stress is delayed by about 5-10 minutes. Furthermore, we demonstrated a moisture measurement using a transillumination THz imaging system. As target we chose for this experiment a leaf of Hedera helix held between two thin plastic sheets. The change of the moisture distribution is clearly visible. These results show that the method described here can be applied to nondestructive and real-time monitoring of water content in plants.

Differential diagnosis of normal pressure hydrocephalus by MRI mean diffusivity histogram analysis.

PubMed

Ivkovic, M; Liu, B; Ahmed, F; Moore, D; Huang, C; Raj, A; Kovanlikaya, I; Heier, L; Relkin, N

2013-01-01

Accurate diagnosis of normal pressure hydrocephalus is challenging because the clinical symptoms and radiographic appearance of NPH often overlap those of other conditions, including age-related neurodegenerative disorders such as Alzheimer and Parkinson diseases. We hypothesized that radiologic differences between NPH and AD/PD can be characterized by a robust and objective MR imaging DTI technique that does not require intersubject image registration or operator-defined regions of interest, thus avoiding many pitfalls common in DTI methods. We collected 3T DTI data from 15 patients with probable NPH and 25 controls with AD, PD, or dementia with Lewy bodies. We developed a parametric model for the shape of intracranial mean diffusivity histograms that separates brain and ventricular components from a third component composed mostly of partial volume voxels. To accurately fit the shape of the third component, we constructed a parametric function named the generalized Voss-Dyke function. We then examined the use of the fitting parameters for the differential diagnosis of NPH from AD, PD, and DLB. Using parameters for the MD histogram shape, we distinguished clinically probable NPH from the 3 other disorders with 86% sensitivity and 96% specificity. The technique yielded 86% sensitivity and 88% specificity when differentiating NPH from AD only. An adequate parametric model for the shape of intracranial MD histograms can distinguish NPH from AD, PD, or DLB with high sensitivity and specificity.

Accurate analysis and visualization of cardiac (11)C-PIB uptake in amyloidosis with semiautomatic software.

PubMed

Kero, Tanja; Lindsjö, Lars; Sörensen, Jens; Lubberink, Mark

2016-08-01

(11)C-PIB PET is a promising non-invasive diagnostic tool for cardiac amyloidosis. Semiautomatic analysis of PET data is now available but it is not known how accurate these methods are for amyloid imaging. The aim of this study was to evaluate the feasibility of one semiautomatic software tool for analysis and visualization of (11)C-PIB left ventricular retention index (RI) in cardiac amyloidosis. Patients with systemic amyloidosis and cardiac involvement (n = 10) and healthy controls (n = 5) were investigated with dynamic (11)C-PIB PET. Two observers analyzed the PET studies with semiautomatic software to calculate the left ventricular RI of (11)C-PIB and to create parametric images. The mean RI at 15-25 min from the semiautomatic analysis was compared with RI based on manual analysis and showed comparable values (0.056 vs 0.054 min(-1) for amyloidosis patients and 0.024 vs 0.025 min(-1) in healthy controls; P = .78) and the correlation was excellent (r = 0.98). Inter-reader reproducibility also was excellent (intraclass correlation coefficient, ICC > 0.98). Parametric polarmaps and histograms made visual separation of amyloidosis patients and healthy controls fast and simple. Accurate semiautomatic analysis of cardiac (11)C-PIB RI in amyloidosis patients is feasible. Parametric polarmaps and histograms make visual interpretation fast and simple.

Changing space and sound: Parametric design and variable acoustics

NASA Astrophysics Data System (ADS)

Norton, Christopher William

This thesis examines the potential for parametric design software to create performance based design using acoustic metrics as the design criteria. A former soundstage at the University of Southern California used by the Thornton School of Music is used as a case study for a multiuse space for orchestral, percussion, master class and recital use. The criteria used for each programmatic use include reverberation time, bass ratio, and the early energy ratios of the clarity index and objective support. Using a panelized ceiling as a design element to vary the parameters of volume, panel orientation and type of absorptive material, the relationships between these parameters and the design criteria are explored. These relationships and subsequently derived equations are applied to Grasshopper parametric modeling software for Rhino 3D (a NURBS modeling software). Using the target reverberation time and bass ratio for each programmatic use as input for the parametric model, the genomic optimization function of Grasshopper - Galapagos - is run to identify the optimum ceiling geometry and material distribution.

First Demonstration of Electrostatic Damping of Parametric Instability at Advanced LIGO

NASA Astrophysics Data System (ADS)

Blair, Carl; Gras, Slawek; Abbott, Richard; Aston, Stuart; Betzwieser, Joseph; Blair, David; DeRosa, Ryan; Evans, Matthew; Frolov, Valera; Fritschel, Peter; Grote, Hartmut; Hardwick, Terra; Liu, Jian; Lormand, Marc; Miller, John; Mullavey, Adam; O'Reilly, Brian; Zhao, Chunnong; Abbott, B. P.; Abbott, T. D.; Adams, C.; Adhikari, R. X.; Anderson, S. B.; Ananyeva, A.; Appert, S.; Arai, K.; Ballmer, S. W.; Barker, D.; Barr, B.; Barsotti, L.; Bartlett, J.; Bartos, I.; Batch, J. C.; Bell, A. S.; Billingsley, G.; Birch, J.; Biscans, S.; Biwer, C.; Bork, R.; Brooks, A. F.; Ciani, G.; Clara, F.; Countryman, S. T.; Cowart, M. J.; Coyne, D. C.; Cumming, A.; Cunningham, L.; Danzmann, K.; Da Silva Costa, C. F.; Daw, E. J.; DeBra, D.; DeSalvo, R.; Dooley, K. L.; Doravari, S.; Driggers, J. C.; Dwyer, S. E.; Effler, A.; Etzel, T.; Evans, T. M.; Factourovich, M.; Fair, H.; Fernández Galiana, A.; Fisher, R. P.; Fulda, P.; Fyffe, M.; Giaime, J. A.; Giardina, K. D.; Goetz, E.; Goetz, R.; Gray, C.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, E. D.; Hammond, G.; Hanks, J.; Hanson, J.; Harry, G. M.; Heintze, M. C.; Heptonstall, A. W.; Hough, J.; Izumi, K.; Jones, R.; Kandhasamy, S.; Karki, S.; Kasprzack, M.; Kaufer, S.; Kawabe, K.; Kijbunchoo, N.; King, E. J.; King, P. J.; Kissel, J. S.; Korth, W. Z.; Kuehn, G.; Landry, M.; Lantz, B.; Lockerbie, N. A.; Lundgren, A. P.; MacInnis, M.; Macleod, D. M.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martin, I. W.; Martynov, D. V.; Mason, K.; Massinger, T. J.; Matichard, F.; Mavalvala, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McIntyre, G.; McIver, J.; Mendell, G.; Merilh, E. L.; Meyers, P. M.; Mittleman, R.; Moreno, G.; Mueller, G.; Munch, J.; Nuttall, L. K.; Oberling, J.; Oppermann, P.; Oram, Richard J.; Ottaway, D. J.; Overmier, H.; Palamos, J. R.; Paris, H. R.; Parker, W.; Pele, A.; Penn, S.; Phelps, M.; Pierro, V.; Pinto, I.; Principe, M.; Prokhorov, L. G.; Puncken, O.; Quetschke, V.; Quintero, E. A.; Raab, F. J.; Radkins, H.; Raffai, P.; Reid, S.; Reitze, D. H.; Robertson, N. A.; Rollins, J. G.; Roma, V. J.; Romie, J. H.; Rowan, S.; Ryan, K.; Sadecki, T.; Sanchez, E. J.; Sandberg, V.; Savage, R. L.; Schofield, R. M. S.; Sellers, D.; Shaddock, D. A.; Shaffer, T. J.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sigg, D.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Sorazu, B.; Staley, A.; Strain, K. A.; Tanner, D. B.; Taylor, R.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Torrie, C. I.; Traylor, G.; Vajente, G.; Valdes, G.; van Veggel, A. A.; Vecchio, A.; Veitch, P. J.; Venkateswara, K.; Vo, T.; Vorvick, C.; Walker, M.; Ward, R. L.; Warner, J.; Weaver, B.; Weiss, R.; Weßels, P.; Willke, B.; Wipf, C. C.; Worden, J.; Wu, G.; Yamamoto, H.; Yancey, C. C.; Yu, Hang; Yu, Haocun; Zhang, L.; Zucker, M. E.; Zweizig, J.; LSC Instrument Authors

2017-04-01

Interferometric gravitational wave detectors operate with high optical power in their arms in order to achieve high shot-noise limited strain sensitivity. A significant limitation to increasing the optical power is the phenomenon of three-mode parametric instabilities, in which the laser field in the arm cavities is scattered into higher-order optical modes by acoustic modes of the cavity mirrors. The optical modes can further drive the acoustic modes via radiation pressure, potentially producing an exponential buildup. One proposed technique to stabilize parametric instability is active damping of acoustic modes. We report here the first demonstration of damping a parametrically unstable mode using active feedback forces on the cavity mirror. A 15 538 Hz mode that grew exponentially with a time constant of 182 sec was damped using electrostatic actuation, with a resulting decay time constant of 23 sec. An average control force of 0.03 nN was required to maintain the acoustic mode at its minimum amplitude.

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Triaxial ellipsoid dimensions and rotational poles of seven asteroids from Lick Observatory adaptive optics images, and of Ceres

NASA Astrophysics Data System (ADS)

Drummond, Jack; Christou, Julian

2008-10-01

Seven main belt asteroids, 2 Pallas, 3 Juno, 4 Vesta, 16 Psyche, 87 Sylvia, 324 Bamberga, and 707 Interamnia, were imaged with the adaptive optics system on the 3 m Shane telescope at Lick Observatory in the near infrared, and their triaxial ellipsoid dimensions and rotational poles have been determined with parametric blind deconvolution. In addition, the dimensions and pole for 1 Ceres are derived from resolved images at multiple epochs, even though it is an oblate spheroid.

ERTS direct readout ground station study

NASA Technical Reports Server (NTRS)

1971-01-01

A system configuration which provides for a wide variety of user requirements is described. Two distinct user types are considered and optimized configurations are provided. Independent satellite transmission systems allow simultaneous signal transmission to Regional Collection Centers via a high data rate channel and to local users who require near real time consumption of lower rate data. In order to maximize the ultimate utility of this study effort, a parametric system description is given such that in essence a shopping list is provided. To achieve these results, it was necessary to consider all technical disciplines associated with high resolution satellite imaging systems including signal processing, modulation and coding, recording, and display techniques. A total systems study was performed.

Sizing up Asteroids at Lick Observatory with Adaptive Optics

NASA Astrophysics Data System (ADS)

Drummond, Jack D.; Christou, J.

2006-12-01

Using the Shane 3 meter telescope with adaptive optics at Lick Observatory, we have determined the triaxial dimensions and rotational poles of five asteroids, 3 Juno, 4 Vesta, 16 Psyche, 87 Sylvia, and 324 Bamberga. Parametric blind deconvolution was applied to images obtained mostly at 2.5 microns in 2004 and 2006. This is the first time Bamberga’s pole has been determined, and the results for the other four asteroids are in agreement with the analysis of decades of lightcurves by others. The techniques developed here to find sizes, shapes, and poles, in only one or two nights, can be applied to smaller asteroids that are resolved with larger telescopes.

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study

NASA Astrophysics Data System (ADS)

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-03-01

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

Multi-parametric monitoring and assessment of High Intensity Focused Ultrasound (HIFU) boiling by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): An ex vivo feasibility study

PubMed Central

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-01-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase-shift during high energy HIFU treatment with tissue boiling. Forty three (n=43) thermal lesions were formed in ex vivo canine liver specimens (n=28). Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-s, 20-s and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and Passive Cavitation Detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δφ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite unpredictable changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property change throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes. PMID:24556974

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study.

PubMed

Hou, Gary Y; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E

2014-03-07

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

Quantitative imaging of protein targets in the human brain with PET

NASA Astrophysics Data System (ADS)

Gunn, Roger N.; Slifstein, Mark; Searle, Graham E.; Price, Julie C.

2015-11-01

PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts, partial volume effects, age effects, image registration and normalization, input functions and metabolites, parametric imaging, receptor internalization and genetic factors.

Teledetection passive et processus decisionnel a reference spatiale: Application a l'aquaculture en milieu marin

NASA Astrophysics Data System (ADS)

Habbane, Mohamed

L'objectif de cette etude est d'elaborer un processus decisionnel a reference spatiale (PDRS) pour la mariculture. Le PDRS est applique aux eaux cotieres de la baie des Chaleurs, dans le golfe du Saint-Laurent (Canada). Une carte preliminaire regionale d'indices du potentiel maricole, d'une limite de resolution spatiale de 1 kmsp2, est produite avec des parametres du niveau 1. Ces parametres englobent la temperature de l'eau de surface, extraite des images AVHRR, la salinite, les courants ainsi que les pigments chlorophylliens, quantifies a l'aide de mesures in situ. Les images AVHRR, prises en 1994, ont ete utiliees comme reference primaire pour selectionner des aires pouvant supporter une activite maricole sur la cote nord de la baie des Chaleurs. La temperature de surface extraite de ces images permet une analyse mesoechelle a la fois qualitative et quantitative des processus cotiers observes pendant la periode d'acquisition des donnees. Les autres donnees, soit la salinite, les courants et les concentrations en pigments chlorophylliens, sont analysees de facon a identifier la variabilite spatio-temporelle des caracteristiques des eaux de surface. L'ensemble des informations permet de produire une carte preliminaire regionale d'indices du potentiel maricole de la partie centrale de la baie des Chaleurs. Selon cet indice (defini entre 0 et 1), le secteur de potentiel aquicole de 0,5 a 0,75 s'etend sur une superficie d'environ 300 kmsp2. La localisation de cette aire potentielle est en accord avec les fortes concentrations en pigments chlrophylliens, presentant des conditions environnementales ideales a une haute productivite biologique. Par la suite la carte preliminaire est modifiee en tenant compte des parametres du niveau 2. Ces parametres sont la geomorphologie littorale, la bathymetrie, les sediments en suspension, les vents, les vagues, le debit d'eau douce, la glace marine, le carbone organique dissous, les aires de peche et les sources de pollution. Ces parametres sont compares deux a deux par rapport a la carte preliminaire regionale d'indices du potentiel maricole pour determiner leur poids relatif. La carte finale produite avec ces parametres du niveau 2 presente un secteur ou les indices du potentiel maricole sont de 0,5 a 0,75. Ce secteur longe la cote et epouse les isobathes de 10 a 30 m de profondeur. L'effet de la profondeur d'eau semble avoir jouer un role important. Le secteur de potentiel maricole de 0,25 a 0,5 est toujours present et couvre une superficie d'environ 426 kmsp2. L'etude necessitera toujours un suivi des conditions environnementales prevalant dans la region. Ce suivi peut etre effectue a l'aide d'un outil de vision aerospatiale (capteurs de teledetection) et d'analyse spatio-temporelle (SIG-PDRS). (Abstract shortened by UMI.)

A novel semiconductor-based, fully incoherent amplified spontaneous emission light source for ghost imaging

PubMed Central

Hartmann, Sébastien; Elsäßer, Wolfgang

2017-01-01

Initially, ghost imaging (GI) was demonstrated with entangled light from parametric down conversion. Later, classical light sources were introduced with the development of thermal light GI concepts. State-of-the-art classical GI light sources rely either on complex combinations of coherent light with spatially randomizing optical elements or on incoherent lamps with monochromating optics, however suffering strong losses of efficiency and directionality. Here, a broad-area superluminescent diode is proposed as a new light source for classical ghost imaging. The coherence behavior of this spectrally broadband emitting opto-electronic light source is investigated in detail. An interferometric two-photon detection technique is exploited in order to resolve the ultra-short correlation timescales. We thereby quantify the coherence time, the photon statistics as well as the number of spatial modes unveiling a complete incoherent light behavior. With a one-dimensional proof-of-principle GI experiment, we introduce these compact emitters to the field which could be beneficial for high-speed GI systems as well as for long range GI sensing in future applications. PMID:28150737

Fluid flow in porous media using image-based modelling to parametrize Richards' equation.

PubMed

Cooper, L J; Daly, K R; Hallett, P D; Naveed, M; Koebernick, N; Bengough, A G; George, T S; Roose, T

2017-11-01

The parameters in Richards' equation are usually calculated from experimentally measured values of the soil-water characteristic curve and saturated hydraulic conductivity. The complex pore structures that often occur in porous media complicate such parametrization due to hysteresis between wetting and drying and the effects of tortuosity. Rather than estimate the parameters in Richards' equation from these indirect measurements, image-based modelling is used to investigate the relationship between the pore structure and the parameters. A three-dimensional, X-ray computed tomography image stack of a soil sample with voxel resolution of 6 μm has been used to create a computational mesh. The Cahn-Hilliard-Stokes equations for two-fluid flow, in this case water and air, were applied to this mesh and solved using the finite-element method in COMSOL Multiphysics. The upscaled parameters in Richards' equation are then obtained via homogenization. The effect on the soil-water retention curve due to three different contact angles, 0°, 20° and 60°, was also investigated. The results show that the pore structure affects the properties of the flow on the large scale, and different contact angles can change the parameters for Richards' equation.

Does transitioning from computed radiography (CR) to direct radiography (DR) with portable imaging systems affect workflow efficiency?

NASA Astrophysics Data System (ADS)

Gali, Raja L.; Roth, Christopher G.; Smith, Elizabeth; Dave, Jaydev K.

2018-03-01

In digital radiography, computed radiography (CR) technology is based on latent image capture by storage phosphors whereas direct radiography (DR) technology is based either on indirect conversion using a scintillator or direct conversion using a photoconductor. DR-based portable imaging systems may enhance workflow efficiency. The purpose of this work was to investigate changes in workflow efficiency at a tertiary healthcare center after transitioning from CR to DR technology for imaging with portable x-ray units. An IRB exemption was obtained. Data for all inpatient-radiographs acquired with portable x-ray units from July-2014 till June-2015 (period 1) with CR technology (AMX4 or AMX4+ portable unit from GE Healthcare, NX workstation from Agfa Healthcare for digitization), from July-2015 till June-2016 (period 2) with DR technology (Carestream DRX-Revolution x-ray units and DRX-1C image receptors) and from July-2016 till January-2017 (period 3; same DR technology) were extracted using Centricity RIS-IC (GE Healthcare). Duration between the imaging-examination scheduled time and completed time (timesch-com) was calculated and compared using non-parametric tests (between the three time periods with corrections for multiple comparisons; three time periods were used to identify if there were any other potential temporal trends not related to transitioning from CR to DR). IBM's SPSS package was used for statistical analysis. Overall data was obtained from 33131, 32194, and 18015 cases in periods 1, 2 and 3, respectively. Independent-Samples Kruskal-Wallis test revealed a statistically significant difference in timesch-com across the three time periods (χ2(2, n= 83,340) = 2053, p < 0.001). The timesch-com was highest for period 1 i.e., radiographs acquired with CR technology (median: 64 minutes) and it decreased significantly for radiographs acquired with DR technology in periods 2 (median: 49 minutes; p < 0.001) and 3 (median∶ 44 minutes; p < 0.001). Overall, adoption of DR technology resulted in a drop in timesch-com by 27% relative to the use of CR technology. Transitioning from CR to DR was associated with improved workflow efficiency for radiographic imaging with portable x-ray units.

Known-component 3D-2D registration for quality assurance of spine surgery pedicle screw placement

NASA Astrophysics Data System (ADS)

Uneri, A.; De Silva, T.; Stayman, J. W.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Gokaslan, Z. L.; Wolinsky, J.-P.; Siewerdsen, J. H.

2015-10-01

A 3D-2D image registration method is presented that exploits knowledge of interventional devices (e.g. K-wires or spine screws—referred to as ‘known components’) to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product. The known-component registration (KC-Reg) algorithm uses robust 3D-2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g. approximation of a screw as a simple cylinder, referred to as ‘parametrically-known’ component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as ‘exactly-known’ component [eKC] registration). 3D-2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the ‘acceptance window’ of the spinal pedicle. Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1-4 mm and  <5° using simple parametric (pKC) models, further improved to  <1 mm and  <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of  >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach. 3D-2D registration combined with 3D models of known surgical devices offers a novel method for intraoperative QA. The method provides a near-real-time independent check against pedicle breach, facilitating revision within the same procedure if necessary and providing more rigorous verification of the surgical product.

A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series

NASA Astrophysics Data System (ADS)

Rovira, F.; Palau, J. L.; Millán, M.

2009-09-01

Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original time series by using the Fourier transform of the modelled signal. Acknowledgements The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (València, Spain). This study has been partially funded by the European Commission (FP VI, Integrated Project CIRCE - No. 036961) and by the Ministerio de Ciencia e Innovación, research projects "TRANSREG” (CGL2007-65359/CLI) and "GRACCIE” (CSD2007-00067, Program CONSOLIDER-INGENIO 2010).

Simultaneous water activation and glucose metabolic rate imaging with PET

NASA Astrophysics Data System (ADS)

Verhaeghe, Jeroen; Reader, Andrew J.

2013-02-01

A novel imaging and signal separation strategy is proposed to be able to separate [18F]FDG and multiple [15O]H2O signals from a simultaneously acquired dynamic PET acquisition of the two tracers. The technique is based on the fact that the dynamics of the two tracers are very distinct. By adopting an appropriate bolus injection strategy and by defining tailored sets of basis functions that model either the FDG or water component, it is possible to separate the FDG and water signal. The basis functions are inspired from the spectral analysis description of dynamic PET studies and are defined as the convolution of estimated generating functions (GFs) with a set of decaying exponential functions. The GFs are estimated from the overall measured head curve, while the decaying exponential functions are pre-determined. In this work, the time activity curves (TACs) are modelled post-reconstruction but the model can be incorporated in a global 4D reconstruction strategy. Extensive PET simulation studies are performed considering single [18F]FDG and 6 [15O]H2O bolus injections for a total acquisition time of 75 min. The proposed method is evaluated at multiple noise levels and different parameters were estimated such as [18F]FDG uptake and blood flow estimated from the [15O]H2O component, requiring a full dynamic analysis of the two components, static images of [18F]FDG and the water components as well as [15O]H2O activation. It is shown that the resulting images and parametric values in ROIs are comparable to images obtained from separate imaging, illustrating the feasibility of simultaneous imaging of [18F]FDG and [15O]H2O components. For more information on this article, see medicalphysicsweb.org

An extensive photometric catalogue of CALIFA galaxies

NASA Astrophysics Data System (ADS)

Gilhuly, Colleen; Courteau, Stéphane

2018-06-01

We present an extensive compendium of photometrically determined structural properties for all Calar Alto Legacy Integral Field spectroscopy Area (CALIFA) galaxies in the third data release (DR3). We exploit Sloan Digital Sky Survey (SDSS) images in order to extract one-dimensional (1D) gri surface brightness profiles for all CALIFA DR3 galaxies. We also derive a variety of non-parametric quantities and parametric models fitted to 1D i-band profiles. The galaxy images are decomposed using the 2D bulge-disc decomposition programs IMFIT and GALFIT. The relative performance and merit of our 1D and 2D modelling approaches are assessed. Where possible, we compare and augment our photometry with existing measurements from the literature. Close agreement is generally found with the studies of Walcher et al. and Méndez-Abreu et al., though some significant differences exist. Various structural metrics are also highlighted on account of their tight dispersion against an independent variable, such as the circular velocity.

Optical coherence tomography can assess skeletal muscle tissue from mouse models of muscular dystrophy by parametric imaging of the attenuation coefficient

PubMed Central

Klyen, Blake R.; Scolaro, Loretta; Shavlakadze, Tea; Grounds, Miranda D.; Sampson, David D.

2014-01-01

We present the assessment of ex vivo mouse muscle tissue by quantitative parametric imaging of the near-infrared attenuation coefficient µt using optical coherence tomography. The resulting values of the local total attenuation coefficient µt (mean ± standard error) from necrotic lesions in the dystrophic skeletal muscle tissue of mdx mice are higher (9.6 ± 0.3 mm−1) than regions from the same tissue containing only necrotic myofibers (7.0 ± 0.6 mm−1), and significantly higher than values from intact myofibers, whether from an adjacent region of the same sample (4.8 ± 0.3 mm−1) or from healthy tissue of the wild-type C57 mouse (3.9 ± 0.2 mm−1) used as a control. Our results suggest that the attenuation coefficient could be used as a quantitative means to identify necrotic lesions and assess skeletal muscle tissue in mouse models of human Duchenne muscular dystrophy. PMID:24761302

Method to improve optical parametric oscillator beam quality

DOEpatents

Smith, Arlee V.; Alford, William J.; Bowers, Mark S.

2003-11-11

A method to improving optical parametric oscillator (OPO) beam quality having an optical pump, which generates a pump beam at a pump frequency greater than a desired signal frequency, a nonlinear optical medium oriented so that a signal wave at the desired signal frequency and a corresponding idler wave are produced when the pump beam (wave) propagates through the nonlinear optical medium, resulting in beam walk off of the signal and idler waves, and an optical cavity which directs the signal wave to repeatedly pass through the nonlinear optical medium, said optical cavity comprising an equivalently even number of non-planar mirrors that produce image rotation on each pass through the nonlinear optical medium. Utilizing beam walk off where the signal wave and said idler wave have nonparallel Poynting vectors in the nonlinear medium and image rotation, a correlation zone of distance equal to approximately .rho.L.sub.crystal is created which, through multiple passes through the nonlinear medium, improves the beam quality of the OPO output.

Optical parametric osicllators with improved beam quality

DOEpatents

Smith, Arlee V.; Alford, William J.

2003-11-11

An optical parametric oscillator (OPO) having an optical pump, which generates a pump beam at a pump frequency greater than a desired signal frequency, a nonlinear optical medium oriented so that a signal wave at the desired signal frequency and a corresponding idler wave are produced when the pump beam (wave) propagates through the nonlinear optical medium, resulting in beam walk off of the signal and idler waves, and an optical cavity which directs the signal wave to repeatedly pass through the nonlinear optical medium, said optical cavity comprising an equivalently even number of non-planar mirrors that produce image rotation on each pass through the nonlinear optical medium. Utilizing beam walk off where the signal wave and said idler wave have nonparallel Poynting vectors in the nonlinear medium and image rotation, a correlation zone of distance equal to approximately .rho.L.sub.crystal is created which, through multiple passes through the nonlinear medium, improves the beam quality of the OPO output.

H0LiCOW – IV. Lens mass model of HE 0435-1223 and blind measurement of its time-delay distance for cosmology

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

Wong, Kenneth C.; Suyu, Sherry H.; Auger, Matthew W.

Strong gravitational lenses with measured time delays between the multiple images allow a direct measurement of the time-delay distance to the lens, and thus a measure of cosmological parameters, particularly the Hubble constant, H0. We present a blind lens model analysis of the quadruply imaged quasar lens HE 0435-1223 using deep Hubble Space Telescope imaging, updated time-delay measurements from the COSmological MOnitoring of GRAvItational Lenses (COSMOGRAIL), a measurement of the velocity dispersion of the lens galaxy based on Keck data, and a characterization of the mass distribution along the line of sight. HE 0435-1223 is the third lens analysed as a part of the H0 Lenses in COSMOGRAIL's Wellspring (H0LiCOW) project. We account for various sources of systematic uncertainty, including the detailed treatment of nearby perturbers, the parametrization of the galaxy light and mass profile, and the regions used for lens modelling. We constrain the effective time-delay distance to be D Δt=2612more » $$+208\\atop{-191}$$Mpc, a precision of 7.6 per cent. From HE 0435-1223 alone, we infer a Hubble constant of H 0=73.1$$+5.7\\atop{-6.0}$$kms -1Mpc -1 assuming a flat ΛCDM cosmology. Lastly, the cosmographic inference based on the three lenses analysed by H0LiCOW to date is presented in a companion paper (H0LiCOW Paper V).« less

H0LiCOW – IV. Lens mass model of HE 0435-1223 and blind measurement of its time-delay distance for cosmology

DOE PAGES

Wong, Kenneth C.; Suyu, Sherry H.; Auger, Matthew W.; ...

2016-11-29

Strong gravitational lenses with measured time delays between the multiple images allow a direct measurement of the time-delay distance to the lens, and thus a measure of cosmological parameters, particularly the Hubble constant, H0. We present a blind lens model analysis of the quadruply imaged quasar lens HE 0435-1223 using deep Hubble Space Telescope imaging, updated time-delay measurements from the COSmological MOnitoring of GRAvItational Lenses (COSMOGRAIL), a measurement of the velocity dispersion of the lens galaxy based on Keck data, and a characterization of the mass distribution along the line of sight. HE 0435-1223 is the third lens analysed as a part of the H0 Lenses in COSMOGRAIL's Wellspring (H0LiCOW) project. We account for various sources of systematic uncertainty, including the detailed treatment of nearby perturbers, the parametrization of the galaxy light and mass profile, and the regions used for lens modelling. We constrain the effective time-delay distance to be D Δt=2612more » $$+208\\atop{-191}$$Mpc, a precision of 7.6 per cent. From HE 0435-1223 alone, we infer a Hubble constant of H 0=73.1$$+5.7\\atop{-6.0}$$kms -1Mpc -1 assuming a flat ΛCDM cosmology. Lastly, the cosmographic inference based on the three lenses analysed by H0LiCOW to date is presented in a companion paper (H0LiCOW Paper V).« less

Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach.

PubMed

Katiyar, Prateek; Divine, Mathew R; Kohlhofer, Ursula; Quintanilla-Martinez, Leticia; Schölkopf, Bernhard; Pichler, Bernd J; Disselhorst, Jonathan A

2017-04-01

In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18 F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18 F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18 F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18 F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor heterogeneity using dynamic PET studies. Because SC tumor segmentation is based on the intrinsic structure of the underlying data, it can be easily applied to other cancer types as well. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Spatiotemporal structure of biphoton entanglement in type-II parametric down-conversion

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

Brambilla, E.; Caspani, L.; Lugiato, L. A.

2010-07-15

We investigate the spatiotemporal structure of the biphoton correlation in type-II parametric down-conversion (PDC). As in type-I PDC [Phys. Rev. Lett. 102, 223601 (2009)], we find that the correlation is nonfactorizable in space and time. Differently from type I, the type-II correlation in the spontaneous regime displays an asymmetric V-shaped structure in any cross section including time and one transverse dimension. This asymmetry along the temporal coordinate originates from the signal-idler group velocity mismatch and tends to disappear as the parametric gain is raised. We observe a progressive transition toward a symmetric X-shaped geometry similar to that found in typemore » I when stimulated PDC becomes dominant. We also give quantitative evaluations of the localization in space and in time of the correlation, analyze its behavior for different crystal tuning angles, and underline qualitative differences with respect to type-I PDC.« less

Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

PubMed

Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

2009-02-01

One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

Limits on estimating the width of thin tubular structures in 3D images.

PubMed

Wörz, Stefan; Rohr, Karl

2006-01-01

This work studies limits on estimating the width of thin tubular structures in 3D images. Based on nonlinear estimation theory we analyze the minimal stochastic error of estimating the width. Given a 3D analytic model of the image intensities of tubular structures, we derive a closed-form expression for the Cramér-Rao bound of the width estimate under image noise. We use the derived lower bound as a benchmark and compare it with three previously proposed accuracy limits for vessel width estimation. Moreover, by experimental investigations we demonstrate that the derived lower bound can be achieved by fitting a 3D parametric intensity model directly to the image data.

Imaging non-Gaussian output fields produced by Josephson parametric amplifiers: experiments

NASA Astrophysics Data System (ADS)

Toyli, D. M.; Venkatramani, A. V.; Boutin, S.; Eddins, A.; Didier, N.; Clerk, A. A.; Blais, A.; Siddiqi, I.

2015-03-01

In recent years, squeezed microwave states have become the focus of intense research motivated by applications in continuous-variables quantum computation and precision qubit measurement. Despite numerous demonstrations of vacuum squeezing with superconducting parametric amplifiers such as the Josephson parametric amplifier (JPA), most experiments have also suggested that the squeezed output field becomes non-ideal at the large (> 10dB) signal gains required for low-noise qubit measurement. Here we describe a systematic experimental study of JPA squeezing performance in this regime for varying lumped-element device designs and pumping methods. We reconstruct the JPA output fields through homodyne detection of the field moments and quantify the deviations from an ideal squeezed state using maximal entropy techniques. These methods provide a powerful diagnostic tool to understand how effects such as gain compression impact JPA squeezing. Our results highlight the importance of weak device nonlinearity for generating highly squeezed states. This work is supported by ARO and ONR.

A novel SURE-based criterion for parametric PSF estimation.

PubMed

Xue, Feng; Blu, Thierry

2015-02-01

We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

Non-Parametric Collision Probability for Low-Velocity Encounters

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

2007-01-01

An implicit, but not necessarily obvious, assumption in all of the current techniques for assessing satellite collision probability is that the relative position uncertainty is perfectly correlated in time. If there is any mis-modeling of the dynamics in the propagation of the relative position error covariance matrix, time-wise de-correlation of the uncertainty will increase the probability of collision over a given time interval. The paper gives some examples that illustrate this point. This paper argues that, for the present, Monte Carlo analysis is the best available tool for handling low-velocity encounters, and suggests some techniques for addressing the issues just described. One proposal is for the use of a non-parametric technique that is widely used in actuarial and medical studies. The other suggestion is that accurate process noise models be used in the Monte Carlo trials to which the non-parametric estimate is applied. A further contribution of this paper is a description of how the time-wise decorrelation of uncertainty increases the probability of collision.

EEG Correlates of Fluctuation in Cognitive Performance in an Air Traffic Control Task

DTIC Science & Technology

2014-11-01

using non-parametric statistical analysis to identify neurophysiological patterns due to the time-on-task effect. Significant changes in EEG power...EEG, Cognitive Performance, Power Spectral Analysis , Non-Parametric Analysis Document is available to the public through the Internet...3 Performance Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 EEG

Distributional Effects of Word Frequency on Eye Fixation Durations

ERIC Educational Resources Information Center

Staub, Adrian; White, Sarah J.; Drieghe, Denis; Hollway, Elizabeth C.; Rayner, Keith

2010-01-01

Recent research using word recognition paradigms, such as lexical decision and speeded pronunciation, has investigated how a range of variables affect the location and shape of response time distributions, using both parametric and non-parametric techniques. In this article, we explore the distributional effects of a word frequency manipulation on…

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

PubMed

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

All-fiber optical parametric oscillator for bio-medical imaging applications

NASA Astrophysics Data System (ADS)

Gottschall, Thomas; Meyer, Tobias; Jauregui, Cesar; Just, Florian; Eidam, Tino; Schmitt, Michael; Popp, Jürgen; Limpert, Jens; Tünnermann, Andreas

2017-02-01

Among other modern imaging techniques, stimulated Raman Scattering (SRS) requires an extremely quiet, widely wavelength tunable laser, which, up to now, is unheard of in fiber laser systems. We present a compact all-fiber laser system, which features an optical parametric oscillator (OPO) based on degenerate four-wave mixing (FWM) in an endlessly single-mode photonic-crystal fiber. We employ an all-fiber frequency and repetition rate tunable laser in order to enable wideband conversion in the linear OPO cavity arrangement, the signal and idler radiation can be tuned between 764 and 960 nm and 1164 and 1552 nm at 9.5 MHz. Thus, all biochemically relevant Raman shifts between 922 and 3322 cm-1 may be addressed in combination with a secondary output, which is tunable between 1024 and 1052 nm. This ultra-low noise output emits synchronized pulses with twice the repetition rate to enable SRS imaging. We measure the relative intensity noise of this output beam at 9.5 MHz to be between -145 and -148 dBc, which is low enough to enable high-speed SRS imaging with a good signal-to-noise ratio. The laser system is computer controlled to access a certain energy differences within one second. Combining FWM based conversion, with all-fiber Yb-based fiber lasers enables the construction of the first automated, turn-key and widely tunable fiber laser. This laser concept could be the missing piece to establish CRS imaging as a reliable guiding tool for clinical diagnostics and surgical guidance.

Parametric resonance in the early Universe—a fitting analysis

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

Figueroa, Daniel G.; Torrentí, Francisco, E-mail: daniel.figueroa@cern.ch, E-mail: f.torrenti@csic.es

Particle production via parametric resonance in the early Universe, is a non-perturbative, non-linear and out-of-equilibrium phenomenon. Although it is a well studied topic, whenever a new scenario exhibits parametric resonance, a full re-analysis is normally required. To avoid this tedious task, many works present often only a simplified linear treatment of the problem. In order to surpass this circumstance in the future, we provide a fitting analysis of parametric resonance through all its relevant stages: initial linear growth, non-linear evolution, and relaxation towards equilibrium. Using lattice simulations in an expanding grid in 3+1 dimensions, we parametrize the dynamics' outcome scanningmore » over the relevant ingredients: role of the oscillatory field, particle coupling strength, initial conditions, and background expansion rate. We emphasize the inaccuracy of the linear calculation of the decay time of the oscillatory field, and propose a more appropriate definition of this scale based on the subsequent non-linear dynamics. We provide simple fits to the relevant time scales and particle energy fractions at each stage. Our fits can be applied to post-inflationary preheating scenarios, where the oscillatory field is the inflaton, or to spectator-field scenarios, where the oscillatory field can be e.g. a curvaton, or the Standard Model Higgs.« less

Intervening on risk factors for coronary heart disease: an application of the parametric g-formula.

PubMed

Taubman, Sarah L; Robins, James M; Mittleman, Murray A; Hernán, Miguel A

2009-12-01

Estimating the population risk of disease under hypothetical interventions--such as the population risk of coronary heart disease (CHD) were everyone to quit smoking and start exercising or to start exercising if diagnosed with diabetes--may not be possible using standard analytic techniques. The parametric g-formula, which appropriately adjusts for time-varying confounders affected by prior exposures, is especially well suited to estimating effects when the intervention involves multiple factors (joint interventions) or when the intervention involves decisions that depend on the value of evolving time-dependent factors (dynamic interventions). We describe the parametric g-formula, and use it to estimate the effect of various hypothetical lifestyle interventions on the risk of CHD using data from the Nurses' Health Study. Over the period 1982-2002, the 20-year risk of CHD in this cohort was 3.50%. Under a joint intervention of no smoking, increased exercise, improved diet, moderate alcohol consumption and reduced body mass index, the estimated risk was 1.89% (95% confidence interval: 1.46-2.41). We discuss whether the assumptions required for the validity of the parametric g-formula hold in the Nurses' Health Study data. This work represents the first large-scale application of the parametric g-formula in an epidemiologic cohort study.

Optical parametric amplification of arbitrarily polarized light in periodically poled LiNbO3.

PubMed

Shao, Guang-hao; Song, Xiao-shi; Xu, Fei; Lu, Yan-qing

2012-08-13

Optical parametric amplification (OPA) of arbitrarily polarized light is proposed in a multi-section periodically poled Lithium Niobate (PPLN). External electric field is applied on selected sections to induce the polarization rotation of involved lights, thus the quasi-phase matched optical parametric processes exhibit polarization insensitivity under suitable voltage. In addition to the amplified signal wave, an idler wave with the same polarization is generated simultaneously. As an example, a ~10 times OPA showing polarization independency is simulated. Applications of this technology are also discussed.

Imaging predictors of poststroke depression: methodological factors in voxel-based analysis

PubMed Central

Gozzi, Sophia A; Wood, Amanda G; Chen, Jian; Vaddadi, Krishnarao; Phan, Thanh G

2014-01-01

Objective The purpose of this study was to explore the relationship between lesion location and poststroke depression using statistical parametric mapping. Methods First episode patients with stroke were assessed within 12 days and at 1-month poststroke. Patients with an a priori defined cut-off score of 11 on the Hospital Anxiety and Depression Scale (HADS) at follow-up were further assessed using the Mini-International Neuropsychiatric Interview (MINI) to confirm a clinical diagnosis of major or minor depression in accordance with Diagnostic and Statistical Manual-IV (DSM-IV) inclusion criteria. Participants were included if they were aged 18–85 years, proficient in English and eligible for MRI. Patients were excluded if they had a confounding diagnosis such as major depressive disorder at the time of admission, a neurodegenerative disease, epilepsy or an imminently life-threatening comorbid illness, subarachnoid or subdural stroke, a second episode of stroke before follow-up and/or a serious impairment of consciousness or language. Infarcts observed on MRI scans were manually segmented into binary images, linearly registered into a common stereotaxic coordinate space. Using statistical parametric mapping, we compared infarct patterns in patients with stroke with and without depression. Results 27% (15/55 patients) met criteria for depression at follow-up. Mean infarct volume was 19±53 mL and National Institute of Health Stroke Scale (NIHSS) at Time 1 (within 12 days of stroke) was 4±4, indicating a sample of mild strokes. No voxels or clusters were significant after a multiple comparison correction was applied (p>0.05). Examination of infarct maps showed that there was minimal overlap of infarct location between patients, thus invalidating the voxel comparison analysis. Conclusions This study provided inconclusive evidence for the association between infarcts in a specific region and poststroke depression. PMID:25001395

The Choroid Plexus of the Lateral Ventricle As the Origin of CSF Pulsation Is Questionable.

PubMed

Takizawa, Ken; Matsumae, Mitsunori; Hayashi, Naokazu; Hirayama, Akihiro; Sano, Fumiya; Yatsushiro, Satoshi; Kuroda, Kagayaki

2018-01-15

The advent of magnetic resonance imaging (MRI) enables noninvasive measurement of cerebrospinal fluid (CSF) motion, and new information about CSF motion has now been acquired. The driving force of the CSF has long been thought to be choroid plexus (CP) pulsation, but to investigate whether this phenomenon actually occurs, CSF motion was observed in the ventricular system and subarachnoid space using MRI. Eleven healthy volunteers, ranging in age from 23 to 58 years, participated in this study. The MRI sequences used were four-dimensional phase-contrast (4D-PC) and time-spatial labeling inversion pulse (t-SLIP). The 4D-PC images included sagittal images in the cranial midline, coronal images focusing on the foramen of Monro (FOM), and oblique coronal images of the trigone to quantify CSF velocity and acceleration. These values were compared and analyzed as non-parametric data using the Kolmogorov-Smirnov test and the Mann-Whitney U test. 4D-PC showed that the median CSF velocity was significantly lower in the posterior part of the lateral ventricle than in other regions. The quantitative analysis of velocity and acceleration showed that they were decreased around the CP in the trigone. Image analysis of both velocity mapping and t-SLIP showed suppressed CSF motion around the CP in the trigone. These findings cast doubt on CP pulsation being the driving force for CSF motion.

Tomographic digital subtraction angiography for lung perfusion estimation in rodents.

PubMed

Badea, Cristian T; Hedlund, Laurence W; De Lin, Ming; Mackel, Julie S Boslego; Samei, Ehsan; Johnson, G Allan

2007-05-01

In vivo measurements of perfusion present a challenge to existing small animal imaging techniques such as magnetic resonance microscopy, micro computed tomography, micro positron emission tomography, and microSPECT, due to combined requirements for high spatial and temporal resolution. We demonstrate the use of tomographic digital subtraction angiography (TDSA) for estimation of perfusion in small animals. TDSA augments conventional digital subtraction angiography (DSA) by providing three-dimensional spatial information using tomosynthesis algorithms. TDSA is based on the novel paradigm that the same time density curves can be reproduced in a number of consecutive injections of microL volumes of contrast at a series of different angles of rotation. The capabilities of TDSA are established in studies on lung perfusion in rats. Using an imaging system developed in-house, we acquired data for four-dimensional (4D) imaging with temporal resolution of 140 ms, in-plane spatial resolution of 100 microm, and slice thickness on the order of millimeters. Based on a structured experimental approach, we optimized TDSA imaging providing a good trade-off between slice thickness, the number of injections, contrast to noise, and immunity to artifacts. Both DSA and TDSA images were used to create parametric maps of perfusion. TDSA imaging has potential application in a number of areas where functional perfusion measurements in 4D can provide valuable insight into animal models of disease and response to therapeutics.

The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans

PubMed Central

Boes, Jennifer L.; Bule, Maria; Hoff, Benjamin A.; Chamberlain, Ryan; Lynch, David A.; Stojanovska, Jadranka; Martinez, Fernando J.; Han, Meilan K.; Kazerooni, Ella A.; Ross, Brian D.; Galbán, Craig J.

2015-01-01

Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPD-Gene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. PMID:26568983

Electrical Evaluation of RCA MWS5001D Random Access Memory, Volume 5, Appendix D

NASA Technical Reports Server (NTRS)

Klute, A.

1979-01-01

The electrical characterization and qualification test results are presented for the RCA MWS 5001D random access memory. The tests included functional tests, AC and DC parametric tests, AC parametric worst-case pattern selection test, determination of worst-case transition for setup and hold times, and a series of schmoo plots. Average input high current, worst case input high current, output low current, and data setup time are some of the results presented.

A parametric ribcage geometry model accounting for variations among the adult population.

PubMed

Wang, Yulong; Cao, Libo; Bai, Zhonghao; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2016-09-06

The objective of this study is to develop a parametric ribcage model that can account for morphological variations among the adult population. Ribcage geometries, including 12 pair of ribs, sternum, and thoracic spine, were collected from CT scans of 101 adult subjects through image segmentation, landmark identification (1016 for each subject), symmetry adjustment, and template mesh mapping (26,180 elements for each subject). Generalized procrustes analysis (GPA), principal component analysis (PCA), and regression analysis were used to develop a parametric ribcage model, which can predict nodal locations of the template mesh according to age, sex, height, and body mass index (BMI). Two regression models, a quadratic model for estimating the ribcage size and a linear model for estimating the ribcage shape, were developed. The results showed that the ribcage size was dominated by the height (p=0.000) and age-sex-interaction (p=0.007) and the ribcage shape was significantly affected by the age (p=0.0005), sex (p=0.0002), height (p=0.0064) and BMI (p=0.0000). Along with proper assignment of cortical bone thickness, material properties and failure properties, this parametric ribcage model can directly serve as the mesh of finite element ribcage models for quantifying effects of human characteristics on thoracic injury risks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Variance based joint sparsity reconstruction of synthetic aperture radar data for speckle reduction

NASA Astrophysics Data System (ADS)

Scarnati, Theresa; Gelb, Anne

2018-04-01

In observing multiple synthetic aperture radar (SAR) images of the same scene, it is apparent that the brightness distributions of the images are not smooth, but rather composed of complicated granular patterns of bright and dark spots. Further, these brightness distributions vary from image to image. This salt and pepper like feature of SAR images, called speckle, reduces the contrast in the images and negatively affects texture based image analysis. This investigation uses the variance based joint sparsity reconstruction method for forming SAR images from the multiple SAR images. In addition to reducing speckle, the method has the advantage of being non-parametric, and can therefore be used in a variety of autonomous applications. Numerical examples include reconstructions of both simulated phase history data that result in speckled images as well as the images from the MSTAR T-72 database.

Topography of brain glucose hypometabolism and epileptic network in glucose transporter 1 deficiency.

PubMed

Akman, Cigdem Inan; Provenzano, Frank; Wang, Dong; Engelstad, Kristin; Hinton, Veronica; Yu, Julia; Tikofsky, Ronald; Ichese, Masonari; De Vivo, Darryl C

2015-02-01

(18)F fluorodeoxyglucose positron emission tomography ((18)F FDG-PET) facilitates examination of glucose metabolism. Previously, we described regional cerebral glucose hypometabolism using (18)F FDG-PET in patients with Glucose transporter 1 Deficiency Syndrome (Glut1 DS). We now expand this observation in Glut1 DS using quantitative image analysis to identify the epileptic network based on the regional distribution of glucose hypometabolism. (18)F FDG-PET scans of 16 Glut1 DS patients and 7 healthy participants were examined using Statistical parametric Mapping (SPM). Summed images were preprocessed for statistical analysis using MATLAB 7.1 and SPM 2 software. Region of interest (ROI) analysis was performed to validate SPM results. Visual analysis of the (18)F FDG-PET images demonstrated prominent regional glucose hypometabolism in the thalamus, neocortical regions and cerebellum bilaterally. Group comparison using SPM analysis confirmed that the regional distribution of glucose hypo-metabolism was present in thalamus, cerebellum, temporal cortex and central lobule. Two mildly affected patients without epilepsy had hypometabolism in cerebellum, inferior frontal cortex, and temporal lobe, but not thalamus. Glucose hypometabolism did not correlate with age at the time of PET imaging, head circumference, CSF glucose concentration at the time of diagnosis, RBC glucose uptake, or CNS score. Quantitative analysis of (18)F FDG-PET imaging in Glut1 DS patients confirmed that hypometabolism was present symmetrically in thalamus, cerebellum, frontal and temporal cortex. The hypometabolism in thalamus correlated with the clinical history of epilepsy. Copyright © 2014. Published by Elsevier B.V.

The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

NASA Technical Reports Server (NTRS)

Maluf, David A.; Cheeseman, Peter; Smelyanskyi, Vadim N.; Kuehnel, Frank; Morris, Robin D.; Norvig, Peter (Technical Monitor)

2001-01-01

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

GPS Imaging of Global Vertical Land Motion for Sea Level Studies

NASA Astrophysics Data System (ADS)

Hammond, W. C.; Blewitt, G.; Hamlington, B. D.

2015-12-01

Coastal vertical land motion contributes to the signal of local relative sea level change. Moreover, understanding global sea level change requires understanding local sea level rise at many locations around Earth. It is therefore essential to understand the regional secular vertical land motion attributable to mantle flow, tectonic deformation, glacial isostatic adjustment, postseismic viscoelastic relaxation, groundwater basin subsidence, elastic rebound from groundwater unloading or other processes that can change the geocentric height of tide gauges anchored to the land. These changes can affect inferences of global sea level rise and should be taken into account for global projections. We present new results of GPS imaging of vertical land motion across most of Earth's continents including its ice-free coastlines around North and South America, Europe, Australia, Japan, parts of Africa and Indonesia. These images are based on data from many independent open access globally distributed continuously recording GPS networks including over 13,500 stations. The data are processed in our system to obtain solutions aligned to the International Terrestrial Reference Frame (ITRF08). To generate images of vertical rate we apply the Median Interannual Difference Adjusted for Skewness (MIDAS) algorithm to the vertical times series to obtain robust non-parametric estimates with realistic uncertainties. We estimate the vertical land motion at the location of 1420 tide gauges locations using Delaunay-based geographic interpolation with an empirically derived distance weighting function and median spatial filtering. The resulting image is insensitive to outliers and steps in the GPS time series, omits short wavelength features attributable to unstable stations or unrepresentative rates, and emphasizes long-wavelength mantle-driven vertical rates.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Adaptive time-sequential binary sensing for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Hu, Chenhui; Lu, Yue M.

2012-06-01

We present a novel image sensor for high dynamic range imaging. The sensor performs an adaptive one-bit quantization at each pixel, with the pixel output switched from 0 to 1 only if the number of photons reaching that pixel is greater than or equal to a quantization threshold. With an oracle knowledge of the incident light intensity, one can pick an optimal threshold (for that light intensity) and the corresponding Fisher information contained in the output sequence follows closely that of an ideal unquantized sensor over a wide range of intensity values. This observation suggests the potential gains one may achieve by adaptively updating the quantization thresholds. As the main contribution of this work, we propose a time-sequential threshold-updating rule that asymptotically approaches the performance of the oracle scheme. With every threshold mapped to a number of ordered states, the dynamics of the proposed scheme can be modeled as a parametric Markov chain. We show that the frequencies of different thresholds converge to a steady-state distribution that is concentrated around the optimal choice. Moreover, numerical experiments show that the theoretical performance measures (Fisher information and Craḿer-Rao bounds) can be achieved by a maximum likelihood estimator, which is guaranteed to find globally optimal solution due to the concavity of the log-likelihood functions. Compared with conventional image sensors and the strategy that utilizes a constant single-photon threshold considered in previous work, the proposed scheme attains orders of magnitude improvement in terms of sensor dynamic ranges.

A Parametric Oscillator Experiment for Undergraduates

NASA Astrophysics Data System (ADS)

Huff, Alison; Thompson, Johnathon; Pate, Jacob; Kim, Hannah; Chiao, Raymond; Sharping, Jay

We describe an upper-division undergraduate-level analytic mechanics experiment or classroom demonstration of a weakly-damped pendulum driven into parametric resonance. Students can derive the equations of motion from first principles and extract key oscillator features, such as quality factor and parametric gain, from experimental data. The apparatus is compact, portable and easily constructed from inexpensive components. Motion control and data acquisition are accomplished using an Arduino micro-controller incorporating a servo motor, laser sensor, and data logger. We record the passage time of the pendulum through its equilibrium position and obtain the maximum speed per oscillation as a function of time. As examples of the interesting physics which the experiment reveals, we present contour plots depicting the energy of the system as functions of driven frequency and modulation depth. We observe the transition to steady state oscillation and compare the experimental oscillation threshold with theoretical expectations. A thorough understanding of this hands-on laboratory exercise provides a foundation for current research in quantum information and opto-mechanics, where damped harmonic motion, quality factor, and parametric amplification are central.

What Does Distractibility in ADHD Reveal about Mechanisms for Top-Down Attentional Control?

ERIC Educational Resources Information Center

Friedman-Hill, Stacia R.; Wagman, Meryl R.; Gex, Saskia E.; Pine, Daniel S.; Leibenluft, Ellen; Ungerleider, Leslie G.

2010-01-01

In this study, we attempted to clarify whether distractibility in ADHD might arise from increased sensory-driven interference or from inefficient top-down control. We employed an attentional filtering paradigm in which discrimination difficulty and distractor salience (amount of image "graying") were parametrically manipulated. Increased…

Integrated transrectal probe for translational ultrasound-photoacoustic imaging

NASA Astrophysics Data System (ADS)

Bell, Kevan L.; Harrison, Tyler; Usmani, Nawaid; Zemp, Roger J.

2016-03-01

A compact photoacoustic transrectal probe is constructed for improved imaging in brachytherapy treatment. A 192 element 5 MHz linear transducer array is mounted inside a small 3D printed casing along with an array of optical fibers. The device is fed by a pump laser and tunable NIR-optical parametric oscillator with data collected by a Verasonics ultrasound platform. This assembly demonstrates improved imaging of brachytherapy seeds in phantoms with depths up to 5 cm. The tuneable excitation in combination with standard US integration provides adjustable contrast between the brachytherapy seeds, blood filled tubes and background tissue.

Non-parametric adaptative JPEG fragments carving

NASA Astrophysics Data System (ADS)

Amrouche, Sabrina Cherifa; Salamani, Dalila

2018-04-01

The most challenging JPEG recovery tasks arise when the file header is missing. In this paper we propose to use a two layer machine learning model to restore headerless JPEG images. We first build a classifier able to identify the structural properties of the images/fragments and then use an AutoEncoder (AE) to learn the fragment features for the header prediction. We define a JPEG universal header and the remaining free image parameters (Height, Width) are predicted with a Gradient Boosting Classifier. Our approach resulted in 90% accuracy using the manually defined features and 78% accuracy using the AE features.

Impact of state updating and multi-parametric ensemble for streamflow hindcasting in European river basins

NASA Astrophysics Data System (ADS)

Noh, S. J.; Rakovec, O.; Kumar, R.; Samaniego, L. E.

2015-12-01

Accurate and reliable streamflow prediction is essential to mitigate social and economic damage coming from water-related disasters such as flood and drought. Sequential data assimilation (DA) may facilitate improved streamflow prediction using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. However, if parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by model ensemble may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we evaluate impacts of streamflow data assimilation over European river basins. Especially, a multi-parametric ensemble approach is tested to consider the effects of parametric uncertainty in DA. Because augmentation of parameters is not required within an assimilation window, the approach could be more stable with limited ensemble members and have potential for operational uses. To consider the response times and non-Gaussian characteristics of internal hydrologic processes, lagged particle filtering is utilized. The presentation will be focused on gains and limitations of streamflow data assimilation and multi-parametric ensemble method over large-scale basins.

STAPP: Spatiotemporal analysis of plantar pressure measurements using statistical parametric mapping.

PubMed

Booth, Brian G; Keijsers, Noël L W; Sijbers, Jan; Huysmans, Toon

2018-05-03

Pedobarography produces large sets of plantar pressure samples that are routinely subsampled (e.g. using regions of interest) or aggregated (e.g. center of pressure trajectories, peak pressure images) in order to simplify statistical analysis and provide intuitive clinical measures. We hypothesize that these data reductions discard gait information that can be used to differentiate between groups or conditions. To test the hypothesis of null information loss, we created an implementation of statistical parametric mapping (SPM) for dynamic plantar pressure datasets (i.e. plantar pressure videos). Our SPM software framework brings all plantar pressure videos into anatomical and temporal correspondence, then performs statistical tests at each sampling location in space and time. Novelly, we introduce non-linear temporal registration into the framework in order to normalize for timing differences within the stance phase. We refer to our software framework as STAPP: spatiotemporal analysis of plantar pressure measurements. Using STAPP, we tested our hypothesis on plantar pressure videos from 33 healthy subjects walking at different speeds. As walking speed increased, STAPP was able to identify significant decreases in plantar pressure at mid-stance from the heel through the lateral forefoot. The extent of these plantar pressure decreases has not previously been observed using existing plantar pressure analysis techniques. We therefore conclude that the subsampling of plantar pressure videos - a task which led to the discarding of gait information in our study - can be avoided using STAPP. Copyright © 2018 Elsevier B.V. All rights reserved.

An interactive local flattening operator to support digital investigations on artwork surfaces.

PubMed

Pietroni, Nico; Massimiliano, Corsini; Cignoni, Paolo; Scopigno, Roberto

2011-12-01

Analyzing either high-frequency shape detail or any other 2D fields (scalar or vector) embedded over a 3D geometry is a complex task, since detaching the detail from the overall shape can be tricky. An alternative approach is to move to the 2D space, resolving shape reasoning to easier image processing techniques. In this paper we propose a novel framework for the analysis of 2D information distributed over 3D geometry, based on a locally smooth parametrization technique that allows us to treat local 3D data in terms of image content. The proposed approach has been implemented as a sketch-based system that allows to design with a few gestures a set of (possibly overlapping) parameterizations of rectangular portions of the surface. We demonstrate that, due to the locality of the parametrization, the distortion is under an acceptable threshold, while discontinuities can be avoided since the parametrized geometry is always homeomorphic to a disk. We show the effectiveness of the proposed technique to solve specific Cultural Heritage (CH) tasks: the analysis of chisel marks over the surface of a unfinished sculpture and the local comparison of multiple photographs mapped over the surface of an artwork. For this very difficult task, we believe that our framework and the corresponding tool are the first steps toward a computer-based shape reasoning system, able to support CH scholars with a medium they are more used to. © 2011 IEEE

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Stochastic stability of parametrically excited random systems

NASA Astrophysics Data System (ADS)

Labou, M.

2004-01-01

Multidegree-of-freedom dynamic systems subjected to parametric excitation are analyzed for stochastic stability. The variation of excitation intensity with time is described by the sum of a harmonic function and a stationary random process. The stability boundaries are determined by the stochastic averaging method. The effect of random parametric excitation on the stability of trivial solutions of systems of differential equations for the moments of phase variables is studied. It is assumed that the frequency of harmonic component falls within the region of combination resonances. Stability conditions for the first and second moments are obtained. It turns out that additional parametric excitation may have a stabilizing or destabilizing effect, depending on the values of certain parameters of random excitation. As an example, the stability of a beam in plane bending is analyzed.

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Automatic assessment of dynamic contrast-enhanced MRI in an ischemic rat hindlimb model: an exploratory study of transplanted multipotent progenitor cells.

PubMed

Hsu, Li-Yueh; Wragg, Andrew; Anderson, Stasia A; Balaban, Robert S; Boehm, Manfred; Arai, Andrew E

2008-02-01

This study presents computerized automatic image analysis for quantitatively evaluating dynamic contrast-enhanced MRI in an ischemic rat hindlimb model. MRI at 7 T was performed on animals in a blinded placebo-controlled experiment comparing multipotent adult progenitor cell-derived progenitor cell (MDPC)-treated, phosphate buffered saline (PBS)-injected, and sham-operated rats. Ischemic and non-ischemic limb regions of interest were automatically segmented from time-series images for detecting changes in perfusion and late enhancement. In correlation analysis of the time-signal intensity histograms, the MDPC-treated limbs correlated well with their corresponding non-ischemic limbs. However, the correlation coefficient of the PBS control group was significantly lower than that of the MDPC-treated and sham-operated groups. In semi-quantitative parametric maps of contrast enhancement, there was no significant difference in hypo-enhanced area between the MDPC and PBS groups at early perfusion-dependent time frames. However, the late-enhancement area was significantly larger in the PBS than the MDPC group. The results of this exploratory study show that MDPC-treated rats could be objectively distinguished from PBS controls. The differences were primarily determined by late contrast enhancement of PBS-treated limbs. These computerized methods appear promising for assessing perfusion and late enhancement in dynamic contrast-enhanced MRI.

Dissociating neural variability related to stimulus quality and response times in perceptual decision-making.

PubMed

Bode, Stefan; Bennett, Daniel; Sewell, David K; Paton, Bryan; Egan, Gary F; Smith, Philip L; Murawski, Carsten

2018-03-01

According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Phase-sensitive fiber-based parametric all-optical switch.

PubMed

Parra-Cetina, Josué; Kumpera, Aleš; Karlsson, Magnus; Andrekson, Peter A

2015-12-28

We experimentally demonstrate, for the first time, an all-optical switch in a phase-sensitive fiber optic parametric amplifier operated in saturation. We study the effect of phase variation of the signal and idler waves on the pump power depletion. By changing the phase of a 0.9 mW signal/idler pair wave by π/2 rad, a pump power extinction ratio of 30.4 dB is achieved. Static and dynamic characterizations are also performed and time domain results presented.

Multi-channel lock-in amplifier assisted femtosecond time-resolved fluorescence non-collinear optical parametric amplification spectroscopy with efficient rejection of superfluorescence background.

PubMed

Mao, Pengcheng; Wang, Zhuan; Dang, Wei; Weng, Yuxiang

2015-12-01

Superfluorescence appears as an intense background in femtosecond time-resolved fluorescence noncollinear optical parametric amplification spectroscopy, which severely interferes the reliable acquisition of the time-resolved fluorescence spectra especially for an optically dilute sample. Superfluorescence originates from the optical amplification of the vacuum quantum noise, which would be inevitably concomitant with the amplified fluorescence photons during the optical parametric amplification process. Here, we report the development of a femtosecond time-resolved fluorescence non-collinear optical parametric amplification spectrometer assisted with a 32-channel lock-in amplifier for efficient rejection of the superfluorescence background. With this spectrometer, the superfluorescence background signal can be significantly reduced to 1/300-1/100 when the seeding fluorescence is modulated. An integrated 32-bundle optical fiber is used as a linear array light receiver connected to 32 photodiodes in one-to-one mode, and the photodiodes are further coupled to a home-built 32-channel synchronous digital lock-in amplifier. As an implementation, time-resolved fluorescence spectra for rhodamine 6G dye in ethanol solution at an optically dilute concentration of 10(-5)M excited at 510 nm with an excitation intensity of 70 nJ/pulse have been successfully recorded, and the detection limit at a pump intensity of 60 μJ/pulse was determined as about 13 photons/pulse. Concentration dependent redshift starting at 30 ps after the excitation in time-resolved fluorescence spectra of this dye has also been observed, which can be attributed to the formation of the excimer at a higher concentration, while the blueshift in the earlier time within 10 ps is attributed to the solvation process.

Multi-channel lock-in amplifier assisted femtosecond time-resolved fluorescence non-collinear optical parametric amplification spectroscopy with efficient rejection of superfluorescence background

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

Mao, Pengcheng; Wang, Zhuan; Dang, Wei

Superfluorescence appears as an intense background in femtosecond time-resolved fluorescence noncollinear optical parametric amplification spectroscopy, which severely interferes the reliable acquisition of the time-resolved fluorescence spectra especially for an optically dilute sample. Superfluorescence originates from the optical amplification of the vacuum quantum noise, which would be inevitably concomitant with the amplified fluorescence photons during the optical parametric amplification process. Here, we report the development of a femtosecond time-resolved fluorescence non-collinear optical parametric amplification spectrometer assisted with a 32-channel lock-in amplifier for efficient rejection of the superfluorescence background. With this spectrometer, the superfluorescence background signal can be significantly reduced to 1/300–1/100more » when the seeding fluorescence is modulated. An integrated 32-bundle optical fiber is used as a linear array light receiver connected to 32 photodiodes in one-to-one mode, and the photodiodes are further coupled to a home-built 32-channel synchronous digital lock-in amplifier. As an implementation, time-resolved fluorescence spectra for rhodamine 6G dye in ethanol solution at an optically dilute concentration of 10{sup −5}M excited at 510 nm with an excitation intensity of 70 nJ/pulse have been successfully recorded, and the detection limit at a pump intensity of 60 μJ/pulse was determined as about 13 photons/pulse. Concentration dependent redshift starting at 30 ps after the excitation in time-resolved fluorescence spectra of this dye has also been observed, which can be attributed to the formation of the excimer at a higher concentration, while the blueshift in the earlier time within 10 ps is attributed to the solvation process.« less

Towards the evidence of a purely spatial Einstein-Podolsky-Rosen paradox in images: measurement scheme and first experimental results

NASA Astrophysics Data System (ADS)

Devaux, F.; Mougin-Sisini, J.; Moreau, P. A.; Lantz, E.

2012-07-01

We propose a scheme to evidence the Einstein-Podolsky-Rosen (EPR) paradox for photons produced by spontaneous down conversion, from measurement of purely spatial correlations of photon positions both in the near- and in the far-field. Experimentally, quantum correlations have been measured in the far-field of parametric fluorescence created in a type II BBO crystal. Imaging is performed in the photon counting regime with an electron-multiplying CCD (EMCCD) camera.

Improving the Diagnostic Specificity of CT for Early Detection of Lung Cancer: 4D CT-Based Pulmonary Nodule Elastometry

DTIC Science & Technology

2015-10-01

malignant PNs treated with stereotactic ablative radiotherapy ( SABR ) with those of the lung. Methods: We analyzed breath-hold images of 30...patients with malignant PNs who underwent SABR in our department. A parametric nonrigid transformation model based on multi-level B-spline guided by Sum of...and 50 of 4D CT and deep inhale and natural exhale of breath-hold CT images of 30 MPN treated with stereotactic ablative radiotherapy ( SABR ). The

Transmural ultrasound imaging of thermal lesion and action potential changes in perfused canine cardiac wedge preparations by high intensity focused ultrasound ablation.

PubMed

Wu, Ziqi; Gudur, Madhu S R; Deng, Cheri X

2013-01-01

Intra-procedural imaging is important for guiding cardiac arrhythmia ablation. It is difficult to obtain intra-procedural correlation of thermal lesion formation with action potential (AP) changes in the transmural plane during ablation. This study tested parametric ultrasound imaging for transmural imaging of lesion and AP changes in high intensity focused ultrasound (HIFU) ablation using coronary perfused canine ventricular wedge preparations (n = 13). The preparations were paced from epi/endocardial surfaces and subjected to HIFU application (3.5 MHz, 11 Hz pulse-repetition-frequency, 70% duty cycle, duration 4 s, 3500 W/cm(2)), during which simultaneous optical mapping (1 kframes/s) using di-4-ANEPPS and ultrasound imaging (30 MHz) of the same transmural surface of the wedge were performed. Spatiotemporally correlated AP measurements and ultrasound imaging allowed quantification of the reduction of AP amplitude (APA), shortening of AP duration at 50% repolarization, AP triangulation, decrease of optical AP rise, and change of conduction velocity along tissue depth direction within and surrounding HIFU lesions. The threshold of irreversible change in APA correlating to lesions was determined to be 43 ± 1% with a receiver operating characteristic (ROC) area under curve (AUC) of 0.96 ± 0.01 (n = 13). Ultrasound imaging parameters such as integrated backscatter, Rayleigh (α) and log-normal (σ) parameters, cumulative extrema of σ were tested, with the cumulative extrema of σ performing the best in detecting lesion (ROC AUC 0.89 ± 0.01, n = 13) and change of APA (ROC AUC 0.79 ± 0.03, n = 13). In conclusion, characteristic tissue and AP changes in HIFU ablation were identified and spatiotemporally correlated using optical mapping and ultrasound imaging. Parametric ultrasound imaging using cumulative extrema of σ can detect HIFU lesion and APA reduction.

Transmural Ultrasound Imaging of Thermal Lesion and Action Potential Changes in Perfused Canine Cardiac Wedge Preparations by High Intensity Focused Ultrasound Ablation

PubMed Central

Wu, Ziqi; Gudur, Madhu S. R.; Deng, Cheri X.

2013-01-01

Intra-procedural imaging is important for guiding cardiac arrhythmia ablation. It is difficult to obtain intra-procedural correlation of thermal lesion formation with action potential (AP) changes in the transmural plane during ablation. This study tested parametric ultrasound imaging for transmural imaging of lesion and AP changes in high intensity focused ultrasound (HIFU) ablation using coronary perfused canine ventricular wedge preparations (n = 13). The preparations were paced from epi/endocardial surfaces and subjected to HIFU application (3.5 MHz, 11 Hz pulse-repetition-frequency, 70% duty cycle, duration 4 s, 3500 W/cm2), during which simultaneous optical mapping (1 kframes/s) using di-4-ANEPPS and ultrasound imaging (30 MHz) of the same transmural surface of the wedge were performed. Spatiotemporally correlated AP measurements and ultrasound imaging allowed quantification of the reduction of AP amplitude (APA), shortening of AP duration at 50% repolarization, AP triangulation, decrease of optical AP rise, and change of conduction velocity along tissue depth direction within and surrounding HIFU lesions. The threshold of irreversible change in APA correlating to lesions was determined to be 43±1% with a receiver operating characteristic (ROC) area under curve (AUC) of 0.96±0.01 (n = 13). Ultrasound imaging parameters such as integrated backscatter, Rayleigh (α) and log-normal (σ) parameters, cumulative extrema of σ were tested, with the cumulative extrema of σ performing the best in detecting lesion (ROC AUC 0.89±0.01, n = 13) and change of APA (ROC AUC 0.79±0.03, n = 13). In conclusion, characteristic tissue and AP changes in HIFU ablation were identified and spatiotemporally correlated using optical mapping and ultrasound imaging. Parametric ultrasound imaging using cumulative extrema of σ can detect HIFU lesion and APA reduction. PMID:24349337

Spatio-temporal distribution of global solar radiation for Mexico using GOES data

NASA Astrophysics Data System (ADS)

Bonifaz, R.; Cuahutle, M.; Valdes, M.; Riveros, D.

2013-05-01

Increased need of sustainable and renewable energies around the world requires studies about the amount and distribution of such types of energies. Global solar radiation distribution in space and time is a key component on order to know the availability of the energy for different applications. Using GOES hourly data, the heliosat model was implemented for Mexico. Details about the model and its components are discussed step by stem an once obtained the global solar radiation images, different time datasets (hourly, daily, monthly and seasonal) were built in order to know the spatio-temporal behavior of this type of energy. Preliminary maps of the available solar global radiation energy for Mexico are presented, the amount and variation of the solar radiation by regions are analyzed and discussed. Future work includes a better parametrization of the model using calibrated ground stations data and more use of more complex models for better results.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Parametric Amplifier and Oscillator Based on Josephson Junction Circuitry

NASA Astrophysics Data System (ADS)

Yamamoto, T.; Koshino, K.; Nakamura, Y.

While the demand for low-noise amplification is ubiquitous, applications where the quantum-limited noise performance is indispensable are not very common. Microwave parametric amplifiers with near quantum-limited noise performance were first demonstrated more than 20 years ago. However, there had been little effort until recently to improve the performance or the ease of use of these amplifiers, partly because of a lack of any urgent motivation. The emergence of the field of quantum information processing in superconducting systems has changed this situation dramatically. The need to reliably read out the state of a given qubit using a very weak microwave probe within a very short time has led to renewed interest in these quantum-limited microwave amplifiers, which are already widely used as tools in this field. Here, we describe the quantum mechanical theory for one particular parametric amplifier design, called the flux-driven Josephson parametric amplifier, which we developed in 2008. The theory predicts the performance of this parametric amplifier, including its gain, bandwidth, and noise temperature. We also present the phase detection capability of this amplifier when it is operated with a pump power that is above the threshold, i.e., as a parametric phase-locked oscillator or parametron.

Incorporating parametric uncertainty into population viability analysis models

USGS Publications Warehouse

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Problems in nonlinear acoustics: Scattering of sound by sound, parametric receiving arrays, nonlinear effects in asymmetric sound beams and pulsed finite amplitude sound beams

NASA Astrophysics Data System (ADS)

Hamilton, Mark F.

1989-08-01

Four projects are discussed in this annual summary report, all of which involve basic research in nonlinear acoustics: Scattering of Sound by Sound, a theoretical study of two nonconlinear Gaussian beams which interact to produce sum and difference frequency sound; Parametric Receiving Arrays, a theoretical study of parametric reception in a reverberant environment; Nonlinear Effects in Asymmetric Sound Beams, a numerical study of two dimensional finite amplitude sound fields; and Pulsed Finite Amplitude Sound Beams, a numerical time domain solution of the KZK equation.

Semi-quantitative assessment of pulmonary perfusion in children using dynamic contrast-enhanced MRI

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Thong, William E.; Ou, Phalla

2013-03-01

This paper addresses the study of semi-quantitative assessment of pulmonary perfusion acquired from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in a study population mainly composed of children with pulmonary malformations. The automatic analysis approach proposed is based on the indicator-dilution theory introduced in 1954. First, a robust method is developed to segment the pulmonary artery and the lungs from anatomical MRI data, exploiting 2D and 3D mathematical morphology operators. Second, the time-dependent contrast signal of the lung regions is deconvolved by the arterial input function for the assessment of the local hemodynamic system parameters, ie. mean transit time, pulmonary blood volume and pulmonary blood flow. The discrete deconvolution method implements here a truncated singular value decomposition (tSVD) method. Parametric images for the entire lungs are generated as additional elements for diagnosis and quantitative follow-up. The preliminary results attest the feasibility of perfusion quantification in pulmonary DCE-MRI and open an interesting alternative to scintigraphy for this type of evaluation, to be considered at least as a preliminary decision in the diagnostic due to the large availability of the technique and to the non-invasive aspects.

Three-dimensional MRI perfusion maps: a step beyond volumetric analysis in mental disorders

PubMed Central

Fabene, Paolo F; Farace, Paolo; Brambilla, Paolo; Andreone, Nicola; Cerini, Roberto; Pelizza, Luisa; Versace, Amelia; Rambaldelli, Gianluca; Birbaumer, Niels; Tansella, Michele; Sbarbati, Andrea

2007-01-01

A new type of magnetic resonance imaging analysis, based on fusion of three-dimensional reconstructions of time-to-peak parametric maps and high-resolution T1-weighted images, is proposed in order to evaluate the perfusion of selected volumes of interest. Because in recent years a wealth of data have suggested the crucial involvement of vascular alterations in mental diseases, we tested our new method on a restricted sample of schizophrenic patients and matched healthy controls. The perfusion of the whole brain was compared with that of the caudate nucleus by means of intrasubject analysis. As expected, owing to the encephalic vascular pattern, a significantly lower time-to-peak was observed in the caudate nucleus than in the whole brain in all healthy controls, indicating that the suggested method has enough sensitivity to detect subtle perfusion changes even in small volumes of interest. Interestingly, a less uniform pattern was observed in the schizophrenic patients. The latter finding needs to be replicated in an adequate number of subjects. In summary, the three-dimensional analysis method we propose has been shown to be a feasible tool for revealing subtle vascular changes both in normal subjects and in pathological conditions. PMID:17229290

Stability analysis of a time-periodic 2-dof MEMS structure

NASA Astrophysics Data System (ADS)

Kniffka, Till Jochen; Welte, Johannes; Ecker, Horst

2012-11-01

Microelectromechanical systems (MEMS) are becoming important for all kinds of industrial applications. Among them are filters in communication devices, due to the growing demand for efficient and accurate filtering of signals. In recent developments single degree of freedom (1-dof) oscillators, that are operated at a parametric resonances, are employed for such tasks. Typically vibration damping is low in such MEM systems. While parametric excitation (PE) is used so far to take advantage of a parametric resonance, this contribution suggests to also exploit parametric anti-resonances in order to improve the damping behavior of such systems. Modeling aspects of a 2-dof MEM system and first results of the analysis of the non-linear and the linearized system are the focus of this paper. In principle the investigated system is an oscillating mechanical system with two degrees of freedom x = [x1x2]T that can be described by Mx+Cx+K1x+K3(x2)x+Fes(x,V(t)) = 0. The system is inherently non-linear because of the cubic mechanical stiffness K3 of the structure, but also because of electrostatic forces (1+cos(ωt))Fes(x) that act on the system. Electrostatic forces are generated by comb drives and are proportional to the applied time-periodic voltage V(t). These drives also provide the means to introduce time-periodic coefficients, i.e. parametric excitation (1+cos(ωt)) with frequency ω. For a realistic MEM system the coefficients of the non-linear set of differential equations need to be scaled for efficient numerical treatment. The final mathematical model is a set of four non-linear time-periodic homogeneous differential equations of first order. Numerical results are obtained from two different methods. The linearized time-periodic (LTP) system is studied by calculating the Monodromy matrix of the system. The eigenvalues of this matrix decide on the stability of the LTP-system. To study the unabridged non-linear system, the bifurcation software ManLab is employed. Continuation analysis including stability evaluations are executed and show the frequency ranges for which the 2-dof system becomes unstable due to parametric resonances. Moreover, the existence of frequency intervals are shown where enhanced damping for the system is observed for this MEMS. The results from the stability studies are confirmed by simulation results.

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

PubMed

Nguyen, N; Milanfar, P; Golub, G

2001-01-01

In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

Elastic full-waveform inversion and parametrization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

NASA Astrophysics Data System (ADS)

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-06-01

Seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter trade-off, arising from the simultaneous variations of different physical parameters, which increase the nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parametrization and acquisition arrangement. An appropriate choice of model parametrization is important to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parametrizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) data for unconventional heavy oil reservoir characterization. Six model parametrizations are considered: velocity-density (α, β and ρ΄), modulus-density (κ, μ and ρ), Lamé-density (λ, μ΄ and ρ‴), impedance-density (IP, IS and ρ″), velocity-impedance-I (α΄, β΄ and I_P^' }) and velocity-impedance-II (α″, β″ and I_S^' }). We begin analysing the interparameter trade-off by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. We discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter trade-offs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter trade-offs for various model parametrizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parametrization, the inverted density profile can be overestimated, underestimated or spatially distorted. Among the six cases, only the velocity-density parametrization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. The heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson's ratios, can be identified clearly with the inverted isotropic-elastic parameters.

Resting-state networks in healthy adult subjects: a comparison between a 32-element and an 8-element phased array head coil at 3.0 Tesla.

PubMed

Paolini, Marco; Keeser, Daniel; Ingrisch, Michael; Werner, Natalie; Kindermann, Nicole; Reiser, Maximilian; Blautzik, Janusch

2015-05-01

Little research exists on the influence of a magnetic resonance imaging (MRI) head coil's channel count on measured resting-state functional connectivity. To compare a 32-element (32ch) and an 8-element (8ch) phased array head coil with respect to their potential to detect functional connectivity within resting-state networks. Twenty-six healthy adults (mean age, 21.7 years; SD, 2.1 years) underwent resting-state functional MRI at 3.0 Tesla with both coils using equal standard imaging parameters and a counterbalanced design. Independent component analysis (ICA) at different model orders and a dual regression approach were performed. Voxel-wise non-parametric statistical between-group contrasts were determined using permutation-based non-parametric inference. Phantom measurements demonstrated a generally higher image signal-to-noise ratio using the 32ch head coil. However, the results showed no significant differences between corresponding resting-state networks derived from both coils (p < 0.05, FWE-corrected). Using the identical standard acquisition parameters, the 32ch head coil does not offer any significant advantages in detecting ICA-based functional connectivity within RSNs. © The Foundation Acta Radiologica 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Separation of β-amyloid binding and white matter uptake of 18F-flutemetamol using spectral analysis

PubMed Central

Heurling, Kerstin; Buckley, Christopher; Vandenberghe, Rik; Laere, Koen Van; Lubberink, Mark

2015-01-01

The kinetic components of the β-amyloid ligand 18F-flutemetamol binding in grey and white matter were investigated through spectral analysis, and a method developed for creation of parametric images separating grey and white matter uptake. Tracer uptake in grey and white matter and cerebellar cortex was analyzed through spectral analysis in six subjects, with (n=4) or without (n=2) apparent β-amyloid deposition, having undergone dynamic 18F-flutemetamol scanning with arterial blood sampling. The spectra were divided into three components: slow, intermediate and fast basis function rates. The contribution of each of the components to total volume of distribution (VT) was assessed for different tissue types. The slow component dominated in white matter (average 90%), had a higher contribution to grey matter VT in subjects with β-amyloid deposition (average 44%) than without (average 6%) and was absent in cerebellar cortex, attributing the slow component of 18F-flutemetamol uptake in grey matter to β-amyloid binding. Parametric images of voxel-based spectral analysis were created for VT, the slow component and images segmented based on the slow component contribution; confirming that grey matter and white matter uptake can be discriminated on voxel-level using a threshold for the contribution from the slow component to VT. PMID:26550542

Individualism, conservatism, and radicalism as criteria for processing political beliefs: a parametric fMRI study.

PubMed

Zamboni, Giovanna; Gozzi, Marta; Krueger, Frank; Duhamel, Jean-René; Sirigu, Angela; Grafman, Jordan

2009-01-01

Politics is a manifestation of the uniquely human ability to debate, decide, and reach consensus on decisions affecting large groups over long durations of time. Recent neuroimaging studies on politics have focused on the association between brain regions and specific political behaviors by adopting party or ideological affiliation as a criterion to classify either experimental stimuli or subjects. However, it is unlikely that complex political beliefs (i.e., "the government should protect freedom of speech") are evaluated only on a liberal-to-conservative criterion. Here we used multidimensional scaling and parametric functional magnetic resonance imaging to identify which criteria/dimensions people use to structure complex political beliefs and which brain regions are concurrently activated. We found that three independent dimensions explained the variability of a set of statements expressing political beliefs and that each dimension was reflected in a distinctive pattern of neural activation: individualism (medial prefrontal cortex and temporoparietal junction), conservatism (dorsolateral prefrontal cortex), and radicalism (ventral striatum and posterior cingulate). The structures we identified are also known to be important in self-other processing, social decision-making in ambivalent situations, and reward prediction. Our results extend current knowledge on the neural correlates of the structure of political beliefs, a fundamental aspect of the human ability to coalesce into social entities.

Characterizing the constitutive response and energy absorption of rigid polymeric foams subjected to intermediate-velocity impact

DOE PAGES

Koohbor, Behrad; Kidane, Addis; Lu, Wei-Yang

2016-06-27

As an optimum energy-absorbing material system, polymeric foams are needed to dissipate the kinetic energy of an impact, while maintaining the impact force transferred to the protected object at a low level. As a result, it is crucial to accurately characterize the load bearing and energy dissipation performance of foams at high strain rate loading conditions. There are certain challenges faced in the accurate measurement of the deformation response of foams due to their low mechanical impedance. In the present work, a non-parametric method is successfully implemented to enable the accurate assessment of the compressive constitutive response of rigid polymericmore » foams subjected to impact loading conditions. The method is based on stereovision high speed photography in conjunction with 3D digital image correlation, and allows for accurate evaluation of inertia stresses developed within the specimen during deformation time. In conclusion, full-field distributions of stress, strain and strain rate are used to extract the local constitutive response of the material at any given location along the specimen axis. In addition, the effective energy absorbed by the material is calculated. Finally, results obtained from the proposed non-parametric analysis are compared with data obtained from conventional test procedures.« less

Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis.

PubMed

Fröhlich, Kilian; Winder, Klemens; Linker, Ralf A; Engelhorn, Tobias; Dörfler, Arnd; Lee, De-Hyung; Hilz, Max J; Schwab, Stefan; Seifert, Frank

2018-06-01

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.

The Use of Metaphors as a Parametric Design Teaching Model: A Case Study

ERIC Educational Resources Information Center

Agirbas, Asli

2018-01-01

Teaching methodologies for parametric design are being researched all over the world, since there is a growing demand for computer programming logic and its fabrication process in architectural education. The computer programming courses in architectural education are usually done in a very short period of time, and so students have no chance to…

Intracavity-pumped Raman laser action in a mid IR, continuous-wave (cw) MgO:PPLN optical parametric oscillator

NASA Astrophysics Data System (ADS)

Okishev, Andrey V.; Zuegel, Jonathan D.

2006-12-01

Intracavity-pumped Raman laser action in a fiber-laser pumped, single-resonant, continuous-wave (cw) MgO:PPLN optical parametric oscillator with a high-Q linear resonator has been observed for the first time to our knowledge. Experimental results of this phenomenon investigation will be discussed.

Geological terrain models

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.

1981-01-01

The initial phase of a program to determine the best interpretation strategy and sensor configuration for a radar remote sensing system for geologic applications is discussed. In this phase, terrain modeling and radar image simulation were used to perform parametric sensitivity studies. A relatively simple computer-generated terrain model is presented, and the data base, backscatter file, and transfer function for digital image simulation are described. Sets of images are presented that simulate the results obtained with an X-band radar from an altitude of 800 km and at three different terrain-illumination angles. The simulations include power maps, slant-range images, ground-range images, and ground-range images with statistical noise incorporated. It is concluded that digital image simulation and computer modeling provide cost-effective methods for evaluating terrain variations and sensor parameter changes, for predicting results, and for defining optimum sensor parameters.

Robustness against parametric noise of nonideal holonomic gates

NASA Astrophysics Data System (ADS)

Lupo, Cosmo; Aniello, Paolo; Napolitano, Mario; Florio, Giuseppe

2007-07-01

Holonomic gates for quantum computation are commonly considered to be robust against certain kinds of parametric noise, the cause of this robustness being the geometric character of the transformation achieved in the adiabatic limit. On the other hand, the effects of decoherence are expected to become more and more relevant when the adiabatic limit is approached. Starting from the system described by Florio [Phys. Rev. A 73, 022327 (2006)], here we discuss the behavior of nonideal holonomic gates at finite operational time, i.e., long before the adiabatic limit is reached. We have considered several models of parametric noise and studied the robustness of finite-time gates. The results obtained suggest that the finite-time gates present some effects of cancellation of the perturbations introduced by the noise which mimic the geometrical cancellation effect of standard holonomic gates. Nevertheless, a careful analysis of the results leads to the conclusion that these effects are related to a dynamical instead of a geometrical feature.

Sleep analysis for wearable devices applying autoregressive parametric models.

PubMed

Mendez, M O; Villantieri, O; Bianchi, A; Cerutti, S

2005-01-01

We applied time-variant and time-invariant parametric models in both healthy subjects and patients with sleep disorder recordings in order to assess the skills of those approaches to sleep disorders diagnosis in wearable devices. The recordings present the Obstructive Sleep Apnea (OSA) pathology which is characterized by fluctuations in the heart rate, bradycardia in apneonic phase and tachycardia at the recovery of ventilation. Data come from a web database in www.physionet.org. During OSA the spectral indexes obtained by time-variant lattice filters presented oscillations that correspond to the changes brady-tachycardia of the RR intervals and greater values than healthy ones. Multivariate autoregressive models showed an increment in very low frequency component (PVLF) at each apneic event. Also a rise in high frequency component (PHF) occurred over the breathing restore in the spectrum of both quadratic coherence and cross-spectrum in OSA. These autoregressive parametric approaches could help in the diagnosis of Sleep Disorder inside of the wearable devices.

Segmentation of Pollen Tube Growth Videos Using Dynamic Bi-Modal Fusion and Seam Carving.

PubMed

Tambo, Asongu L; Bhanu, Bir

2016-05-01

The growth of pollen tubes is of significant interest in plant cell biology, as it provides an understanding of internal cell dynamics that affect observable structural characteristics such as cell diameter, length, and growth rate. However, these parameters can only be measured in experimental videos if the complete shape of the cell is known. The challenge is to accurately obtain the cell boundary in noisy video images. Usually, these measurements are performed by a scientist who manually draws regions-of-interest on the images displayed on a computer screen. In this paper, a new automated technique is presented for boundary detection by fusing fluorescence and brightfield images, and a new efficient method of obtaining the final cell boundary through the process of Seam Carving is proposed. This approach takes advantage of the nature of the fusion process and also the shape of the pollen tube to efficiently search for the optimal cell boundary. In video segmentation, the first two frames are used to initialize the segmentation process by creating a search space based on a parametric model of the cell shape. Updates to the search space are performed based on the location of past segmentations and a prediction of the next segmentation.Experimental results show comparable accuracy to a previous method, but significant decrease in processing time. This has the potential for real time applications in pollen tube microscopy.

Efficient use of mobile devices for quantification of pressure injury images.

PubMed

Garcia-Zapirain, Begonya; Sierra-Sosa, Daniel; Ortiz, David; Isaza-Monsalve, Mariano; Elmaghraby, Adel

2018-01-01

Pressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods. We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries.

The application of statistical parametric mapping to 123I-FP-CIT SPECT in dementia with Lewy bodies, Alzheimer's disease and Parkinson's disease.

PubMed

Colloby, Sean J; O'Brien, John T; Fenwick, John D; Firbank, Michael J; Burn, David J; McKeith, Ian G; Williams, E David

2004-11-01

Dopaminergic loss can be visualised using (123)I-FP-CIT single photon emission computed tomography (SPECT) in several disorders including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Most previous SPECT studies have adopted region of interest (ROI) methods for analysis, which are subjective and operator-dependent. The purpose of this study was to investigate differences in striatal binding of (123)I-FP-CIT SPECT using the automated technique of statistical parametric mapping (SPM99) in subjects with DLB, Alzheimer's disease (AD), PD and healthy age-matched controls. This involved spatial normalisation of each subject's image to a customised template, followed by smoothing and intensity normalisation of each image to its corresponding mean occipital count per voxel. Group differences were assessed using a two-sample t test. Applying a height threshold of P

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Tahari, Abdel K; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ~15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ~45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ~35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.

Dynamic whole body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

Static whole body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single bed-coverage limiting the axial field-of-view to ~15–20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole body PET acquisition protocol of ~45min total length is presented, composed of (i) an initial 6-min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (6 passes x 7 bed positions, each scanned for 45sec). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares (OLS) Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of 10 different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole-body. In addition, the total acquisition length can be reduced from 45min to ~35min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error (MSE) and the CNR metrics, resulting in enhanced task-based imaging. PMID:24080962

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-10-01

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ˜15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ˜45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ˜35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.

Usefulness of parametric renal clearance images in the assessment of basic risk factors for renalnal clearance images in the assessment of basic risk factors for renal scarring in children with recurrent urinary tract infections.

PubMed

Pietrzak-Stelasiak, Ewa; Bieńkiewicz, Małgorzata; Woźnicki, Wojciech; Bubińska, Krystyna; Kowalewska-Pietrzak, Magdalena; Płachcińska, Anna; Kuśmierek, Jacek

2017-01-01

Clinically confirmed incidents of acute pyelonephritis (APN) following recurrent infections of urinary tract (UTI) form basic risk factors for renal scarring in children. Vesico-uretheral reflux (VUR) of higher grade is additional risk factor for this scarring. Opinions on diagnostic value of summed sequential images of renal uptake phase (SUM) of dynamic renal scintigraphy in detection of renal scars are diverse. However, several publications point to higher diagnostic efficacy of clearance parametric images (PAR) generated from this study. To establish a clinical value of parametric renal clearance images in detection of renal scarring. A prospective study was performed in a group of 91 children at the age of 4 to 18 years with recurrent UTI. Clinically documented incidents of APN were noted in 32 children: in 8 cases - one and in the remaining 24 - 2 to 5 (mean 3) incidents. In the remaining 59 patients only infections of the lower part of urinary tract were diagnosed. Static renal 99mTc-DMSA SPECT study and after 2-4 days dynamic renal studies (99mTc-EC) were performed in every patient not earlier than 6 months after the last documented incident of UTI. PAR images generated from a dynamic study by in-house developed software and SUM images were compared with a gold standard SPECT study. Percentages of children with detected renal scar(s) with SPECT and PAR methods amounted to 55% and 54%, respectively and were statistically significantly higher (p < 0.0001) than with SUM method - 31%. Scars in children with history of APN detected with SPECT and PAR methods were significantly more frequent than with infections of only lower part of urinary tract (72% vs. 46%; p = 0.017 and 69% vs. 46%; p = 0.036, respectively). A SUM method did not reveal statistically significant differences between frequencies of detection of scars in groups specified above - 38% vs. 27% (p = 0.31). Both SPECT and PAR methods showed also that frequencies of occurrence of renal scars in children with higher grades of VUR were higher than without or with lower grades of VUR: 79% vs. 50% (p = 0.048) and 79% vs. 49% (p = 0.04). A SUM method did not reveal higher frequency of renal scars in children with high VUR grades: 36% vs. 30% (p = 0.44). Results obtained with PAR and SPECT methods were similar. An advantage of PAR over SUM images obtained from a dynamic renal scintigraphy in detection of renal scars in children with UTI was confirmed.

Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth.

PubMed

Mischi, Massimo; Turco, Simona; Lavini, Cristina; Kompatsiari, Kyveli; de la Rosette, Jean J M C H; Breeuwer, Marcel; Wijkstra, Hessel

2014-08-01

Cancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI. The microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented. The proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy. Cancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results. A new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research.

Modeling personnel turnover in the parametric organization

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1991-01-01

A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.

Noise-enhanced Parametric Resonance in Perturbed Galaxies

NASA Astrophysics Data System (ADS)

Sideris, Ioannis V.; Kandrup, Henry E.

2004-02-01

This paper describes how parametric resonances associated with a galactic potential subjected to relatively low-amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation frequency, modeled as colored noise. One aim thereby is to allow for the effects of a changing oscillation frequency as the density distribution associated with a galaxy evolves during violent relaxation. Another is to mimic the possible effects of internal substructures, satellite galaxies, and/or a high-density environment. The principal conclusions are that allowing for a variable frequency does not vitiate the effects of parametric resonance, and that, in at least some cases, such variations can increase the overall importance of parametric resonance associated with systematic pulsations. In memory of Professor H. E. Kandrup, a brilliant scientist, excellent teacher, and good friend. His genius and sense of humor will be greatly missed.

Diffeomorphic demons: efficient non-parametric image registration.

PubMed

Vercauteren, Tom; Pennec, Xavier; Perchant, Aymeric; Ayache, Nicholas

2009-03-01

We propose an efficient non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. We provide strong theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage for the symmetric forces variant of the demons algorithm. We show on controlled experiments that this advantage is confirmed in practice and yields a faster convergence. In the second part of this paper, we adapt the optimization procedure underlying the demons algorithm to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of displacement fields by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the gold standard, available in controlled experiments, in terms of Jacobians.

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Preclinical Biokinetic Modelling of Tc-99m Radiophamaceuticals Obtained from Semi-Automatic Image Processing.

PubMed

Cornejo-Aragón, Luz G; Santos-Cuevas, Clara L; Ocampo-García, Blanca E; Chairez-Oria, Isaac; Diaz-Nieto, Lorenza; García-Quiroz, Janice

2017-01-01

The aim of this study was to develop a semi automatic image processing algorithm (AIPA) based on the simultaneous information provided by X-ray and radioisotopic images to determine the biokinetic models of Tc-99m radiopharmaceuticals from quantification of image radiation activity in murine models. These radioisotopic images were obtained by a CCD (charge couple device) camera coupled to an ultrathin phosphorous screen in a preclinical multimodal imaging system (Xtreme, Bruker). The AIPA consisted of different image processing methods for background, scattering and attenuation correction on the activity quantification. A set of parametric identification algorithms was used to obtain the biokinetic models that characterize the interaction between different tissues and the radiopharmaceuticals considered in the study. The set of biokinetic models corresponded to the Tc-99m biodistribution observed in different ex vivo studies. This fact confirmed the contribution of the semi-automatic image processing technique developed in this study.

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images.

PubMed

Pang, Jincheng; Özkucur, Nurdan; Ren, Michael; Kaplan, David L; Levin, Michael; Miller, Eric L

2015-11-01

Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

Spatio-temporal Variability of Albedo and its Impact on Glacier Melt Modelling

NASA Astrophysics Data System (ADS)

Kinnard, C.; Mendoza, C.; Abermann, J.; Petlicki, M.; MacDonell, S.; Urrutia, R.

2017-12-01

Albedo is an important variable for the surface energy balance of glaciers, yet its representation within distributed glacier mass-balance models is often greatly simplified. Here we study the spatio-temporal evolution of albedo on Glacier Universidad, central Chile (34°S, 70°W), using time-lapse terrestrial photography, and investigate its effect on the shortwave radiation balance and modelled melt rates. A 12 megapixel digital single-lens reflex camera was setup overlooking the glacier and programmed to take three daily images of the glacier during a two-year period (2012-2014). One image was chosen for each day with no cloud shading on the glacier. The RAW images were projected onto a 10m resolution digital elevation model (DEM), using the IMGRAFT software (Messerli and Grinsted, 2015). A six-parameter camera model was calibrated using a single image and a set of 17 ground control points (GCPs), yielding a georeferencing accuracy of <1 pixel in image coordinates. The camera rotation was recalibrated for new images based on a set of common tie points over stable terrain, thus accounting for possible camera movement over time. The reflectance values from the projected image were corrected for topographic and atmospheric influences using a parametric solar irradiation model, following a modified algorithm based on Corripio (2004), and then converted to albedo using reference albedo measurements from an on-glacier automatic weather station (AWS). The image-based albedo was found to compare well with independent albedo observations from a second AWS in the glacier accumulation area. Analysis of the albedo maps showed that the albedo is more spatially-variable than the incoming solar radiation, making albedo a more important factor of energy balance spatial variability. The incorporation of albedo maps within an enhanced temperature index melt model revealed that the spatio-temporal variability of albedo is an important factor for the calculation of glacier-wide meltwater fluxes.

Modeling and Simulation of a Parametrically Resonant Micromirror With Duty-Cycled Excitation.

PubMed

Shahid, Wajiha; Qiu, Zhen; Duan, Xiyu; Li, Haijun; Wang, Thomas D; Oldham, Kenn R

2014-12-01

High frequency large scanning angle electrostatically actuated microelectromechanical systems (MEMS) mirrors are used in a variety of applications involving fast optical scanning. A 1-D parametrically resonant torsional micromirror for use in biomedical imaging is analyzed here with respect to operation by duty-cycled square waves. Duty-cycled square wave excitation can have significant advantages for practical mirror regulation and/or control. The mirror's nonlinear dynamics under such excitation is analyzed in a Hill's equation form. This form is used to predict stability regions (the voltage-frequency relationship) of parametric resonance behavior over large scanning angles using iterative approximations for nonlinear capacitance behavior of the mirror. Numerical simulations are also performed to obtain the mirror's frequency response over several voltages for various duty cycles. Frequency sweeps, stability results, and duty cycle trends from both analytical and simulation methods are compared with experimental results. Both analytical models and simulations show good agreement with experimental results over the range of duty cycled excitations tested. This paper discusses the implications of changing amplitude and phase with duty cycle for robust open-loop operation and future closed-loop operating strategies.

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

Texture-based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric 'skin age' modelling.

PubMed

Orun, A B; Seker, H; Uslan, V; Goodyer, E; Smith, G

2017-06-01

The textural structure of 'skin age'-related subskin components enables us to identify and analyse their unique characteristics, thus making substantial progress towards establishing an accurate skin age model. This is achieved by a two-stage process. First by the application of textural analysis using laser speckle imaging, which is sensitive to textural effects within the λ = 650 nm spectral band region. In the second stage, a Bayesian inference method is used to select attributes from which a predictive model is built. This technique enables us to contrast different skin age models, such as the laser speckle effect against the more widely used normal light (LED) imaging method, whereby it is shown that our laser speckle-based technique yields better results. The method introduced here is non-invasive, low cost and capable of operating in real time; having the potential to compete against high-cost instrumentation such as confocal microscopy or similar imaging devices used for skin age identification purposes. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Myocardial perfusion assessment with contrast echocardiography

NASA Astrophysics Data System (ADS)

Desco, Manuel; Ledesma-Carbayo, Maria J.; Santos, Andres; Garcia-Fernandez, Miguel A.; Marcos-Alberca, Pedro; Malpica, Norberto; Antoranz, Jose C.; Garcia-Barreno, Pedro

2001-05-01

Assessment of intramyocardial perfusion by contrast echocardiography is a promising new technique that allows to obtain quantitative parameters for the assessment of ischemic disease. In this work, a new methodology and a software prototype developed for this task are presented. It has been validated with Coherent Contrast Imaging (CCI) images acquired with an Acuson Sequoia scanner. Contrast (Optison microbubbles) is injected continuously during the scan. 150 images are acquired using low mechanical index U/S pulses. A burst of high mechanical index pulses is used to destroy bubbles, thus allowing to detect the contrast wash-in. The stud is performed in two conditions: rest and pharmacologically induced stress. The software developed allows to visualized the study (cine) and to select several ROIs within the heart wall. The position of these ROIs along the cardiac cycle is automatically corrected on the basis of the gradient field, and they can also be manually corrected in case the automatic procedure fails. Time curves are analyzed according to a parametric model that incorporates both contrast inflow rate and cyclic variations. Preliminary clinical results on 80 patients have allowed us to identify normal and pathological patterns and to establish the correlation of quantitative parameters with the real diagnosis.

Visualizing epithelial expression of EGFR in vivo with distal scanning side-viewing confocal endomicroscope

NASA Astrophysics Data System (ADS)

Duan, Xiyu; Li, Haijun; Zhou, Juan; Zhou, Quan; Oldham, Kenn R.; Wang, Thomas D.

2016-11-01

Confocal endomicroscopy is an emerging imaging technology that has recently been introduced into the clinic to instantaneously collect “optical biopsies” in vivo with histology-like quality. Here, we demonstrate a fast scanner located in the distal end of a side-viewing instrument using a compact lens assembly with numerical aperture of 0.5 to achieve a working distance of 100 μm and field-of-view of 300 × 400 μm2. The microelectromechanical systems (MEMS) mirror was designed based on the principle of parametric resonance and images at 5 frames per second. The instrument has a 4.2 mm outer diameter and 3 cm rigid length, and can pass through the biopsy channel of a medical endoscope. We achieved real time optical sections of NIR fluorescence with 0.87 μm lateral resolution, and were able to visualize in vivo binding of a Cy5.5-labeled peptide specific for EGFR to the cell surface of pre-cancerous colonocytes within the epithelium of dysplastic crypts in mouse colon. By performing targeted imaging with endomicroscopy, we can visualize molecular expression patterns in vivo that provide a biological basis for disease detection.

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Noninvasive Quantitative Imaging of Collagen Microstructure in Three-Dimensional Hydrogels Using High-Frequency Ultrasound

PubMed Central

Mercado, Karla P.; Helguera, María; Hocking, Denise C.

2015-01-01

Collagen I is widely used as a natural component of biomaterials for both tissue engineering and regenerative medicine applications. The physical and biological properties of fibrillar collagens are strongly tied to variations in collagen fiber microstructure. The goal of this study was to develop the use of high-frequency quantitative ultrasound to assess collagen microstructure within three-dimensional (3D) hydrogels noninvasively and nondestructively. The integrated backscatter coefficient (IBC) was employed as a quantitative ultrasound parameter to detect, image, and quantify spatial variations in collagen fiber density and diameter. Collagen fiber microstructure was varied by fabricating hydrogels with different collagen concentrations or polymerization temperatures. IBC values were computed from measurements of the backscattered radio-frequency ultrasound signals collected using a single-element transducer (38-MHz center frequency, 13–47 MHz bandwidth). The IBC increased linearly with increasing collagen concentration and decreasing polymerization temperature. Parametric 3D images of the IBC were generated to visualize and quantify regional variations in collagen microstructure throughout the volume of hydrogels fabricated in standard tissue culture plates. IBC parametric images of corresponding cell-embedded collagen gels showed cell accumulation within regions having elevated collagen IBC values. The capability of this ultrasound technique to noninvasively detect and quantify spatial differences in collagen microstructure offers a valuable tool to monitor the structural properties of collagen scaffolds during fabrication, to detect functional differences in collagen microstructure, and to guide fundamental research on the interactions of cells and collagen matrices. PMID:25517512

Noninvasive Quantitative Imaging of Collagen Microstructure in Three-Dimensional Hydrogels Using High-Frequency Ultrasound.

PubMed

Mercado, Karla P; Helguera, María; Hocking, Denise C; Dalecki, Diane

2015-07-01

Collagen I is widely used as a natural component of biomaterials for both tissue engineering and regenerative medicine applications. The physical and biological properties of fibrillar collagens are strongly tied to variations in collagen fiber microstructure. The goal of this study was to develop the use of high-frequency quantitative ultrasound to assess collagen microstructure within three-dimensional (3D) hydrogels noninvasively and nondestructively. The integrated backscatter coefficient (IBC) was employed as a quantitative ultrasound parameter to detect, image, and quantify spatial variations in collagen fiber density and diameter. Collagen fiber microstructure was varied by fabricating hydrogels with different collagen concentrations or polymerization temperatures. IBC values were computed from measurements of the backscattered radio-frequency ultrasound signals collected using a single-element transducer (38-MHz center frequency, 13-47 MHz bandwidth). The IBC increased linearly with increasing collagen concentration and decreasing polymerization temperature. Parametric 3D images of the IBC were generated to visualize and quantify regional variations in collagen microstructure throughout the volume of hydrogels fabricated in standard tissue culture plates. IBC parametric images of corresponding cell-embedded collagen gels showed cell accumulation within regions having elevated collagen IBC values. The capability of this ultrasound technique to noninvasively detect and quantify spatial differences in collagen microstructure offers a valuable tool to monitor the structural properties of collagen scaffolds during fabrication, to detect functional differences in collagen microstructure, and to guide fundamental research on the interactions of cells and collagen matrices.

Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

NASA Astrophysics Data System (ADS)

Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

2011-03-01

An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

Optimal methods for fitting probability distributions to propagule retention time in studies of zoochorous dispersal.

PubMed

Viana, Duarte S; Santamaría, Luis; Figuerola, Jordi

2016-02-01

Propagule retention time is a key factor in determining propagule dispersal distance and the shape of "seed shadows". Propagules dispersed by animal vectors are either ingested and retained in the gut until defecation or attached externally to the body until detachment. Retention time is a continuous variable, but it is commonly measured at discrete time points, according to pre-established sampling time-intervals. Although parametric continuous distributions have been widely fitted to these interval-censored data, the performance of different fitting methods has not been evaluated. To investigate the performance of five different fitting methods, we fitted parametric probability distributions to typical discretized retention-time data with known distribution using as data-points either the lower, mid or upper bounds of sampling intervals, as well as the cumulative distribution of observed values (using either maximum likelihood or non-linear least squares for parameter estimation); then compared the estimated and original distributions to assess the accuracy of each method. We also assessed the robustness of these methods to variations in the sampling procedure (sample size and length of sampling time-intervals). Fittings to the cumulative distribution performed better for all types of parametric distributions (lognormal, gamma and Weibull distributions) and were more robust to variations in sample size and sampling time-intervals. These estimated distributions had negligible deviations of up to 0.045 in cumulative probability of retention times (according to the Kolmogorov-Smirnov statistic) in relation to original distributions from which propagule retention time was simulated, supporting the overall accuracy of this fitting method. In contrast, fitting the sampling-interval bounds resulted in greater deviations that ranged from 0.058 to 0.273 in cumulative probability of retention times, which may introduce considerable biases in parameter estimates. We recommend the use of cumulative probability to fit parametric probability distributions to propagule retention time, specifically using maximum likelihood for parameter estimation. Furthermore, the experimental design for an optimal characterization of unimodal propagule retention time should contemplate at least 500 recovered propagules and sampling time-intervals not larger than the time peak of propagule retrieval, except in the tail of the distribution where broader sampling time-intervals may also produce accurate fits.

Creating A Data Base For Design Of An Impeller

NASA Technical Reports Server (NTRS)

Prueger, George H.; Chen, Wei-Chung

1993-01-01

Report describes use of Taguchi method of parametric design to create data base facilitating optimization of design of impeller in centrifugal pump. Data base enables systematic design analysis covering all significant design parameters. Reduces time and cost of parametric optimization of design: for particular impeller considered, one can cover 4,374 designs by computational simulations of performance for only 18 cases.

Spacelab mission dependent training parametric resource requirements study

NASA Technical Reports Server (NTRS)

Ogden, D. H.; Watters, H.; Steadman, J.; Conrad, L.

1976-01-01

Training flows were developed for typical missions, resource relationships analyzed, and scheduling optimization algorithms defined. Parametric analyses were performed to study the effect of potential changes in mission model, mission complexity and training time required on the resource quantities required to support training of payload or mission specialists. Typical results of these analyses are presented both in graphic and tabular form.

Realization of High-Fidelity, on Chip Readout of Solid-state Quantum Bits

DTIC Science & Technology

2017-08-29

estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the...and characterized Josephson Traveling Wave Parametric Amplifiers (JTWPA or TWPA), superconducting amplifiers providing significantly greater...Publications/Patents: 2015: • C. Macklin, et al., “A near-quantum-limited Josephson traveling -wave parametric amplifier”, Science, (2015). • N

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay.

PubMed

Tutsoy, Onder; Barkana, Duygun Erol; Tugal, Harun

2018-05-01

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Trial-dependent psychometric functions accounting for perceptual learning in 2-AFC discrimination tasks.

PubMed

Kattner, Florian; Cochrane, Aaron; Green, C Shawn

2017-09-01

The majority of theoretical models of learning consider learning to be a continuous function of experience. However, most perceptual learning studies use thresholds estimated by fitting psychometric functions to independent blocks, sometimes then fitting a parametric function to these block-wise estimated thresholds. Critically, such approaches tend to violate the basic principle that learning is continuous through time (e.g., by aggregating trials into large "blocks" for analysis that each assume stationarity, then fitting learning functions to these aggregated blocks). To address this discrepancy between base theory and analysis practice, here we instead propose fitting a parametric function to thresholds from each individual trial. In particular, we implemented a dynamic psychometric function whose parameters were allowed to change continuously with each trial, thus parameterizing nonstationarity. We fit the resulting continuous time parametric model to data from two different perceptual learning tasks. In nearly every case, the quality of the fits derived from the continuous time parametric model outperformed the fits derived from a nonparametric approach wherein separate psychometric functions were fit to blocks of trials. Because such a continuous trial-dependent model of perceptual learning also offers a number of additional advantages (e.g., the ability to extrapolate beyond the observed data; the ability to estimate performance on individual critical trials), we suggest that this technique would be a useful addition to each psychophysicist's analysis toolkit.

Spatial pattern separation of chemicals and frequency-independent components by terahertz spectroscopic imaging

NASA Astrophysics Data System (ADS)

Watanabe, Yuuki; Kawase, Kodo; Ikari, Tomofumi; Ito, Hiromasa; Ishikawa, Youichi; Minamide, Hiroaki

2003-10-01

We separated the component spatial patterns of frequency-dependent absorption in chemicals and frequency-independent components such as plastic, paper, and measurement noise in terahertz (THz) spectroscopic images, using known spectral curves. Our measurement system, which uses a widely tunable coherent THz-wave parametric oscillator source, can image at a specific frequency in the range 1-2 THz. The component patterns of chemicals can easily be extracted by use of the frequency-independent components. This method could be successfully used for nondestructive inspection for the detection of illegal drugs and devices of bioterrorism concealed, e.g., inside mail and packages.

Parametric Study of a YAV-8B Harrier in Ground Effect using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Pandya, Shishir; Chaderjian, Neal; Ahmad, Jasim; Kwak, Dochan (Technical Monitor)

2002-01-01

A process is described which enables the generation of 35 time-dependent viscous solutions for a YAV-8B Harrier in ground effect in one week. Overset grids are used to model the complex geometry of the Harrier aircraft and the interaction of its jets with the ground plane and low-speed ambient flow. The time required to complete this parametric study is drastically reduced through the use of process automation, modern computational platforms, and parallel computing. Moreover, a dual-time-stepping algorithm is described which improves solution robustness. Unsteady flow visualization and a frequency domain analysis are also used to identify and correlated key flow structures with the time variation of lift.

NASA Tech Briefs, March 2009

NASA Technical Reports Server (NTRS)

2009-01-01

Topics covered include: Improved Instrument for Detecting Water and Ice in Soil; Real-Time Detection of Dust Devils from Pressure Readings; Determining Surface Roughness in Urban Areas Using Lidar Data; DSN Data Visualization Suite; Hamming and Accumulator Codes Concatenated with MPSK or QAM; Wide-Angle-Scanning Reflectarray Antennas Actuated by MEMS; Biasable Subharmonic Membrane Mixer for 520 to 600 GHz; Hardware Implementation of Serially Concatenated PPM Decoder; Symbolic Processing Combined with Model-Based Reasoning; Presentation Extensions of the SOAP; Spreadsheets for Analyzing and Optimizing Space Missions; Processing Ocean Images to Detect Large Drift Nets; Alternative Packaging for Back-Illuminated Imagers; Diamond Machining of an Off-Axis Biconic Aspherical Mirror; Laser Ablation Increases PEM/Catalyst Interfacial Area; Damage Detection and Self-Repair in Inflatable/Deployable Structures; Polyimide/Glass Composite High-Temperature Insulation; Nanocomposite Strain Gauges Having Small TCRs; Quick-Connect Windowed Non-Stick Penetrator Tips for Rapid Sampling; Modeling Unsteady Cavitation and Dynamic Loads in Turbopumps; Continuous-Flow System Produces Medical-Grade Water; Discrimination of Spore-Forming Bacilli Using spoIVA; nBn Infrared Detector Containing Graded Absorption Layer; Atomic References for Measuring Small Accelerations; Ultra-Broad-Band Optical Parametric Amplifier or Oscillator; Particle-Image Velocimeter Having Large Depth of Field; Enhancing SERS by Means of Supramolecular Charge Transfer; Improving 3D Wavelet-Based Compression of Hyperspectral Images; Improved Signal Chains for Readout of CMOS Imagers; SOI CMOS Imager with Suppression of Cross-Talk; Error-Rate Bounds for Coded PPM on a Poisson Channel; Biomorphic Multi-Agent Architecture for Persistent Computing; and Using Covariance Analysis to Assess Pointing Performance.

Restoration of MRI data for intensity non-uniformities using local high order intensity statistics

PubMed Central

Hadjidemetriou, Stathis; Studholme, Colin; Mueller, Susanne; Weiner, Michael; Schuff, Norbert

2008-01-01

MRI at high magnetic fields (>3.0 T) is complicated by strong inhomogeneous radio-frequency fields, sometimes termed the “bias field”. These lead to non-biological intensity non-uniformities across the image. They can complicate further image analysis such as registration and tissue segmentation. Existing methods for intensity uniformity restoration have been optimized for 1.5 T, but they are less effective for 3.0 T MRI, and not at all satisfactory for higher fields. Also, many of the existing restoration algorithms require a brain template or use a prior atlas, which can restrict their practicalities. In this study an effective intensity uniformity restoration algorithm has been developed based on non-parametric statistics of high order local intensity co-occurrences. These statistics are restored with a non-stationary Wiener filter. The algorithm also assumes a smooth non-uniformity and is stable. It does not require a prior atlas and is robust to variations in anatomy. In geriatric brain imaging it is robust to variations such as enlarged ventricles and low contrast to noise ratio. The co-occurrence statistics improve robustness to whole head images with pronounced non-uniformities present in high field acquisitions. Its significantly improved performance and lower time requirements have been demonstrated by comparing it to the very commonly used N3 algorithm on BrainWeb MR simulator images as well as on real 4 T human head images. PMID:18621568

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

NASA Astrophysics Data System (ADS)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

A Parametric Computational Model of the Action Potential of Pacemaker Cells.

PubMed

Ai, Weiwei; Patel, Nitish D; Roop, Partha S; Malik, Avinash; Andalam, Sidharta; Yip, Eugene; Allen, Nathan; Trew, Mark L

2018-01-01

A flexible, efficient, and verifiable pacemaker cell model is essential to the design of real-time virtual hearts that can be used for closed-loop validation of cardiac devices. A new parametric model of pacemaker action potential is developed to address this need. The action potential phases are modeled using hybrid automaton with one piecewise-linear continuous variable. The model can capture rate-dependent dynamics, such as action potential duration restitution, conduction velocity restitution, and overdrive suppression by incorporating nonlinear update functions. Simulated dynamics of the model compared well with previous models and clinical data. The results show that the parametric model can reproduce the electrophysiological dynamics of a variety of pacemaker cells, such as sinoatrial node, atrioventricular node, and the His-Purkinje system, under varying cardiac conditions. This is an important contribution toward closed-loop validation of cardiac devices using real-time heart models.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

[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.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

2016-05-01

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y- R e- V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

Hybrid PET/MR imaging: physics and technical considerations.

PubMed

Shah, Shetal N; Huang, Steve S

2015-08-01

In just over a decade, hybrid imaging with FDG PET/CT has become a standard bearer in the management of cancer patients. An exquisitely sensitive whole-body imaging modality, it combines the ability to detect subtle biologic changes with FDG PET and the anatomic information offered by CT scans. With advances in MR technology and advent of novel targeted PET radiotracers, hybrid PET/MRI is an evolutionary technique that is poised to revolutionize hybrid imaging. It offers unparalleled spatial resolution and functional multi-parametric data combined with biologic information in the non-invasive detection and characterization of diseases, without the deleterious effects of ionizing radiation. This article reviews the basic principles of FDG PET and MR imaging, discusses the salient technical developments of hybrid PET/MR systems, and provides an introduction to FDG PET/MR image acquisition.

Towards Dynamic Contrast Specific Ultrasound Tomography

NASA Astrophysics Data System (ADS)

Demi, Libertario; van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-10-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography.

PubMed

Demi, Libertario; Van Sloun, Ruud J G; Wijkstra, Hessel; Mischi, Massimo

2016-10-05

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography

PubMed Central

Demi, Libertario; Van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-01-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast. PMID:27703251