Multibeam Formation with a Parametric Sonar

DTIC Science & Technology

1976-03-05

AD-A022 815 MULTIBEAM FORMATION WITH A PARAMETRIC SONAR Robert L. White Texas University at Austin Prepared for: Office of Naval Research 5 March...PARAMETRIC SONAR Final Report under Contract N00014-70-A-0166, Task 0020 1 February - 31 July 1974 Robe&, L. White OFFICE OF NAVAL RESEARCH Contract N00014...78712 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. r-X: ~ ... ABSTRACT Parametric sonar has proven to be an effective concept in sonar

Parametric Imaging Of Digital Subtraction Angiography Studies For Renal Transplant Evaluation

NASA Astrophysics Data System (ADS)

Gallagher, Joe H.; Meaney, Thomas F.; Flechner, Stuart M.; Novick, Andrew C.; Buonocore, Edward

1981-11-01

A noninvasive method for diagnosing acute tubular necrosis and rejection would be an important tool for the management of renal transplant patients. From a sequence of digital subtraction angiographic images acquired after an intravenous injection of radiographic contrast material, the parametric images of the maximum contrast, the time when the maximum contrast is reached, and two times the time at which one half of the maximum contrast is reached are computed. The parametric images of the time when the maximum is reached clearly distinguish normal from abnormal renal function. However, it is the parametric image of two times the time when one half of the maximum is reached which provides some assistance in differentiating acute tubular necrosis from rejection.

Star Formation at z = 2.481 in the Lensed Galaxy SDSS J1110 = 6459. I. Lens Modeling and Source Reconstruction

NASA Astrophysics Data System (ADS)

Johnson, Traci L.; Sharon, Keren; Gladders, Michael D.; Rigby, Jane R.; Bayliss, Matthew B.; Wuyts, Eva; Whitaker, Katherine E.; Florian, Michael; Murray, Katherine T.

2017-07-01

Using the combined resolving power of the Hubble Space Telescope and gravitational lensing, we resolve star-forming structures in a z˜ 2.5 galaxy on scales much smaller than the usual kiloparsec diffraction limit of HST. SGAS J111020.0+645950.8 is a clumpy, star-forming galaxy lensed by the galaxy cluster SDSS J1110+6459 at z=0.659, with a total magnification ˜ 30× across the entire arc. We use a hybrid parametric/non-parametric strong lensing mass model to compute the deflection and magnification of this giant arc, reconstruct the light distribution of the lensed galaxy in the source plane, and resolve the star formation into two dozen clumps. We develop a forward-modeling technique to model each clump in the source plane. We ray-trace the model to the image plane, convolve with the instrumental point-spread function (PSF), and compare with the GALFIT model of the clumps in the image plane, which decomposes clump structure from more extended emission. This technique has the advantage, over ray-tracing, of accounting for the asymmetric lensing shear of the galaxy in the image plane and the instrument PSF. At this resolution, we can begin to study star formation on a clump-by-clump basis, toward the goal of understanding feedback mechanisms and the buildup of exponential disks at high redshift. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program # 13003.

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.

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.

Early science from the Pan-STARRS1 Optical Galaxy Survey (POGS): Maps of stellar mass and star formation rate surface density obtained from distributed-computing pixel-SED fitting

NASA Astrophysics Data System (ADS)

Thilker, David A.; Vinsen, K.; Galaxy Properties Key Project, PS1

2014-01-01

To measure resolved galactic physical properties unbiased by the mask of recent star formation and dust features, we are conducting a citizen-scientist enabled nearby galaxy survey based on the unprecedented optical (g,r,i,z,y) imaging from Pan-STARRS1 (PS1). The PS1 Optical Galaxy Survey (POGS) covers 3π steradians (75% of the sky), about twice the footprint of SDSS. Whenever possible we also incorporate ancillary multi-wavelength image data from the ultraviolet (GALEX) and infrared (WISE, Spitzer) spectral regimes. For each cataloged nearby galaxy with a reliable redshift estimate of z < 0.05 - 0.1 (dependent on donated CPU power), publicly-distributed computing is being harnessed to enable pixel-by-pixel spectral energy distribution (SED) fitting, which in turn provides maps of key physical parameters such as the local stellar mass surface density, crude star formation history, and dust attenuation. With pixel SED fitting output we will then constrain parametric models of galaxy structure in a more meaningful way than ordinarily achieved. In particular, we will fit multi-component (e.g. bulge, bar, disk) galaxy models directly to the distribution of stellar mass rather than surface brightness in a single band, which is often locally biased. We will also compute non-parametric measures of morphology such as concentration, asymmetry using the POGS stellar mass and SFR surface density images. We anticipate studying how galactic substructures evolve by comparing our results with simulations and against more distant imaging surveys, some of which which will also be processed in the POGS pipeline. The reliance of our survey on citizen-scientist volunteers provides a world-wide opportunity for education. We developed an interactive interface which highlights the science being produced by each volunteer’s own CPU cycles. The POGS project has already proven popular amongst the public, attracting about 5000 volunteers with nearly 12,000 participating computers, and is growing rapidly.

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).

Nakagami-m parametric imaging for characterization of thermal coagulation and cavitation erosion induced by HIFU.

PubMed

Han, Meng; Wang, Na; Guo, Shifang; Chang, Nan; Lu, Shukuan; Wan, Mingxi

2018-07-01

Nowadays, both thermal and mechanical ablation techniques of HIFU associated with cavitation have been developed for noninvasive treatment. A specific challenge for the successful clinical implementation of HIFU is to achieve real-time imaging for the evaluation and determination of therapy outcomes such as necrosis or homogenization. Ultrasound Nakagami-m parametric imaging highlights the degrading shadowing effects of bubbles and can be used for tissue characterization. The aim of this study is to investigate the performance of Nakagami-m parametric imaging for evaluating and differentiating thermal coagulation and cavitation erosion induced by HIFU. Lesions were induced in basic bovine serum albumin (BSA) phantoms and ex vivo porcine livers using a 1.6 MHz single-element transducer. Thermal and mechanical lesions induced by two types of HIFU sequences respectively were evaluated using Nakagami-m parametric imaging and ultrasound B-mode imaging. The lesion sizes estimated using Nakagami-m parametric imaging technique were all closer to the actual sizes than those of B-mode imaging. The p-value obtained from the t-test between the mean m values of thermal coagulation and cavitation erosion was smaller than 0.05, demonstrating that the m values of thermal lesions were significantly different from that of mechanical lesions, which was confirmed by ex vivo experiments and histologic examination showed that different changes result from HIFU exposure, one of tissue dehydration resulting from the thermal effect, and the other of tissue homogenate resulting from mechanical effect. This study demonstrated that Nakagami-m parametric imaging is a potential real-time imaging technique for evaluating and differentiating thermal coagulation and cavitation erosion. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

PubMed

Yang, Li; Wang, Guobao; Qi, Jinyi

2016-04-01

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

Acoustic Characterization of Fluorinert FC-43 Liquid with Helium Gas Bubbles: Numerical Experiments

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

Vanhille, Christian; Pantea, Cristian; Sinha, Dipen N.

In this work, we define the acoustic characteristics of a biphasic fluid consisting of static helium gas bubbles in liquid Fluorinert FC-43 and study the propagation of ultrasound of finite amplitudes in this medium. Very low sound speed and high sound attenuation are found, in addition to a particularly high acoustic nonlinear parameter. This result suggests the possibility of using this medium as a nonlinear enhancer in various applications. In particular, parametric generation of low ultrasonic frequencies is studied in a resonator cavity as a function of driving pressure showing high conversion efficiency. This work suggests that this medium couldmore » be used for applications such as parametric arrays, nondestructive testing, diagnostic medicine, sonochemistry, underwater acoustics, and ultrasonic imaging and to boost the shock formation in fluids.« less

Acoustic Characterization of Fluorinert FC-43 Liquid with Helium Gas Bubbles: Numerical Experiments

DOE PAGES

Vanhille, Christian; Pantea, Cristian; Sinha, Dipen N.

2017-01-19

In this work, we define the acoustic characteristics of a biphasic fluid consisting of static helium gas bubbles in liquid Fluorinert FC-43 and study the propagation of ultrasound of finite amplitudes in this medium. Very low sound speed and high sound attenuation are found, in addition to a particularly high acoustic nonlinear parameter. This result suggests the possibility of using this medium as a nonlinear enhancer in various applications. In particular, parametric generation of low ultrasonic frequencies is studied in a resonator cavity as a function of driving pressure showing high conversion efficiency. This work suggests that this medium couldmore » be used for applications such as parametric arrays, nondestructive testing, diagnostic medicine, sonochemistry, underwater acoustics, and ultrasonic imaging and to boost the shock formation in fluids.« less

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

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.

TU-H-CAMPUS-IeP3-02: Neurovascular 4D Parametric Imaging Using Co-Registration of Biplane DSA Sequences with 3D Vascular Geometry Obtained From Cone Beam CT

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

Balasubramoniam, A; Bednarek, D; Rudin, S

Purpose: To create 4D parametric images using biplane Digital Subtraction Angiography (DSA) sequences co-registered with the 3D vascular geometry obtained from Cone Beam-CT (CBCT). Methods: We investigated a method to derive multiple 4D Parametric Imaging (PI) maps using only one CBCT acquisition. During this procedure a 3D-DSA geometry is stored and used subsequently for all 4D images. Each time a biplane DSA is acquired, we calculate 2D parametric maps of Bolus Arrival Time (BAT), Mean Transit Time (MTT) and Time to Peak (TTP). Arterial segments which are nearly parallel with one of the biplane imaging planes in the 2D parametricmore » maps are co-registered with the 3D geometry. The values in the remaining vascular network are found using spline interpolation since the points chosen for co-registration on the vasculature are discrete and remaining regions need to be interpolated. To evaluate the method we used a patient CT volume data set for 3D printing a neurovascular phantom containing a complete Circle of Willis. We connected the phantom to a flow loop with a peristaltic pump, simulating physiological flow conditions. Contrast media was injected with an automatic injector at 10 ml/sec. Images were acquired with a Toshiba Infinix C-arm and 4D parametric image maps of the vasculature were calculated. Results: 4D BAT, MTT, and TTP parametric image maps of the Circle of Willis were derived. We generated color-coded 3D geometries which avoided artifacts due to vessel overlap or foreshortening in the projection direction. Conclusion: The software was tested successfully and multiple 4D parametric images were obtained from biplane DSA sequences without the need to acquire additional 3D-DSA runs. This can benefit the patient by reducing the contrast media and the radiation dose normally associated with these procedures. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies.

PubMed

Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross

2016-06-01

To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dpetstep images and noise properties agreed better with MC. The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dpetstep can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

Parametric Methods for Dynamic 11C-Phenytoin PET Studies.

PubMed

Mansor, Syahir; Yaqub, Maqsood; Boellaard, Ronald; Froklage, Femke E; de Vries, Anke; Bakker, Esther D M; Voskuyl, Rob A; Eriksson, Jonas; Schwarte, Lothar A; Verbeek, Joost; Windhorst, Albert D; Lammertsma, Adriaan A

2017-03-01

In this study, the performance of various methods for generating quantitative parametric images of dynamic 11 C-phenytoin PET studies was evaluated. Methods: Double-baseline 60-min dynamic 11 C-phenytoin PET studies, including online arterial sampling, were acquired for 6 healthy subjects. Parametric images were generated using Logan plot analysis, a basis function method, and spectral analysis. Parametric distribution volume (V T ) and influx rate ( K 1 ) were compared with those obtained from nonlinear regression analysis of time-activity curves. In addition, global and regional test-retest (TRT) variability was determined for parametric K 1 and V T values. Results: Biases in V T observed with all parametric methods were less than 5%. For K 1 , spectral analysis showed a negative bias of 16%. The mean TRT variabilities of V T and K 1 were less than 10% for all methods. Shortening the scan duration to 45 min provided similar V T and K 1 with comparable TRT performance compared with 60-min data. Conclusion: Among the various parametric methods tested, the basis function method provided parametric V T and K 1 values with the least bias compared with nonlinear regression data and showed TRT variabilities lower than 5%, also for smaller volume-of-interest sizes (i.e., higher noise levels) and shorter scan duration. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

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

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.

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.

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.

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

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

Häggström, Ida, E-mail: haeggsti@mskcc.org; Beattie, Bradley J.; Schmidtlein, C. Ross

2016-06-15

Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuationmore » are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.« less

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

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.

Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.

PubMed

Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien

2017-01-01

Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.

Effects of Regularisation Priors and Anatomical Partial Volume Correction on Dynamic PET Data

NASA Astrophysics Data System (ADS)

Caldeira, Liliana L.; Silva, Nuno da; Scheins, Jürgen J.; Gaens, Michaela E.; Shah, N. Jon

2015-08-01

Dynamic PET provides temporal information about the tracer uptake. However, each PET frame has usually low statistics, resulting in noisy images. Furthermore, PET images suffer from partial volume effects. The goal of this study is to understand the effects of prior regularisation on dynamic PET data and subsequent anatomical partial volume correction. The Median Root Prior (MRP) regularisation method was used in this work during reconstruction. The quantification and noise in image-domain and time-domain (time-activity curves) as well as the impact on parametric images is assessed and compared with Ordinary Poisson Ordered Subset Expectation Maximisation (OP-OSEM) reconstruction with and without Gaussian filter. This study shows the improvement in PET images and time-activity curves (TAC) in terms of noise as well as in the parametric images when using prior regularisation in dynamic PET data. Anatomical partial volume correction improves the TAC and consequently, parametric images. Therefore, the use of MRP with anatomical partial volume correction is of interest for dynamic PET studies.

Parametric imaging using subharmonic signals from ultrasound contrast agents in patients with breast lesions.

PubMed

Eisenbrey, John R; Dave, Jaydev K; Merton, Daniel A; Palazzo, Juan P; Hall, Anne L; Forsberg, Flemming

2011-01-01

Parametric maps showing perfusion of contrast media can be useful tools for characterizing lesions in breast tissue. In this study we show the feasibility of parametric subharmonic imaging (SHI), which allows imaging of a vascular marker (the ultrasound contrast agent) while providing near complete tissue suppression. Digital SHI clips of 16 breast lesions from 14 women were acquired. Patients were scanned using a modified LOGIQ 9 scanner (GE Healthcare, Waukesha, WI) transmitting/receiving at 4.4/2.2 MHz. Using motion-compensated cumulative maximum intensity (CMI) sequences, parametric maps were generated for each lesion showing the time to peak (TTP), estimated perfusion (EP), and area under the time-intensity curve (AUC). Findings were grouped and compared according to biopsy results as benign lesions (n = 12, including 5 fibroadenomas and 3 cysts) and carcinomas (n = 4). For each lesion CMI, TTP, EP, and AUC parametric images were generated. No significant variations were detected with CMI (P = .80), TTP (P = .35), or AUC (P = .65). A statistically significant variation was detected for the average pixel EP (P = .002). Especially, differences were seen between carcinoma and benign lesions (mean ± SD, 0.10 ± 0.03 versus 0.05 ± 0.02 intensity units [IU]/s; P = .0014) and between carcinoma and fibroadenoma (0.10 ± 0.03 versus 0.04 ± 0.01 IU/s; P = .0044), whereas differences between carcinomas and cysts were found to be nonsignificant. In conclusion, a parametric imaging method for characterization of breast lesions using the high contrast to tissue signal provided by SHI has been developed. While the preliminary sample size was limited, results show potential for breast lesion characterization based on perfusion flow parameters.

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).

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.

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.

Direct Metal Deposition of H13 Tool Steel on Copper Alloy Substrate: Parametric Investigation

NASA Astrophysics Data System (ADS)

Imran, M. Khalid; Masood, S. H.; Brandt, Milan

2015-12-01

Over the past decade, researchers have demonstrated interest in tribology and prototyping by the laser aided material deposition process. Laser aided direct metal deposition (DMD) enables the formation of a uniform clad by melting the powder to form desired component from metal powder materials. In this research H13 tool steel has been used to clad on a copper alloy substrate using DMD. The effects of laser parameters on the quality of DMD deposited clad have been investigated and acceptable processing parameters have been determined largely through trial-and-error approaches. The relationships between DMD process parameters and the product characteristics such as porosity, micro-cracks and microhardness have been analysed using scanning electron microscope (SEM), image analysis software (ImageJ) and microhardness tester. It has been found that DMD parameters such as laser power, powder mass flow rate, feed rate and focus size have an important role in clad quality and crack formation.

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.

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.

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

Direct reconstruction of parametric images for brain PET with event-by-event motion correction: evaluation in two tracers across count levels

NASA Astrophysics Data System (ADS)

Germino, Mary; Gallezot, Jean-Dominque; Yan, Jianhua; Carson, Richard E.

2017-07-01

Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, ‘direct reconstruction’, incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [11C]AFM (serotonin transporter) and [11C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K 1 and distribution volume (V T  =  K 1/k 2) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K 1 and V T with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K 1 CoV by 35-48% (simulated dataset), 39-43% ([11C]AFM dataset) and 30-36% ([11C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V T CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V T by 51% on average in the [11C]UCB-J dataset. Direct reconstruction of dynamic brain PET with event-by-event motion correction is achievable and dramatically more robust to noise in V T images than the indirect method.

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.

Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach

PubMed Central

Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M.; El Fakhri, Georges

2013-01-01

Purpose: Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Methods: Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. Results: At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%–29% and 32%–70% for 50 × 106 and 10 × 106 detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40–50 iterations), while more than 500 iterations were needed for CG. Conclusions: The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method. PMID:24089922

Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

PubMed

Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges

2013-10-01

Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.

Three-Dimensional Unstained Live-Cell Imaging Using Stimulated Parametric Emission Microscopy

NASA Astrophysics Data System (ADS)

Dang, Hieu M.; Kawasumi, Takehito; Omura, Gen; Umano, Toshiyuki; Kajiyama, Shin'ichiro; Ozeki, Yasuyuki; Itoh, Kazuyoshi; Fukui, Kiichi

2009-09-01

The ability to perform high-resolution unstained live imaging is very important to in vivo study of cell structures and functions. Stimulated parametric emission (SPE) microscopy is a nonlinear-optical microscopy based on ultra-fast electronic nonlinear-optical responses. For the first time, we have successfully applied this technique to archive three-dimensional (3D) images of unstained sub-cellular structures, such as, microtubules, nuclei, nucleoli, etc. in live cells. Observation of a complete cell division confirms the ability of SPE microscopy for long time-scale imaging.

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.

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

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

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.

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.

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.

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

The Route to an Integrative Associative Memory Is Influenced by Emotion

PubMed Central

Murray, Brendan D.; Kensinger, Elizabeth A.

2014-01-01

Though the hippocampus typically has been implicated in processes related to associative binding, special types of associations – such as those created by integrative mental imagery – may be supported by processes implemented in other medial temporal-lobe or sensory processing regions. Here, we investigated what neural mechanisms underlie the formation and subsequent retrieval of integrated mental images, and whether those mechanisms differ based on the emotionality of the integration (i.e., whether it contains an emotional item or not). Participants viewed pairs of words while undergoing a functional MRI scan. They were instructed to imagine the two items separately from one another (“non-integrative” study) or as a single, integrated mental image (“integrative” study). They provided ratings of how successful they were at generating vivid images that fit the instructions. They were then given a surprise associative recognition test, also while undergoing an fMRI scan. The cuneus showed parametric correspondence to increasing imagery success selectively during encoding and retrieval of emotional integrations, while the parahippocampal gyri and prefrontal cortices showed parametric correspondence during the encoding and retrieval of non-emotional integrations. Connectivity analysis revealed that selectively during negative integration, left amygdala activity was negatively correlated with frontal and hippocampal activity. These data indicate that individuals utilize two different neural routes for forming and retrieving integrations depending on their emotional content, and they suggest a potentially disruptive role for the amygdala on frontal and medial-temporal regions during negative integration. PMID:24427267

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

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.

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.

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.

Method of development of the program of forming of parametrical drawings of details in the AutoCAD software product

NASA Astrophysics Data System (ADS)

Alshakova, E. L.

2017-01-01

The program in the AutoLISP language allows automatically to form parametrical drawings during the work in the AutoCAD software product. Students study development of programs on AutoLISP language with the use of the methodical complex containing methodical instructions in which real examples of creation of images and drawings are realized. Methodical instructions contain reference information necessary for the performance of the offered tasks. The method of step-by-step development of the program is the basis for training in programming on AutoLISP language: the program draws elements of the drawing of a detail by means of definitely created function which values of arguments register in that sequence in which AutoCAD gives out inquiries when performing the corresponding command in the editor. The process of the program design is reduced to the process of step-by-step formation of functions and sequence of their calls. The author considers the development of the AutoLISP program for the creation of parametrical drawings of details, the defined design, the user enters the dimensions of elements of details. These programs generate variants of tasks of the graphic works performed in educational process of "Engineering graphics", "Engineering and computer graphics" disciplines. Individual tasks allow to develop at students skills of independent work in reading and creation of drawings, as well as 3D modeling.

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

ACCELERATING MR PARAMETER MAPPING USING SPARSITY-PROMOTING REGULARIZATION IN PARAMETRIC DIMENSION

PubMed Central

Velikina, Julia V.; Alexander, Andrew L.; Samsonov, Alexey

2013-01-01

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which utilizes smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist. PMID:23213053

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.

The most complete photometric analysis of 548 CALIFA galaxies

NASA Astrophysics Data System (ADS)

Gilhuly, Colleen

We present an extensive photometric catalog for 548 CALIFA galaxies observed as of the summer of 2015. CALIFA is currently lacking photometry matching the scale and diversity of its spectroscopy; this work is intended to meet all photometric needs for CALIFA galaxies while also identifying best photometric practices for upcoming integral field spectroscopy surveys such as SAMI and MaNGA. This catalog comprises gri surface brightness profiles derived from Sloan Digital Sky Survey (SDSS) imaging, a variety of non-parametric quantities extracted from these pro files, and parametric models fitted to the i-band pro files (1D) and original galaxy images (2D). To compliment our photometric analysis, we contrast the relative performance of our 1D and 2D modelling approaches. The ability of each measurement to characterize the global properties of galaxies is quantitatively assessed, in the context of constructing the tightest scaling relations. Where possible, we compare our photometry with existing photometrically or spectroscopically obtained measurements from the literature. Close agreement is found with Walcher et al. (2014), the current source of basic photometry and classifications of CALIFA galaxies, while comparisons with spectroscopically derived quantities reveals the effect of CALIFA's limited field of view compared to broadband imaging surveys such as the SDSS. The colour-magnitude diagram, star formation main sequence, and Tully-Fisher relation of CALIFA galaxies are studied, to give a small example of the investigations possible with this rich catalog. We conclude with a discussion of points of concern for ongoing integral field spectroscopy surveys and directions for future expansion and exploitation of this work.

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.

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

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

RCSED—A Value-added Reference Catalog of Spectral Energy Distributions of 800,299 Galaxies in 11 Ultraviolet, Optical, and Near-infrared Bands: Morphologies, Colors, Ionized Gas, and Stellar Population Properties

NASA Astrophysics Data System (ADS)

Chilingarian, Igor V.; Zolotukhin, Ivan Yu.; Katkov, Ivan Yu.; Melchior, Anne-Laure; Rubtsov, Evgeniy V.; Grishin, Kirill A.

2017-02-01

We present RCSED, the value-added Reference Catalog of Spectral Energy Distributions of galaxies, which contains homogenized spectrophotometric data for 800,299 low- and intermediate-redshift galaxies (0.007< z< 0.6) selected from the Sloan Digital Sky Survey spectroscopic sample. Accessible from the Virtual Observatory (VO) and complemented with detailed information on galaxy properties obtained with state-of-the-art data analysis, RCSED enables direct studies of galaxy formation and evolution over the last 5 Gyr. We provide tabulated color transformations for galaxies of different morphologies and luminosities, and analytic expressions for the red sequence shape in different colors. RCSED comprises integrated k-corrected photometry in up to 11 ultraviolet, optical, and near-infrared bands published by the GALEX, SDSS, and UKIDSS wide-field imaging surveys; results of the stellar population fitting of SDSS spectra including best-fitting templates, velocity dispersions, parameterized star formation histories, and stellar metallicities computed for instantaneous starburst and exponentially declining star formation models; parametric and non-parametric emission line fluxes and profiles; and gas phase metallicities. We link RCSED to the Galaxy Zoo morphological classification and galaxy bulge+disk decomposition results of Simard et al. We construct the color-magnitude, Faber-Jackson, and mass-metallicity relations; compare them with the literature; and discuss systematic errors of the galaxy properties presented in our catalog. RCSED is accessible from the project web site and via VO simple spectrum access and table access services using VO-compliant applications. We describe several examples of SQL queries to the database. Finally, we briefly discuss existing and future scientific applications of RCSED and prospective catalog extensions to higher redshifts and different wavelengths. .

An analytical parametric study of the broadband noise from axial-flow fans

NASA Technical Reports Server (NTRS)

Chou, Shau-Tak; George, Albert R.

1987-01-01

The rotating dipole analysis of Ffowcs Williams and Hawkings (1969) is used to predict the far field noise radiation due to various rotor broadband noise mechanisms. Consideration is given to inflow turbulence noise, attached boundary layer/trailing-edge interaction noise, tip-vortex formation noise, and trailing-edge thickness noise. The parametric dependence of broadband noise from unducted axial-flow fans on several critical variables is studied theoretically. The angle of attack of the rotor blades, which is related to the rotor performance, is shown to be important to the trailing-edge noise and to the tip-vortex formation noise.

Lunar and Planetary Science XXXV: Venus

NASA Technical Reports Server (NTRS)

2004-01-01

The session "Venus" included the following reports:Preliminary Study of Laser-induced Breakdown Spectroscopy (LIBS) for a Venus Mission; Venus Surface Investigation Using VIRTIS Onboard the ESA/Venus Express Mission; Use of Magellan Images for Venus Landing Safety Assessment; Volatile Element Geochemistry in the Lower Atmosphere of Venus; Resurfacing Styles and Rates on Venus: Assessment of 18 Venusian Quadrangles; Stereo Imaging of Impact Craters in the Beta-Atla-Themis (BAT) Region, Venus; Depths of Extended Crater-related Deposits on Venus ; Potential Pyroclastic Deposit in the Nemesis Tessera (V14) Quadrangle of Venus; Relationship Between Coronae, Regional Plains and Rift Zones on Venus, Preliminary Results; Coronae of Parga Chasma, Venus; The Evolution of Four Volcano/Corona Hybrids on Venus; Calderas on Venus and Earth: Comparison and Models of Formation; Venus Festoon Deposits: Analysis of Characteristics and Modes of Emplacement; Topographic and Structural Analysis of Devana Chasma, Venus: A Propagating Rift System; Anomalous Radial Structures at Irnini Mons, Venus: A Parametric Study of Stresses on a Pressurized Hole; Analysis of Gravity and Topography Signals in Atalanta-Vinmara and Lavinia Planitiae Canali are Lava, Not River, Channels; and Formation of Venusian Channels in a Shield Paint Substrate.

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.

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

Reconstructing The Star Formation Histories Of Galaxies Through Sed Fitting Using The Dense Basis Method

NASA Astrophysics Data System (ADS)

Iyer, Kartheik; Gawiser, Eric

2017-06-01

The Dense Basis SED fitting method reveals previously inaccessible information about the number and duration of star formation episodes and the timing of stellar mass assembly as well as uncertainties in these quantities, in addition to accurately recovering traditional SED parameters including M*, SFR and dust attenuation. This is done using basis Star Formation Histories (SFHs) chosen by comparing the goodness-of-fit of mock galaxy SEDs to the goodness-of-reconstruction of their SFHs, trained and validated using three independent datasets of mock galaxies at z=1 from SAMs, Hydrodynamic simulations and stochastic realizations. Of the six parametrizations of SFHs considered, we reject the traditional parametrizations of constant and exponential SFHs and suggest four novel improvements, quantifying the bias and scatter of each parametrization. We then apply the method to a sample of 1100 CANDELS GOODS-S galaxies at 110^9 M_sun, in contrast to current simulations. About 40% of the CANDEL galaxies have SFHs whose maximum occurs at or near the epoch of observation. These results are presented in Iyer and Gawiser (2017, ApJ 838 127), available at https://arxiv.org/abs/1702.04371

Unveiling the Shape Evolution and Halide-Ion-Segregation in Blue-Emitting Formamidinium Lead Halide Perovskite Nanocrystals Using an Automated Microfluidic Platform.

PubMed

Lignos, Ioannis; Protesescu, Loredana; Emiroglu, Dilara Börte; Maceiczyk, Richard; Schneider, Simon; Kovalenko, Maksym V; deMello, Andrew J

2018-02-14

Hybrid organic-inorganic perovskites and in particular formamidinium lead halide (FAPbX 3 , X = Cl, Br, I) perovskite nanocrystals (NCs) have shown great promise for their implementation in optoelectronic devices. Specifically, the Br and I counterparts have shown unprecedented photoluminescence properties, including precise wavelength tuning (530-790 nm), narrow emission linewidths (<100 meV) and high photoluminescence quantum yields (70-90%). However, the controlled formation of blue emitting FAPb(Cl 1-x Br x ) 3 NCs lags behind their green and red counterparts and the mechanism of their formation remains unclear. Herein, we report the formation of FAPb(Cl 1-x Br x ) 3 NCs with stable emission between 440 and 520 nm in a fully automated droplet-based microfluidic reactor and subsequent reaction upscaling in conventional laboratory glassware. The thorough parametric screening allows for the elucidation of parametric zones (FA-to-Pb and Br-to-Cl molar ratios, temperature, and excess oleic acid) for the formation of nanoplatelets and/or NCs. In contrast to CsPb(Cl 1-x Br x ) 3 NCs, based on online parametric screening and offline structural characterization, we demonstrate that the controlled synthesis of Cl-rich perovskites (above 60 at% Cl) with stable emission remains a challenge due to fast segregation of halide ions.

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.

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.

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.

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.

Polariton Pattern Formation and Photon Statistics of the Associated Emission

NASA Astrophysics Data System (ADS)

Whittaker, C. E.; Dzurnak, B.; Egorov, O. A.; Buonaiuto, G.; Walker, P. M.; Cancellieri, E.; Whittaker, D. M.; Clarke, E.; Gavrilov, S. S.; Skolnick, M. S.; Krizhanovskii, D. N.

2017-07-01

We report on the formation of a diverse family of transverse spatial polygon patterns in a microcavity polariton fluid under coherent driving by a blue-detuned pump. Patterns emerge spontaneously as a result of energy-degenerate polariton-polariton scattering from the pump state to interfering high-order vortex and antivortex modes, breaking azimuthal symmetry. The interplay between a multimode parametric instability and intrinsic optical bistability leads to a sharp spike in the value of second-order coherence g(2 )(0 ) of the emitted light, which we attribute to the strongly superlinear kinetics of the underlying scattering processes driving the formation of patterns. We show numerically by means of a linear stability analysis how the growth of parametric instabilities in our system can lead to spontaneous symmetry breaking, predicting the formation and competition of different pattern states in good agreement with experimental observations.

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 .

Impact of temporal, spatial and cascaded effects on the pulse formation in ultra-broadband parametric amplifiers.

PubMed

Lang, T; Harth, A; Matyschok, J; Binhammer, T; Schultze, M; Morgner, U

2013-01-14

A 2 + 1 dimensional nonlinear pulse propagation model is presented, illustrating the weighting of different effects for the parametric amplification of ultra-broadband spectra in different regimes of energy scaling. Typical features in the distribution of intensity and phase of state-of-the-art OPA-systems can be understood by cascaded spatial and temporal effects.

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.

Integrated software environment based on COMKAT for analyzing tracer pharmacokinetics with molecular imaging.

PubMed

Fang, Yu-Hua Dean; Asthana, Pravesh; Salinas, Cristian; Huang, Hsuan-Ming; Muzic, Raymond F

2010-01-01

An integrated software package, Compartment Model Kinetic Analysis Tool (COMKAT), is presented in this report. COMKAT is an open-source software package with many functions for incorporating pharmacokinetic analysis in molecular imaging research and has both command-line and graphical user interfaces. With COMKAT, users may load and display images, draw regions of interest, load input functions, select kinetic models from a predefined list, or create a novel model and perform parameter estimation, all without having to write any computer code. For image analysis, COMKAT image tool supports multiple image file formats, including the Digital Imaging and Communications in Medicine (DICOM) standard. Image contrast, zoom, reslicing, display color table, and frame summation can be adjusted in COMKAT image tool. It also displays and automatically registers images from 2 modalities. Parametric imaging capability is provided and can be combined with the distributed computing support to enhance computation speeds. For users without MATLAB licenses, a compiled, executable version of COMKAT is available, although it currently has only a subset of the full COMKAT capability. Both the compiled and the noncompiled versions of COMKAT are free for academic research use. Extensive documentation, examples, and COMKAT itself are available on its wiki-based Web site, http://comkat.case.edu. Users are encouraged to contribute, sharing their experience, examples, and extensions of COMKAT. With integrated functionality specifically designed for imaging and kinetic modeling analysis, COMKAT can be used as a software environment for molecular imaging and pharmacokinetic analysis.

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.

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

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.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials.

PubMed

Zadpoor, Amir A

2017-07-25

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials

PubMed Central

Zadpoor, Amir A.

2017-01-01

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes. PMID:28757572

Analysis of Parametric Adaptive Signal Detection with Applications to Radars and Hyperspectral Imaging

DTIC Science & Technology

2010-02-01

98 8.4.5 Training Screening ............................. .................................................................99 8.5 Experimental...associated with the proposed parametric model. Several im- portant issues are discussed, including model order selection, training screening , and time...parameters associated with the NS-AR model. In addition, we develop model order selection, training screening , and time-series based whitening and

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.

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.

apART: system for the acquisition, processing, archiving, and retrieval of digital images in an open, distributed imaging environment

NASA Astrophysics Data System (ADS)

Schneider, Uwe; Strack, Ruediger

1992-04-01

apART reflects the structure of an open, distributed environment. According to the general trend in the area of imaging, network-capable, general purpose workstations with capabilities of open system image communication and image input are used. Several heterogeneous components like CCD cameras, slide scanners, and image archives can be accessed. The system is driven by an object-oriented user interface where devices (image sources and destinations), operators (derived from a commercial image processing library), and images (of different data types) are managed and presented uniformly to the user. Browsing mechanisms are used to traverse devices, operators, and images. An audit trail mechanism is offered to record interactive operations on low-resolution image derivatives. These operations are processed off-line on the original image. Thus, the processing of extremely high-resolution raster images is possible, and the performance of resolution dependent operations is enhanced significantly during interaction. An object-oriented database system (APRIL), which can be browsed, is integrated into the system. Attribute retrieval is supported by the user interface. Other essential features of the system include: implementation on top of the X Window System (X11R4) and the OSF/Motif widget set; a SUN4 general purpose workstation, inclusive ethernet, magneto optical disc, etc., as the hardware platform for the user interface; complete graphical-interactive parametrization of all operators; support of different image interchange formats (GIF, TIFF, IIF, etc.); consideration of current IPI standard activities within ISO/IEC for further refinement and extensions.

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.

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.

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

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.

Lesion registration for longitudinal disease tracking in an imaging informatics-based multiple sclerosis eFolder

NASA Astrophysics Data System (ADS)

Ma, Kevin; Liu, Joseph; Zhang, Xuejun; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2016-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system needs to quantify lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. In order to perform lesion registration, we have developed a brain warping and normalizing methodology using Statistical Parametric Mapping (SPM) MATLAB toolkit for brain MRI. Patients' brain MR images are processed via SPM's normalization processes, and the brain images are analyzed and warped according to the tissue probability map. Lesion identification and contouring are completed by neuroradiologists, and lesion volume quantification is completed by the eFolder's CAD program. Lesion comparison results in longitudinal studies show key growth and active regions. The results display successful lesion registration and tracking over a longitudinal study. Lesion change results are graphically represented in the web-based user interface, and users are able to correlate patient progress and changes in the MRI images. The completed lesion and disease tracking tool would enable the eFolder to provide complete patient profiles, improve the efficiency of patient care, and perform comprehensive data analysis through an integrated imaging informatics system.

Multi-parametric surface plasmon resonance platform for studying liposome-serum interactions and protein corona formation.

PubMed

Kari, Otto K; Rojalin, Tatu; Salmaso, Stefano; Barattin, Michela; Jarva, Hanna; Meri, Seppo; Yliperttula, Marjo; Viitala, Tapani; Urtti, Arto

2017-04-01

When nanocarriers are administered into the blood circulation, a complex biomolecular layer known as the "protein corona" associates with their surface. Although the drivers of corona formation are not known, it is widely accepted that this layer mediates biological interactions of the nanocarrier with its surroundings. Label-free optical methods can be used to study protein corona formation without interfering with its dynamics. We demonstrate the proof-of-concept for a multi-parametric surface plasmon resonance (MP-SPR) technique in monitoring the formation of a protein corona on surface-immobilized liposomes subjected to flowing 100 % human serum. We observed the formation of formulation-dependent "hard" and "soft" coronas with distinct refractive indices, layer thicknesses, and surface mass densities. MP-SPR was also employed to determine the affinity (K D ) of a complement system molecule (C3b) with cationic liposomes with and without polyethylene glycol. Tendency to create a thick corona correlated with a higher affinity of opsonin C3b for the surface. The label-free platform provides a fast and robust preclinical tool for tuning nanocarrier surface architecture and composition to control protein corona formation.

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.

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.

Effect of Micro-Bubbles in Water on Beam Patterns of Parametric Array

NASA Astrophysics Data System (ADS)

Hashiba, Kunio; Masuzawa, Hiroshi

2003-05-01

The improvement in efficiency of a parametric array by nonlinear oscillation of micro-bubbles in water is studied in this paper. The micro-bubble oscillation can increase the nonlinear coefficient of the acoustic medium. The amplitude of the difference-frequency wave along the longitudinal axis and its beam patterns in the field including the layer with micro-bubbles were analyzed using a Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation. As a result, the largest improvement in efficiency was obtained and a narrow parametric beam was formed by forming a layer with micro-bubbles in front of a parametric sound radiator as thick as about the shock formation distance. If the layer becomes significantly thicker than the distance, the beam of the difference-frequency wave in the far-field will become broader. If the layer is significantly thinner than the distance, the intensity level of the wave in the far-field will be too low.

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.

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.

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.

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.

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.

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.

Adaptive matched filter spatial detection performance on standard imagery from a wideband VHF/UHF SAR

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

Allen, M.R.; Phillips, S.A.; Sofianos, D.J.

1994-12-31

The adaptive matched filter was implemented as a spatial detector for amplitude-only or complex images, and applied to an image formed by standard narrow band means from a wide angle, wideband radar. Direct performance comparisons were made between different implementations and various matched and mismatched cases by using a novel approach to generate ROC curves parametrically. For perfectly matched cases, performance using imaged targets was found to be significantly lower than potential performance of artificial targets whose features differed from the background. Incremental gain due to whitening the background was also found to be small, indicating little background spatial correlation.more » It is conjectured that the relatively featureless behavior in both targets and background is due to the image formation process, since this technique averages together all wide angle, wideband information. For mismatched cases where the signature was unknown, the amplitude detector losses were approximately equal to whatever gain over noncoherent integration that matching provided. However, the complex detector was generally very sensitive to unknown information, especially phase, and produced much larger losses. Whitening under these mismatched conditions produced further losses. Detector choice thus depends primarily on how reproducible target signatures are, especially if phase is used, and the subsequent number of stored signatures necessary to account for various imaging aspect angles.« less

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.

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.

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.

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

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping

PubMed Central

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-01-01

Background Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. Methods The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). Results A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. Conclusion The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques. PMID:18312639

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping.

PubMed

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-02-29

Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.

Temporal Simultons in Optical Parametric Oscillators

NASA Astrophysics Data System (ADS)

Jankowski, Marc; Marandi, Alireza; Phillips, C. R.; Hamerly, Ryan; Ingold, Kirk A.; Byer, Robert L.; Fejer, M. M.

2018-02-01

We report the first demonstration of a regime of operation in optical parametric oscillators (OPOs), in which the formation of temporal simultons produces stable femtosecond half-harmonic pulses. Simultons are simultaneous bright-dark solitons of a signal field at frequency ω and the pump field at 2 ω , which form in a quadratic nonlinear medium. The formation of simultons in an OPO is due to the interplay of nonlinear pulse acceleration with the timing mismatch between the pump repetition period and the cold-cavity round-trip time and is evidenced by sech2 spectra with broad instantaneous bandwidths when the resonator is detuned to a slightly longer round-trip time than the pump repetition period. We provide a theoretical description of an OPO operating in a regime dominated by these dynamics, observe the distinct features of simulton formation in an experiment, and verify our results with numerical simulations. These results represent a new regime of operation in nonlinear resonators, which can lead to efficient and scalable sources of few-cycle frequency combs at arbitrary wavelengths.

Dense granular flow around a rigid or flexible intruder

NASA Astrophysics Data System (ADS)

Kolb, Evelyne; Adda-Bedia, Mokhtar

2012-02-01

We experimentally studied the flow of a dense granular material around an obstacle (rigid cylinder or flexible plate) placed in a 2 dimensional confined cell at a packing fraction near the 2D jamming threshold. In the case of the rigid obstacle, the displacement field of grains as well as the drag force experienced by the obstacle were simultaneously recorded and a parametric study was done by changing the cell size, the intruder diameter or the packing fraction. The drag force experienced by the intruder and the formation of a wake behind the obstacle were very sensitive to the approach to jamming. The same experimental set-up was adapted to a flexible intruder and coupling between the granular flow and fibre deflexion were imaged. The deformation of the fibre could be compared with theoretical predictions from elastica.

Fractional motion model for characterization of anomalous diffusion from NMR signals.

PubMed

Fan, Yang; Gao, Jia-Hong

2015-07-01

Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

Fractional motion model for characterization of anomalous diffusion from NMR signals

NASA Astrophysics Data System (ADS)

Fan, Yang; Gao, Jia-Hong

2015-07-01

Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

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.

Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques.

PubMed

Caixinha, Miguel; Santos, Mário; Santos, Jaime

2016-04-01

To demonstrate the feasibility of a new methodology for cataract hardness characterization and automatic classification using ultrasound techniques, different cataract degrees were induced in 210 porcine lenses. A 25-MHz ultrasound transducer was used to obtain acoustical parameters (velocity and attenuation) and backscattering signals. B-Scan and parametric Nakagami images were constructed. Ninety-seven parameters were extracted and subjected to a Principal Component Analysis. Bayes, K-Nearest-Neighbours, Fisher Linear Discriminant and Support Vector Machine (SVM) classifiers were used to automatically classify the different cataract severities. Statistically significant increases with cataract formation were found for velocity, attenuation, mean brightness intensity of the B-Scan images and mean Nakagami m parameter (p < 0.01). The four classifiers showed a good performance for healthy versus cataractous lenses (F-measure ≥ 92.68%), while for initial versus severe cataracts the SVM classifier showed the higher performance (90.62%). The results showed that ultrasound techniques can be used for non-invasive cataract hardness characterization and automatic classification. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

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.

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.

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

NASA Astrophysics Data System (ADS)

Bereau, Tristan; Wang, Zun-Jing; Deserno, Markus

2014-03-01

Interfacial systems are at the core of fascinating phenomena in many disciplines, such as biochemistry, soft-matter physics, and food science. However, the parametrization of accurate, reliable, and consistent coarse-grained (CG) models for systems at interfaces remains a challenging endeavor. In the present work, we explore to what extent two independently developed solvent-free CG models of peptides and lipids—of different mapping schemes, parametrization methods, target functions, and validation criteria—can be combined by only tuning the cross-interactions. Our results show that the cross-parametrization can reproduce a number of structural properties of membrane peptides (for example, tilt and hydrophobic mismatch), in agreement with existing peptide-lipid CG force fields. We find encouraging results for two challenging biophysical problems: (i) membrane pore formation mediated by the cooperative action of several antimicrobial peptides, and (ii) the insertion and folding of the helix-forming peptide WALP23 in the membrane.

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.

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.

Parametric amplification of a superconducting plasma wave

DOE PAGES

Rajasekaran, S.; Casandruc, E.; Laplace, Y.; ...

2016-07-11

Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor–metal oscillations and soliton formation. In this paper, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Finally, parametric amplification is sensitivemore » to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.« less

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.

Pattern formation without diffraction matching in optical parametric oscillators with a metamaterial.

PubMed

Tassin, Philippe; Van der Sande, Guy; Veretennicoff, Irina; Kockaert, Pascal; Tlidi, Mustapha

2009-05-25

We consider a degenerate optical parametric oscillator containing a left-handed material. We show that the inclusion of a left-handed material layer allows for controlling the strength and sign of the diffraction coefficient at either the pump or the signal frequency. Subsequently, we demonstrate the existence of stable dissipative structures without diffraction matching, i.e., without the usual relationship between the diffraction coefficients of the signal and pump fields. Finally, we investigate the size scaling of these light structures with decreasing diffraction strength.

Numerical parametric studies of spray combustion instability

NASA Technical Reports Server (NTRS)

Pindera, M. Z.

1993-01-01

A coupled numerical algorithm has been developed for studies of combustion instabilities in spray-driven liquid rocket engines. The model couples gas and liquid phase physics using the method of fractional steps. Also introduced is a novel, efficient methodology for accounting for spray formation through direct solution of liquid phase equations. Preliminary parametric studies show marked sensitivity of spray penetration and geometry to droplet diameter, considerations of liquid core, and acoustic interactions. Less sensitivity was shown to the combustion model type although more rigorous (multi-step) formulations may be needed for the differences to become apparent.

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

Two-dimensional numerical simulation of acoustic wave phase conjugation in magnetostrictive elastic media.

PubMed

Voinovich, Peter; Merlen, Alain

2005-12-01

The effect of parametric wave phase conjugation (WPC) in application to ultrasound or acoustic waves in magnetostrictive solids has been addressed numerically by Ben Khelil et al. [J. Acoust. Soc. Am. 109, 75-83 (2001)] using 1-D unsteady formulation. Here the numerical method presented by Voinovich et al. [Shock waves 13(3), 221-230 (2003)] extends the analysis to the 2-D effects. The employed model describes universally elastic solids and liquids. A source term similar to Ben Khelil et al.'s accounts for the coupling between deformation and magnetostriction due to external periodic magnetic field. The compatibility between the isotropic constitutive law of the medium and the model of magnetostriction has been considered. Supplementary to the 1-D simulations, the present model involves longitudinal/transversal mode conversion at the sample boundaries and separate magnetic field coupling with dilatation and shear stress. The influence of those factors in a 2-D geometry on the potential output of a magneto-elastic wave phase conjugator is analyzed in this paper. The process under study includes propagation of a wave burst of a given frequency from a point source in a liquid into the active solid, amplification of the waves due to parametric resonance, and formation of time-reversed waves, their radiation into liquid, and focusing. The considered subject is particularly important for ultrasonic applications in acoustic imaging, nondestructive testing, or medical diagnostics and therapy.

Two-dimensional numerical simulation of acoustic wave phase conjugation in magnetostrictive elastic media

NASA Astrophysics Data System (ADS)

Voinovich, Peter; Merlen, Alain

2005-12-01

The effect of parametric wave phase conjugation (WPC) in application to ultrasound or acoustic waves in magnetostrictive solids has been addressed numerically by Ben Khelil et al. [J. Acoust. Soc. Am. 109, 75-83 (2001)] using 1-D unsteady formulation. Here the numerical method presented by Voinovich et al. [Shock waves 13(3), 221-230 (2003)] extends the analysis to the 2-D effects. The employed model describes universally elastic solids and liquids. A source term similar to Ben Khelil et al.'s accounts for the coupling between deformation and magnetostriction due to external periodic magnetic field. The compatibility between the isotropic constitutive law of the medium and the model of magnetostriction has been considered. Supplementary to the 1-D simulations, the present model involves longitudinal/transversal mode conversion at the sample boundaries and separate magnetic field coupling with dilatation and shear stress. The influence of those factors in a 2-D geometry on the potential output of a magneto-elastic wave phase conjugator is analyzed in this paper. The process under study includes propagation of a wave burst of a given frequency from a point source in a liquid into the active solid, amplification of the waves due to parametric resonance, and formation of time-reversed waves, their radiation into liquid, and focusing. The considered subject is particularly important for ultrasonic applications in acoustic imaging, nondestructive testing, or medical diagnostics and therapy.

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

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.

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

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.

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.

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.

Analytical approaches to image orientation and stereo digitization applied in the Budnlab software. (Polish Title: Rozwiazania analityczne zwiazane z obsluga procesu orientacji zdjec oraz wykonywaniem opracowan wektorowych w programie Bundlab)

NASA Astrophysics Data System (ADS)

Kolecki, J.

2015-12-01

The Bundlab software has been developed mainly for academic and research application. This work can be treated as a kind of a report describing the current state of the development of this computer program, focusing especially on the analytical solutions. Firstly, the overall characteristics of the software are provided. Then the description of the image orientation procedure starting from the relative orientation is addressed. The applied solution is based on the coplanarity equation parametrized with the essential matrix. The problem is reformulated in order to solve it using methods of algebraic geometry. The solution is followed by the optimization involving the least square criterion. The formation of the image block from the oriented models as well as the absolute orientation procedure were implemented using the Horn approach as a base algorithm. The second part of the paper is devoted to the tools and methods applied in the stereo digitization module. The solutions that support the user and improve the accuracy are given. Within the paper a few exemplary applications and products are mentioned. The work finishes with the concepts of development and improvements of existing functions.

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.

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.

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.

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.

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.

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

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

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.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Transmission of wave energy in curved ducts

NASA Technical Reports Server (NTRS)

Rostafinski, W.

1973-01-01

A formation of wave energy flow was developed for motion in curved ducts. A parametric study over a range of frequencies determined the ability of circular bends to transmit energy for the case of perfectly rigid walls.

A Nonparametric Approach for Assessing Goodness-of-Fit of IRT Models in a Mixed Format Test

ERIC Educational Resources Information Center

Liang, Tie; Wells, Craig S.

2015-01-01

Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…

[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.

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.

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.

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.

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.

On mass concentrations and magnitude gaps of galaxy systems in the CS82 survey

NASA Astrophysics Data System (ADS)

Vitorelli, André Z.; Cypriano, Eduardo S.; Makler, Martín; Pereira, Maria E. S.; Erben, Thomas; Moraes, Bruno

2018-02-01

Galaxy systems with large magnitude gaps - defined as the difference in magnitude between the central galaxy and the brightest satellite in the central region, such as fossil groups - are claimed to have earlier formation times. In this study, we measure the mass concentration, as an indicator of the formation epoch, of ensembles of galaxy systems divided by redshift and magnitude gaps in the r band. We use cross-correlation weak-lensing measurements with NFW parametric mass profiles to measure masses and concentrations of these ensembles from a catalogue of systems built from the SDSS Coadd by the redMaPPer algorithm. The lensing shear data come from the CFHT Stripe 82 (CS82) survey, and consists of i-band images of the SDSS Stripe 82 region. We find that the stack made up of systems with larger magnitude gaps has a high probability of being more concentrated, in the lowest redshift slice (0.2 < z < 0.4), both when dividing in quartiles (P = 0.98) and tertiles (P = 0.85). These results lend credibility to the claim that systems with large magnitude gaps tend to have been formed early.

Numerical study of Si nanoparticle formation by SiCl4 hydrogenation in RF plasma

NASA Astrophysics Data System (ADS)

Rehmet, Christophe; Cao, Tengfei; Cheng, Yi

2016-04-01

Nanocrystalline silicon (nc-Si) is a promising material for many applications related to electronics and optoelectronics. This work performs numerical simulations in order to understand a new process with high deposition rate production of nc-Si in a radio-frequency plasma reactor. Inductive plasma formation, reaction kinetics and nanoparticle formation have been considered in a sophisticated model. Results show that the plasma parameters could be adjusted in order to improve selectivity between nanoparticle and molecule formation and, thus, the deposition rate. Also, a parametric study helps to optimize the system with appropriate operating conditions.

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.

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

Parametric Characterization of TES Detectors Under DC Bias

NASA Technical Reports Server (NTRS)

Chiao, Meng P.; Smith, Stephen James; Kilbourne, Caroline A.; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chervenak, James A.; Datesman, Aaron M.; Eckart, Megan E.; Ewin, Audrey J.;

Rapid Parameterization Schemes for Aircraft Shape Optimization

NASA Technical Reports Server (NTRS)

Li, Wu

2012-01-01

A rapid shape parameterization tool called PROTEUS is developed for aircraft shape optimization. This tool can be applied directly to any aircraft geometry that has been defined in PLOT3D format, with the restriction that each aircraft component must be defined by only one data block. PROTEUS has eight types of parameterization schemes: planform, wing surface, twist, body surface, body scaling, body camber line, shifting/scaling, and linear morphing. These parametric schemes can be applied to two types of components: wing-type surfaces (e.g., wing, canard, horizontal tail, vertical tail, and pylon) and body-type surfaces (e.g., fuselage, pod, and nacelle). These schemes permit the easy setup of commonly used shape modification methods, and each customized parametric scheme can be applied to the same type of component for any configuration. This paper explains the mathematics for these parametric schemes and uses two supersonic configurations to demonstrate the application of these schemes.

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.

Natural Environment Characterization Using Hybrid Tomographic Aproaches

NASA Astrophysics Data System (ADS)

Huang, Yue; Ferro-Famil, Laurent; Reigber, Andreas

2011-03-01

SAR tomography (SARTOM) is the extension of conventional two-dimensional SAR imaging principle to three dimensions [1]. A real 3D imaging of a scene is achieved by the formation of an additional synthetic aperture in elevation and the coherent combination of images acquired from several parallel flight tracks. This imaging technique allows a direct localization of multiple scattering contributions in a same resolution cell, leading to a refined analysis of volume structures, like forests or dense urban areas. In order to improve the vertical resolution with respect to classical Fourier-based methods, High-Resolution (HR) approaches are used in this paper to perform SAR tomography. Both nonparametric spectral estimators, like Beamforming and Capon and parametric ones, like MUSIC, Maximum Likelihood, are applied to real data sets and compared in terms of scatterer location accuracy and resolution. It is known that nonparametric approaches are in general more robust to focusing artefacts, whereas parametric approaches are characterized by a better vertical resolution. It has been shown [2], [3] that the performance of these spectral analysis approaches is conditioned by the nature of the scattering response of the observed objects. In the scenario of hybrid environments where objects with a deterministic response are embedded in a speckle affected environment, the parameter estimation for this type of scatterers becomes a problem of mixed-spectrum estimation. The impenetrable medium like the ground or object, possesses an isolated localized phase center in the vertical direction, leading to a discrete (line) spectrum. This type of scatterers can be considered as 'h-localized', named 'Isolated Scatterers' (IS). Whereas natural environments consist of a large number of elementary scatterers successively distributed in the vertical direction. This type of scatterers can be described as 'h-distributed' scatterers and characterized by a continuous spectrum. Therefore, the usual spectral estimators may reach some limitations due to their lack of adaptation to both the statistical features of the backscattered information and the type of spectrum of the considered media. In order to overcome this problem, a tomographic focusing approach based on hybrid spectral estimators is introduced and extended to the polarimetric case. It contains two parallel procedures: one is to detect and localize isolated scatterers and the other one is to characterize the natural environment by estimating the heights of the ground and the tree top. These two decoupled procedures permit to more precisely characterize the scenario of hybrid environments.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

In our own image? Emotional and neural processing differences when observing human–human vs human–robot interactions

PubMed Central

Wang, Yin

2015-01-01

Notwithstanding the significant role that human–robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human–human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal–parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. PMID:25911418

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.

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.

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

The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart.

PubMed

Fonseca, Carissa G; Backhaus, Michael; Bluemke, David A; Britten, Randall D; Chung, Jae Do; Cowan, Brett R; Dinov, Ivo D; Finn, J Paul; Hunter, Peter J; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Medrano-Gracia, Pau; Shivkumar, Kalyanam; Suinesiaputra, Avan; Tao, Wenchao; Young, Alistair A

2011-08-15

Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt). http://www.cardiacatlas.org a.young@auckland.ac.nz Supplementary data are available at Bioinformatics online.

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

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.

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.

Parametric Instability Rates in Periodically Driven Band Systems

NASA Astrophysics Data System (ADS)

Lellouch, S.; Bukov, M.; Demler, E.; Goldman, N.

2017-04-01

In this work, we analyze the dynamical properties of periodically driven band models. Focusing on the case of Bose-Einstein condensates, and using a mean-field approach to treat interparticle collisions, we identify the origin of dynamical instabilities arising from the interplay between the external drive and interactions. We present a widely applicable generic numerical method to extract instability rates and link parametric instabilities to uncontrolled energy absorption at short times. Based on the existence of parametric resonances, we then develop an analytical approach within Bogoliubov theory, which quantitatively captures the instability rates of the system and provides an intuitive picture of the relevant physical processes, including an understanding of how transverse modes affect the formation of parametric instabilities. Importantly, our calculations demonstrate an agreement between the instability rates determined from numerical simulations and those predicted by theory. To determine the validity regime of the mean-field analysis, we compare the latter to the weakly coupled conserving approximation. The tools developed and the results obtained in this work are directly relevant to present-day ultracold-atom experiments based on shaken optical lattices and are expected to provide an insightful guidance in the quest for Floquet engineering.

Bim Automation: Advanced Modeling Generative Process for Complex Structures

NASA Astrophysics Data System (ADS)

Banfi, F.; Fai, S.; Brumana, R.

2017-08-01

The new paradigm of the complexity of modern and historic structures, which are characterised by complex forms, morphological and typological variables, is one of the greatest challenges for building information modelling (BIM). Generation of complex parametric models needs new scientific knowledge concerning new digital technologies. These elements are helpful to store a vast quantity of information during the life cycle of buildings (LCB). The latest developments of parametric applications do not provide advanced tools, resulting in time-consuming work for the generation of models. This paper presents a method capable of processing and creating complex parametric Building Information Models (BIM) with Non-Uniform to NURBS) with multiple levels of details (Mixed and ReverseLoD) based on accurate 3D photogrammetric and laser scanning surveys. Complex 3D elements are converted into parametric BIM software and finite element applications (BIM to FEA) using specific exchange formats and new modelling tools. The proposed approach has been applied to different case studies: the BIM of modern structure for the courtyard of West Block on Parliament Hill in Ottawa (Ontario) and the BIM of Masegra Castel in Sondrio (Italy), encouraging the dissemination and interaction of scientific results without losing information during the generative process.

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.

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.

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.

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

Mid-infrared hyperspectral imaging for the detection of explosive compounds

NASA Astrophysics Data System (ADS)

Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.

2012-10-01

Active hyperspectral imaging is a valuable tool in a wide range of applications. A developing market is the detection and identification of energetic compounds through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype mid-infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light over a range of wavelengths. While there are a number of illumination methods, this work illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and directed and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around a MWIR optical parametric oscillator (OPO) source with broad tunability, operating at 2.6 μm to 3.7 μm. Due to material handling procedures associated with explosive compounds, experimental work was undertaken initially using simulant compounds. A second set of compounds that was tested alongside the simulant compounds is a range of confusion compounds. By having the broad wavelength tunability of the OPO, extended absorption spectra of the compounds could be obtained to aid in compound identification. The prototype imager instrument has successfully been used to record the absorption spectra for a range of compounds from the simulant and confusion sets and current work is now investigating actual explosive compounds. The authors see a very promising outlook for the MWIR hyperspectral imager. From an applications point of view this format of imaging instrument could be used for a range of standoff, improvised explosive device (IED) detection applications and potential incident scene forensic investigation.

Petrophysical evaluation of the hydrocarbon potential of the Lower Cretaceous Kharita clastics, North Qarun oil field, Western Desert, Egypt

NASA Astrophysics Data System (ADS)

Teama, Mostafa A.; Nabawy, Bassem S.

2016-09-01

Based on the available well log data of six wells chosen in the North Qarun oil field in the Western Desert of Egypt, the petrophysical evaluation for the Lower Cretaceous Kharita Formation was accomplished. The lithology of Kharita Formation was analyzed using the neutron porosity-density and the neutron porosity-gamma ray crossplots as well as the litho-saturation plot. The petrophysical parameters, include shale volume, effective porosity, water saturation and hydrocarbon pore volume, were determined and traced laterally in the studied field through the iso-parametric maps. The lithology crossplots of the studied wells show that the sandstone is the main lithology of the Kharita Formation intercalated with some calcareous shale. The cutoff values of shale volume, porosity and water saturation for the productive hydrocarbon pay zones are defined to be 40%, 10% and 50%, respectively, which were determined, based on the applied crossplots approach and their limits. The iso-parametric contour maps for the average reservoir parameters; such as net-pay thickness, average porosity, shale volume, water saturation and the hydrocarbon pore volume were illustrated. From the present study, it is found that the Kharita Formation in the North Qarun oil field has promising reservoir characteristics, particularly in the northwestern part of the study area, which is considered as a prospective area for oil accumulation.

Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014

DTIC Science & Technology

2014-11-01

formation about the entity, every new document would drive an update to the entity profile, strongly suggesting vitalness. Figure 3 represents...of the Twenty-Second Text REtrieval Conference (TREC 2013), 2013. Caruana, Richard. Multitask Learning: A Knowledge-Based Source of Inductive Bias. In

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...

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.

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.

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.

Radiation damage free ghost diffraction with atomic resolution

DOE PAGES

Li, Zheng; Medvedev, Nikita; Chapman, Henry N.; ...

2017-12-21

The x-ray free electron lasers can enable diffractive structural determination of protein nanocrystals and single molecules that are too small and radiation-sensitive for conventional x-ray diffraction. However the electronic form factor may be modified during the ultrashort x-ray pulse due to photoionization and electron cascade caused by the intense x-ray pulse. For general x-ray imaging techniques, the minimization of the effects of radiation damage is of major concern to ensure reliable reconstruction of molecular structure. Here in this paper, we show that radiation damage free diffraction can be achieved with atomic spatial resolution by using x-ray parametric down-conversion and ghostmore » diffraction with entangled photons of x-ray and optical frequencies. We show that the formation of the diffraction patterns satisfies a condition analogous to the Bragg equation, with a resolution that can be as fine as the crystal lattice length scale of several Ångstrom. Since the samples are illuminated by low energy optical photons, they can be free of radiation damage.« less

Radiation damage free ghost diffraction with atomic resolution

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

Li, Zheng; Medvedev, Nikita; Chapman, Henry N.

The x-ray free electron lasers can enable diffractive structural determination of protein nanocrystals and single molecules that are too small and radiation-sensitive for conventional x-ray diffraction. However the electronic form factor may be modified during the ultrashort x-ray pulse due to photoionization and electron cascade caused by the intense x-ray pulse. For general x-ray imaging techniques, the minimization of the effects of radiation damage is of major concern to ensure reliable reconstruction of molecular structure. Here in this paper, we show that radiation damage free diffraction can be achieved with atomic spatial resolution by using x-ray parametric down-conversion and ghostmore » diffraction with entangled photons of x-ray and optical frequencies. We show that the formation of the diffraction patterns satisfies a condition analogous to the Bragg equation, with a resolution that can be as fine as the crystal lattice length scale of several Ångstrom. Since the samples are illuminated by low energy optical photons, they can be free of radiation damage.« less

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.

Transplanted human glial-restricted progenitors can rescue the survival of dysmyelinated mice independent of the production of mature, compact myelin.

PubMed

Lyczek, Agatha; Arnold, Antje; Zhang, Jiangyang; Campanelli, James T; Janowski, Miroslaw; Bulte, Jeff W M; Walczak, Piotr

2017-05-01

The therapeutic effect of glial progenitor transplantation in diseases of dysmyelination is currently attributed to the formation of new myelin. Using magnetic resonance imaging (MRI), we show that the therapeutic outcome in dysmyelinated shiverer mice is dependent on the extent of cell migration but not the presence of mature and compact myelin. Human or mouse glial restricted progenitors (GRPs) were transplanted into rag2 -/ - shiverer mouse neonates and followed for over one year. Mouse GRPs produced mature myelin as detected with multi-parametric MRI, but showed limited migration without extended animal lifespan. In sharp contrast, human GRPs migrated extensively and significantly increased animal survival, but production of mature myelin did not occur until 46weeks post-grafting. We conclude that human GRPs can extend the survival of transplanted shiverer mice prior to production of mature myelin, while mouse GRPs fail to extend animal survival despite the early presence of mature myelin. This paradox suggests that transplanted GRPs provide therapeutic benefits through biological processes other than the formation of mature myelin capable to foster rapid nerve conduction, challenging the current dogma of the primary role of myelination in regaining function of the central nervous system. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

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

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.

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

NASA Astrophysics Data System (ADS)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

The ATLAS3D Project - XXX. Star formation histories and stellar population scaling relations of early-type galaxies

NASA Astrophysics Data System (ADS)

McDermid, Richard M.; Alatalo, Katherine; Blitz, Leo; Bournaud, Frédéric; Bureau, Martin; Cappellari, Michele; Crocker, Alison F.; Davies, Roger L.; Davis, Timothy A.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Krajnović, Davor; Kuntschner, Harald; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Sarzi, Marc; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.

2015-04-01

We present the stellar population content of early-type galaxies from the ATLAS3D survey. Using spectra integrated within apertures covering up to one effective radius, we apply two methods: one based on measuring line-strength indices and applying single stellar population (SSP) models to derive SSP-equivalent values of stellar age, metallicity, and alpha enhancement; and one based on spectral fitting to derive non-parametric star formation histories, mass-weighted average values of age, metallicity, and half-mass formation time-scales. Using homogeneously derived effective radii and dynamically determined galaxy masses, we present the distribution of stellar population parameters on the Mass Plane (MJAM, σe, R^maj_e), showing that at fixed mass, compact early-type galaxies are on average older, more metal-rich, and more alpha-enhanced than their larger counterparts. From non-parametric star formation histories, we find that the duration of star formation is systematically more extended in lower mass objects. Assuming that our sample represents most of the stellar content of today's local Universe, approximately 50 per cent of all stars formed within the first 2 Gyr following the big bang. Most of these stars reside today in the most massive galaxies (>1010.5 M⊙), which themselves formed 90 per cent of their stars by z ˜ 2. The lower mass objects, in contrast, have formed barely half their stars in this time interval. Stellar population properties are independent of environment over two orders of magnitude in local density, varying only with galaxy mass. In the highest density regions of our volume (dominated by the Virgo cluster), galaxies are older, alpha-enhanced, and have shorter star formation histories with respect to lower density regions.

A review of recent developments in parametric based acoustic emission techniques applied to concrete structures

NASA Astrophysics Data System (ADS)

Vidya Sagar, R.; Raghu Prasad, B. K.

2012-03-01

This article presents a review of recent developments in parametric based acoustic emission (AE) techniques applied to concrete structures. It recapitulates the significant milestones achieved by previous researchers including various methods and models developed in AE testing of concrete structures. The aim is to provide an overview of the specific features of parametric based AE techniques of concrete structures carried out over the years. Emphasis is given to traditional parameter-based AE techniques applied to concrete structures. A significant amount of research on AE techniques applied to concrete structures has already been published and considerable attention has been given to those publications. Some recent studies such as AE energy analysis and b-value analysis used to assess damage of concrete bridge beams have also been discussed. The formation of fracture process zone and the AE energy released during the fracture process in concrete beam specimens have been summarised. A large body of experimental data on AE characteristics of concrete has accumulated over the last three decades. This review of parametric based AE techniques applied to concrete structures may be helpful to the concerned researchers and engineers to better understand the failure mechanism of concrete and evolve more useful methods and approaches for diagnostic inspection of structural elements and failure prediction/prevention of concrete structures.

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.

Parametric Study of Amorphous High-Entropy Alloys formation from two New Perspectives: Atomic Radius Modification and Crystalline Structure of Alloying Elements

NASA Astrophysics Data System (ADS)

Hu, Q.; Guo, S.; Wang, J. M.; Yan, Y. H.; Chen, S. S.; Lu, D. P.; Liu, K. M.; Zou, J. Z.; Zeng, X. R.

2017-01-01

Chemical and topological parameters have been widely used for predicting the phase selection in high-entropy alloys (HEAs). Nevertheless, previous studies could be faulted due to the small number of available data points, the negligence of kinetic effects, and the insensitivity to small compositional changes. Here in this work, 92 TiZrHfM, TiZrHfMM, TiZrHfMMM (M = Fe, Cr, V, Nb, Al, Ag, Cu, Ni) HEAs were prepared by melt spinning, to build a reliable and sufficiently large material database to inspect the robustness of previously established parameters. Modification of atomic radii by considering the change of local electronic environment in alloys, was critically found out to be superior in distinguishing the formation of amorphous and crystalline alloys, when compared to using atomic radii of pure elements in topological parameters. Moreover, crystal structures of alloying element were found to play an important role in the amorphous phase formation, which was then attributed to how alloying hexagonal-close-packed elements and face-centered-cubic or body-centered-cubic elements can affect the mixing enthalpy. Findings from this work not only provide parametric studies for HEAs with new and important perspectives, but also reveal possibly a hidden connection among some important concepts in various fields.

Hybrid modeling as a QbD/PAT tool in process development: an industrial E. coli case study.

PubMed

von Stosch, Moritz; Hamelink, Jan-Martijn; Oliveira, Rui

2016-05-01

Process understanding is emphasized in the process analytical technology initiative and the quality by design paradigm to be essential for manufacturing of biopharmaceutical products with consistent high quality. A typical approach to developing a process understanding is applying a combination of design of experiments with statistical data analysis. Hybrid semi-parametric modeling is investigated as an alternative method to pure statistical data analysis. The hybrid model framework provides flexibility to select model complexity based on available data and knowledge. Here, a parametric dynamic bioreactor model is integrated with a nonparametric artificial neural network that describes biomass and product formation rates as function of varied fed-batch fermentation conditions for high cell density heterologous protein production with E. coli. Our model can accurately describe biomass growth and product formation across variations in induction temperature, pH and feed rates. The model indicates that while product expression rate is a function of early induction phase conditions, it is negatively impacted as productivity increases. This could correspond with physiological changes due to cytoplasmic product accumulation. Due to the dynamic nature of the model, rational process timing decisions can be made and the impact of temporal variations in process parameters on product formation and process performance can be assessed, which is central for process understanding.

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.

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.)

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.

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.

Star clusters in the Magellanic Clouds - I. Parametrization and classification of 1072 clusters in the LMC

NASA Astrophysics Data System (ADS)

Nayak, P. K.; Subramaniam, A.; Choudhury, S.; Indu, G.; Sagar, Ram

2016-12-01

We have introduced a semi-automated quantitative method to estimate the age and reddening of 1072 star clusters in the Large Magellanic Cloud (LMC) using the Optical Gravitational Lensing Experiment III survey data. This study brings out 308 newly parametrized clusters. In a first of its kind, the LMC clusters are classified into groups based on richness/mass as very poor, poor, moderate and rich clusters, similar to the classification scheme of open clusters in the Galaxy. A major cluster formation episode is found to happen at 125 ± 25 Myr in the inner LMC. The bar region of the LMC appears prominently in the age range 60-250 Myr and is found to have a relatively higher concentration of poor and moderate clusters. The eastern and the western ends of the bar are found to form clusters initially, which later propagates to the central part. We demonstrate that there is a significant difference in the distribution of clusters as a function of mass, using a movie based on the propagation (in space and time) of cluster formation in various groups. The importance of including the low-mass clusters in the cluster formation history is demonstrated. The catalogue with parameters, classification, and cleaned and isochrone fitted colour-magnitude diagrams of 1072 clusters, which are available as online material, can be further used to understand the hierarchical formation of clusters in selected regions of the LMC.

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-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.

Classification of the visual landscape for transmission planning

Treesearch

Curtis Miller; Nargis Jetha; Rod MacDonald

1979-01-01

The Visual Landscape Type Classification method of the Route and Site Selection Division, Ontario Hydro, defines and delineates the landscape into discrete visual units using parametric and judgmental data. This qualitative and quantitative information is documented in a prescribed format to give each of the approximately 1100 Landscape Types a unique description....

The Effect of Sample Size on Parametric and Nonparametric Factor Analytical Methods

ERIC Educational Resources Information Center

Kalkan, Ömür Kaya; Kelecioglu, Hülya

2016-01-01

Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…

Modeling and Simulation of Plasma-Assisted Ignition and Combustion

DTIC Science & Technology

2013-10-01

local plasma chemistry effects over heat transport in achieving “volumetric” ignition using pulse nanosecond discharges. •detailed parametric studies...electrical breakdown • cathode sheath formation • electron impact dynamics PLASMA DISCHARGE DYNAMICS Plasma Chemistry Ionization, Excitation...quenching of excited species nonequilibrium plasma chemistry low temperature radical chemistry high temperature combustion chemistry School of

Distributed parametric amplifier for RZ-DPSK signal transmission system.

PubMed

Xu, Xing; Zhang, Chi; Yuk, T I; Wong, Kenneth K Y

2012-08-13

We have experimentally demonstrated a single pump distributed parametric amplification (DPA) system for differential phase shift keying (DPSK) signal in a spool of dispersion-shifted fiber (DSF). The gain spectrum of single pump DPA is thoroughly investigated by both simulation and experiment, and a possible reference for optimal input pump power and fiber length relationship is provided to DPA based applications. Furthermore, DPSK format is compared with on-off keying (OOK) within DPA scheme. Eight WDM signal channels at 10-Gb/s are utilized, and approximately 0.5-dB power penalties at the bit-error rate (BER) of 10(-9) are achieved for return-to-zero DPSK (RZ-DPSK), comparing to larger than 1.5-dB with OOK format. In order to improve the system power efficiency, at the receiver, the pump is recycled by a photovoltaic cell and the converted energy can be used by potential low-power-consuming devices, i.e sensors or small-scale electronic circuits. Additionally, with suitable components, the whole DPA concept could be directly applied to the 1.3-μm telecommunication window along the most commonly used single-mode fiber (SMF).

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.

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

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

Correlation between Surface Tension and Water Activity in New Particle Formation

NASA Astrophysics Data System (ADS)

Daskalakis, E.; Salameh, A.

2016-12-01

The impact of aerosol properties on cloud dynamics and the radiative balance of the atmosphere relies on the parametrizations of cloud droplet formation. Such parametrization is based on equilibrium thermodynamics proposed by Köhler in 1936. There is considerable debate in the literature on the importance of factors like the surface tension depression or the water activity decrease for the correct parametrization. To gain fundamental insight into New Particle Formation (NPF), or Cloud Condensation Nuclei (CCN) activation one has to study microscopic properties of aqueous droplets, involving surface and bulk dynamics. The surface tension of droplets can be associated with the effects from Organic Matter (OM), whereas the static dielectric constant of water reflects the structure and dynamics of ions within solutions and can present a measure of water activity. In this study we employ Molecular Dynamics Simulations on aquatic droplets that contain surface active OM (acetaldehyde, methylglyoxal) and salts. We give insight into the dynamics of aquatic droplets with radials of 3.6nm at a level of detail that is not accessible experimentally (J. Phys. Chem. C 2016, 120:11508). We propose that as the surface tension of an aquatic droplet is decreased in the presence of surface-active OM, the water activity is affected as well. This is due to the fact that the water dipoles are oriented based on the salt morphology within the droplet. We suggest that the surface tension depression can be accompanied by the water activity change. This can be associated with the possible effects of surface-active species in terms of salt morphology transitions within an aerosol at the NPF and early particle growth time scales. Based on this study, surface-active OM seems important in controlling (a) the salt morphology transitions within a nucleus during NPF and particle growth and (b) a correlation between surface activity and water activity of ionic aquatic droplets. The latter correlation could be a fundamental property to consider when assessing NPF and the Köhler theory.

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.

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.

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.

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.

Theory of parametrically amplified electron-phonon superconductivity

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

Babadi, Mehrtash; Knap, Michael; Martin, Ivar

2017-07-01

Ultrafast optical manipulation of ordered phases in strongly correlated materials is a topic of significant theoretical, experimental, and technological interest. Inspired by a recent experiment on light-induced superconductivity in fullerenes [M. Mitrano et al., Nature (London) 530, 461 (2016)], we develop a comprehensive theory of light-induced superconductivity in driven electron-phonon systemswith lattice nonlinearities. In analogy with the operation of parametric amplifiers, we show how the interplay between the external drive and lattice nonlinearities lead to significantly enhanced effective electron-phonon couplings. We provide a detailed and unbiased study of the nonequilibrium dynamics of the driven system using the real-time Green's functionmore » technique. To this end, we develop a Floquet generalization of the Migdal-Eliashberg theory and derive a numerically tractable set of quantum Floquet-Boltzmann kinetic equations for the coupled electron-phonon system. We study the role of parametric phonon generation and electronic heating in destroying the transient superconducting state. Finally, we predict the transient formation of electronic Floquet bands in time-and angle-resolved photoemission spectroscopy experiments as a consequence of the proposed mechanism.« less

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.

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.

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.

Preferred orientation in Cr- and Co-based thin films and its effects on the read/write performance of the media

NASA Astrophysics Data System (ADS)

Tsai, Hsiao-chu; Lal, Brij B.; Eltoukhy, Atef

1992-04-01

This work investigates the formation of preferred crystallographic orientation (PO) in Cr underlayer as well as CoCrTa and CoCrPtTa thin films and its effects on the recording performance of longitudinal media. The results show that the thin-film media with comparable coercivity but different crystalline PO as measured by x-ray diffraction exhibit significant difference in high-frequency signal amplitude, pulse width, and signal-to-noise ratio. To illustrate the effect of PO on parametric performance, CoCrTa/Cr and CoCrPtTa/Cr media were sputtered on different substrates and/or using special sputtering processes to achieve comparable coercivity but different PO in the films. A PO of Cr(200), which normally occurs on the NiP/Al substrates under adequate sputtering conditions, is found to be the key to obtaining a PO of Co(11.0) in Co-alloy media. The consequence of preferred in-plane c-axis orientation is a higher coercivity and better parametric performance of the medium. The formation of PO in the Cr underlayer is found to be related to the substrate material and the oxygen content in the sputtered films. The nonmetallic canasite substrates tend to promote PO of more stable Cr(110) rather than Cr(200). Consequently, this leads to a PO of out-of-plane c axis on the following Co films. The PO of magnetic layer appears to be an important factor in determining the parametric performance of the media.

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

VizieR Online Data Catalog: ATLAS3D Project. XXX (McDermid+, 2015)

NASA Astrophysics Data System (ADS)

McDermid, R. M.; Alatalo, K.; Blitz, L.; Bournaud, F.; Bureau, M.; Cappellari, M.; Crocker, A. F.; Davies, R. L.; Davis, T. A.; De Zeeuw, P. T.; Duc, P.-A.; Emsellem, E.; Khochfar, S.; Krajnovic, D.; Kuntschner, H.; Morganti, R.; Naab, T.; Oosterloo, T.; Sarzi, M.; Scott, N.; Serra, P.; Weijmans, A.-M.; Young, L. M.

2015-09-01

We present the stellar population content of early-type galaxies from the ATLAS3D survey. Using spectra integrated within apertures covering up to one effective radius, we apply two methods: one based on measuring line-strength indices and applying single stellar population (SSP) models to derive SSP-equivalent values of stellar age, metallicity, and alpha enhancement; and one based on spectral fitting to derive non-parametric star formation histories, mass-weighted average values of age, metallicity, and half-mass formation time-scales. Using homogeneously derived effective radii and dynamically determined galaxy masses, we present the distribution of stellar population parameters on the Mass Plane (MJAM, σe, Rmaje), showing that at fixed mass, compact early-type galaxies are on average older, more metal-rich, and more alpha-enhanced than their larger counterparts. From non-parametric star formation histories, we find that the duration of star formation is systematically more extended in lower mass objects. Assuming that our sample represents most of the stellar content of today's local Universe, approximately 50 percent of all stars formed within the first 2Gyr following the big bang. Most of these stars reside today in the most massive galaxies (>1010.5M⊙), which themselves formed 90 percent of their stars by z~2. The lower mass objects, in contrast, have formed barely half their stars in this time interval. Stellar population properties are independent of environment over two orders of magnitude in local density, varying only with galaxy mass. In the highest density regions of our volume (dominated by the Virgo cluster), galaxies are older, alpha-enhanced, and have shorter star formation histories with respect to lower density regions. (4 data files).

Advanced Forensic Format: an Open Extensible Format for Disk Imaging

NASA Astrophysics Data System (ADS)

Garfinkel, Simson; Malan, David; Dubec, Karl-Alexander; Stevens, Christopher; Pham, Cecile

This paper describes the Advanced Forensic Format (AFF), which is designed as an alternative to current proprietary disk image formats. AFF offers two significant benefits. First, it is more flexible because it allows extensive metadata to be stored with images. Second, AFF images consume less disk space than images in other formats (e.g., EnCase images). This paper also describes the Advanced Disk Imager, a new program for acquiring disk images that compares favorably with existing alternatives.

On the Nature of Syntactic Variation: Evidence from Complex Predicates and Complex Word-Formation.

ERIC Educational Resources Information Center

Snyder, William

2001-01-01

Provides evidence from child language acquisition and comparative syntax for existence of a syntactic parameter in the classical sense of Chomsky (1981), with simultaneous effects on syntactic argument structure. Implications are that syntax is subject to points of substantive parametric variation as envisioned in Chomsky, and the time course of…

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

Phenotypic Characterization of Toxic Compound Effects on Liver Spheroids Derived from iPSC Using Confocal Imaging and Three-Dimensional Image Analysis.

PubMed

Sirenko, Oksana; Hancock, Michael K; Hesley, Jayne; Hong, Dihui; Cohen, Avrum; Gentry, Jason; Carlson, Coby B; Mann, David A

2016-09-01

Cell models are becoming more complex to better mimic the in vivo environment and provide greater predictivity for compound efficacy and toxicity. There is an increasing interest in exploring the use of three-dimensional (3D) spheroids for modeling developmental and tissue biology with the goal of accelerating translational research in these areas. Accordingly, the development of high-throughput quantitative assays using 3D cultures is an active area of investigation. In this study, we have developed and optimized methods for the formation of 3D liver spheroids derived from human iPS cells and used those for toxicity assessment. We used confocal imaging and 3D image analysis to characterize cellular information from a 3D matrix to enable a multi-parametric comparison of different spheroid phenotypes. The assay enables characterization of compound toxicities by spheroid size (volume) and shape, cell number and spatial distribution, nuclear characterization, number and distribution of cells expressing viability, apoptosis, mitochondrial potential, and viability marker intensities. In addition, changes in the content of live, dead, and apoptotic cells as a consequence of compound exposure were characterized. We tested 48 compounds and compared induced pluripotent stem cell (iPSC)-derived hepatocytes and HepG2 cells in both two-dimensional (2D) and 3D cultures. We observed significant differences in the pharmacological effects of compounds across the two cell types and between the different culture conditions. Our results indicate that a phenotypic assay using 3D model systems formed with human iPSC-derived hepatocytes is suitable for high-throughput screening and can be used for hepatotoxicity assessment in vitro.

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.

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.

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

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.

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.

SDSS-IV MaNGA: constraints on the conditions for star formation in galaxy discs

NASA Astrophysics Data System (ADS)

Stark, David V.; Bundy, Kevin A.; Orr, Matthew E.; Hopkins, Philip F.; Westfall, Kyle; Bershady, Matthew; Li, Cheng; Bizyaev, Dmitry; Masters, Karen L.; Weijmans, Anne-Marie; Lacerna, Ivan; Thomas, Daniel; Drory, Niv; Yan, Renbin; Zhang, Kai

2018-02-01

Regions of disc galaxies with widespread star formation tend to be both gravitationally unstable and self-shielded against ionizing radiation, whereas extended outer discs with little or no star formation tend to be stable and unshielded on average. We explore what drives the transition between these two regimes, specifically whether discs first meet the conditions for self-shielding (parametrized by dust optical depth, τ) or gravitational instability (parametrized by a modified version of Toomre's instability parameters, Qthermal, which quantifies the stability of a gas disc that is thermally supported at T = 104 K). We first introduce a new metric formed by the product of these quantities, Qthermalτ, which indicates whether the conditions for disc instability or self-shielding are easier to meet in a given region of a galaxy, and we discuss how Qthermalτ can be constrained even in the absence of direct gas information. We then analyse a sample of 13 galaxies with resolved gas measurements and find that on average galaxies will reach the threshold for disc instabilities (Qthermal < 1) before reaching the threshold for self-shielding (τ > 1). Using integral field spectroscopic observations of a sample of 236 galaxies from the Mapping Nearby Galaxies at APO (MaNGA) survey, we find that the value of Qthermalτ in star-forming discs is consistent with similar behaviour. These results support a scenario where disc fragmentation and collapse occurs before self-shielding, suggesting that gravitational instabilities are the primary condition for widespread star formation in galaxy discs. Our results support similar conclusions based on recent galaxy simulations.

Development of a ReaxFF reactive force field for ammonium nitrate and application to shock compression and thermal decomposition.

PubMed

Shan, Tzu-Ray; van Duin, Adri C T; Thompson, Aidan P

2014-02-27

We have developed a new ReaxFF reactive force field parametrization for ammonium nitrate. Starting with an existing nitramine/TATB ReaxFF parametrization, we optimized it to reproduce electronic structure calculations for dissociation barriers, heats of formation, and crystal structure properties of ammonium nitrate phases. We have used it to predict the isothermal pressure-volume curve and the unreacted principal Hugoniot states. The predicted isothermal pressure-volume curve for phase IV solid ammonium nitrate agreed with electronic structure calculations and experimental data within 10% error for the considered range of compression. The predicted unreacted principal Hugoniot states were approximately 17% stiffer than experimental measurements. We then simulated thermal decomposition during heating to 2500 K. Thermal decomposition pathways agreed with experimental findings.

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

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.

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.

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.

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.

Imaging first impressions: distinct neural processing of verbal and nonverbal social information.

PubMed

Kuzmanovic, Bojana; Bente, Gary; von Cramon, D Yves; Schilbach, Leonhard; Tittgemeyer, Marc; Vogeley, Kai

2012-03-01

First impressions profoundly influence our attitudes and behavior toward others. However, little is known about whether and to what degree the cognitive processes that underlie impression formation depend on the domain of the available information about the target person. To investigate the neural bases of the influence of verbal as compared to nonverbal information on interpersonal judgments, we identified brain regions where the BOLD signal parametrically increased with increasing strength of evaluation based on either short text vignettes or mimic and gestural behavior. While for verbal stimuli the increasing strength of subjective evaluation was correlated with increased neural activation of precuneus and posterior cingulate cortex (PC/PCC), a similar effect was observed for nonverbal stimuli in the amygdala. These findings support the assumption that qualitatively different cognitive operations underlie person evaluation depending upon the stimulus domain: while the processing of nonverbal person information may be more strongly associated with affective processing as indexed by recruitment of the amygdala, verbal person information engaged the PC/PCC that has been related to social inferential processing. Copyright © 2011 Elsevier Inc. All rights reserved.

Brain perfusion alterations in tick-borne encephalitis-preliminary report.

PubMed

Tyrakowska-Dadełło, Zuzanna; Tarasów, Eugeniusz; Janusek, Dariusz; Moniuszko-Malinowska, Anna; Zajkowska, Joanna; Pancewicz, Sławomir

2018-03-01

Magnetic resonance imaging (MRI) changes in tick-borne encephalitis (TBE) are non-specific and the pathophysiological mechanisms leading to their formation remain unclear. This study investigated brain perfusion in TBE patients using dynamic susceptibility-weighted contrast-enhanced magnetic resonance perfusion imaging (DSC-MRI perfusion). MRI scans were performed for 12 patients in the acute phase, 3-5days after the diagnosis of TBE. Conventional MRI and DSC-MRI perfusion studies were performed. Cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP) parametric maps were created. The bilateral frontal, parietal, and temporal subcortical regions and thalamus were selected as regions of interest. Perfusion parameters of TBE patients were compared to those of a control group. There was a slight increase in CBF and CBV, with significant prolongation of TTP in subcortical areas in the study subjects, while MTT values were comparable to those of the control group. A significant increase in thalamic CBF (p<0.001) and increased CBV (p<0.05) were observed. Increased TTP and a slight reduction in MTT were also observed within this area. The DSC-MRI perfusion study showed that TBE patients had brain perfusion disturbances, expressed mainly in the thalami. These results suggest that DSC-MRI perfusion may provide important information regarding the areas affected in TBE patients. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Bayesian analysis of redshifted 21-cm H I signal and foregrounds: simulations for LOFAR

NASA Astrophysics Data System (ADS)

Ghosh, Abhik; Koopmans, Léon V. E.; Chapman, E.; Jelić, V.

2015-09-01

Observations of the epoch of reionization (EoR) using the 21-cm hyperfine emission of neutral hydrogen (H I) promise to open an entirely new window on the formation of the first stars, galaxies and accreting black holes. In order to characterize the weak 21-cm signal, we need to develop imaging techniques that can reconstruct the extended emission very precisely. Here, we present an inversion technique for LOw Frequency ARray (LOFAR) baselines at the North Celestial Pole (NCP), based on a Bayesian formalism with optimal spatial regularization, which is used to reconstruct the diffuse foreground map directly from the simulated visibility data. We notice that the spatial regularization de-noises the images to a large extent, allowing one to recover the 21-cm power spectrum over a considerable k⊥-k∥ space in the range 0.03 Mpc-1 < k⊥ < 0.19 Mpc-1 and 0.14 Mpc-1 < k∥ < 0.35 Mpc-1 without subtracting the noise power spectrum. We find that, in combination with using generalized morphological component analysis (GMCA), a non-parametric foreground removal technique, we can mostly recover the spherical average power spectrum within 2σ statistical fluctuations for an input Gaussian random root-mean-square noise level of 60 mK in the maps after 600 h of integration over a 10-MHz bandwidth.

The Ruinous Influence of Close Binary Companions on Planetary Systems

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Ireland, Michael; Mann, Andrew; Huber, Daniel; Dupuy, Trent J.

2017-01-01

The majority of solar-type stars are found in binary systems, and the dynamical influence of binary companions is expected to profoundly influence planetary systems. However, the difficulty of identifying planets in binary systems has left the magnitude of this effect uncertain; despite numerous theoretical hurdles to their formation and survival, at least some binary systems clearly host planets. We present high-resolution imaging of nearly 500 Kepler Objects of Interest (KOIs) obtained using adaptive-optics imaging and nonredundant aperture-mask interferometry on the Keck II telescope. We super-resolve some binary systems to projected separations of under 5 AU, showing that planets might form in these dynamically active environments. However, the full distribution of projected separations for our planet-host sample more broadly reveals a deep paucity of binary companions at solar-system scales. When the binary population is parametrized with a semimajor axis cutoff a cut and a suppression factor inside that cutoff S bin, we find with correlated uncertainties that inside acut = 47 +59/-23 AU, the planet occurrence rate in binary systems is only Sbin = 0.34 +0.14/-0.15 times that of wider binaries or single stars. Our results demonstrate that a fifth of all solar-type stars in the Milky Way are disallowed from hosting planetary systems due to the influence of a binary companion.

The Ruinous Influence of Close Binary Companions on Planetary Systems

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Ireland, Michael; Mann, Andrew; Huber, Daniel; Dupuy, Trent J.

2017-06-01

The majority of solar-type stars are found in binary systems, and the dynamical influence of binary companions is expected to profoundly influence planetary systems. However, the difficulty of identifying planets in binary systems has left the magnitude of this effect uncertain; despite numerous theoretical hurdles to their formation and survival, at least some binary systems clearly host planets. We present high-resolution imaging of nearly 500 Kepler Objects of Interest (KOIs) obtained using adaptive-optics imaging and nonredundant aperture-mask interferometry on the Keck II telescope. We super-resolve some binary systems to projected separations of under 5 AU, showing that planets might form in these dynamically active environments. However, the full distribution of projected separations for our planet-host sample more broadly reveals a deep paucity of binary companions at solar-system scales. When the binary population is parametrized with a semimajor axis cutoff a cut and a suppression factor inside that cutoff S bin, we find with correlated uncertainties that inside acut = 47 +59/-23 AU, the planet occurrence rate in binary systems is only Sbin = 0.34+0.14/-0.15 times that of wider binaries or single stars. Our results demonstrate that a fifth of all solar-type stars in the Milky Way are disallowed from hosting planetary systems due to the influence of a binary companion.

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.

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.

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.

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.

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.

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.

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.

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.

Java Library for Input and Output of Image Data and Metadata

NASA Technical Reports Server (NTRS)

Deen, Robert; Levoe, Steven

2003-01-01

A Java-language library supports input and output (I/O) of image data and metadata (label data) in the format of the Video Image Communication and Retrieval (VICAR) image-processing software and in several similar formats, including a subset of the Planetary Data System (PDS) image file format. The library does the following: It provides low-level, direct access layer, enabling an application subprogram to read and write specific image files, lines, or pixels, and manipulate metadata directly. Two coding/decoding subprograms ("codecs" for short) based on the Java Advanced Imaging (JAI) software provide access to VICAR and PDS images in a file-format-independent manner. The VICAR and PDS codecs enable any program that conforms to the specification of the JAI codec to use VICAR or PDS images automatically, without specific knowledge of the VICAR or PDS format. The library also includes Image I/O plugin subprograms for VICAR and PDS formats. Application programs that conform to the Image I/O specification of Java version 1.4 can utilize any image format for which such a plug-in subprogram exists, without specific knowledge of the format itself. Like the aforementioned codecs, the VICAR and PDS Image I/O plug-in subprograms support reading and writing of metadata.

EBR-II and TREAT Digitization Project

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

Griffith, George W.; Rabiti, Cristian

2015-09-01

Digitizing the technical drawings for EBR-II and TREAT provides multiple benefits. Moving the scanned or hard copy drawings to modern 3-D CAD (Computer Aided Drawing) format saves data that could be lost over time. The 3-D drawings produce models that can interface with other drawings to make complex assemblies. The 3-D CAD format can also include detailed material properties and parametric coding that can tie critical dimensions together allowing easier modification. Creating the new files from the old drawings has found multiple inconsistencies that are being flagged or corrected improving understanding of the reactor(s).

[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.

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

SCIFIO: an extensible framework to support scientific image formats.

PubMed

Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

2016-12-07

No gold standard exists in the world of scientific image acquisition; a proliferation of instruments each with its own proprietary data format has made out-of-the-box sharing of that data nearly impossible. In the field of light microscopy, the Bio-Formats library was designed to translate such proprietary data formats to a common, open-source schema, enabling sharing and reproduction of scientific results. While Bio-Formats has proved successful for microscopy images, the greater scientific community was lacking a domain-independent framework for format translation. SCIFIO (SCientific Image Format Input and Output) is presented as a freely available, open-source library unifying the mechanisms of reading and writing image data. The core of SCIFIO is its modular definition of formats, the design of which clearly outlines the components of image I/O to encourage extensibility, facilitated by the dynamic discovery of the SciJava plugin framework. SCIFIO is structured to support coexistence of multiple domain-specific open exchange formats, such as Bio-Formats' OME-TIFF, within a unified environment. SCIFIO is a freely available software library developed to standardize the process of reading and writing scientific image formats.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

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.

Refinement of the Cornell et al. Nucleic Acids Force Field Based on Reference Quantum Chemical Calculations of Glycosidic Torsion Profiles

PubMed Central

2011-01-01

We report a reparameterization of the glycosidic torsion χ of the Cornell et al. AMBER force field for RNA, χOL. The parameters remove destabilization of the anti region found in the ff99 force field and thus prevent formation of spurious ladder-like structural distortions in RNA simulations. They also improve the description of the syn region and the syn–anti balance as well as enhance MD simulations of various RNA structures. Although χOL can be combined with both ff99 and ff99bsc0, we recommend the latter. We do not recommend using χOL for B-DNA because it does not improve upon ff99bsc0 for canonical structures. However, it might be useful in simulations of DNA molecules containing syn nucleotides. Our parametrization is based on high-level QM calculations and differs from conventional parametrization approaches in that it incorporates some previously neglected solvation-related effects (which appear to be essential for obtaining correct anti/high-anti balance). Our χOL force field is compared with several previous glycosidic torsion parametrizations. PMID:21921995

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.

Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution.

PubMed

Perez, Victor; Chang, Bo-Jui; Stelzer, Ernst Hans Karl

2016-11-16

Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution

NASA Astrophysics Data System (ADS)

Perez, Victor; Chang, Bo-Jui; Stelzer, Ernst Hans Karl

2016-11-01

Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

A Parametric Study of Slag Skin Formation in Electroslag Remelting

NASA Astrophysics Data System (ADS)

Yanke, Jeff; Krane, Matthew John M.

In electroslag remelting (ESR), the slag generates heat, chemically refines the melting electrode material, and forms frozen skin on the mold. An axisymmetric model is used to simulate fluid flow, heat transfer, solidification, and electromagnetics and their interaction with slag skin formation in ESR. A volume of fluid (VOF) method is used to track the slag/metal interface, allowing simulation of slag freezing to the mold. Mold diameter and applied current are varied to determine how these parameters affect melt rate and formation of slag skin during ESR. Variations in the slag skin thickness within the slag cap are found to have a significant impact on melt rate and depth of metal sump. Changes in slag cap volume resulted in small changes in melt rate.

Constructing a simple parametric model of shoulder from medical images

NASA Astrophysics Data System (ADS)

Atmani, H.; Fofi, D.; Merienne, F.; Trouilloud, P.

2006-02-01

The modelling of the shoulder joint is an important step to set a Computer-Aided Surgery System for shoulder prosthesis placement. Our approach mainly concerns the bones structures of the scapulo-humeral joint. Our goal is to develop a tool that allows the surgeon to extract morphological data from medical images in order to interpret the biomechanical behaviour of a prosthesised shoulder for preoperative and peroperative virtual surgery. To provide a light and easy-handling representation of the shoulder, a geometrical model composed of quadrics, planes and other simple forms is proposed.

Computation-Friendly Shape Grammars with Application to Determining the Interior Layout of Buildings from Image Data

ERIC Educational Resources Information Center

Yue, Kui

2009-01-01

A shape grammar is a formalism that has been widely applied, in many different fields, to analyzing designs. Computer implementation of a shape grammar interpreter is vital to both research and application. However, implementing a shape grammar interpreter is hard, especially for parametric shapes defined by open terms. This dissertation…

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).

A parametric study of face recognition when image degradations are combined.

PubMed

Uttal, W R; Baruch, T; Allen, L

1997-01-01

This article expands and quantifies one of the classic reports of modern visual perception research--Harmon and Julesz' (1973) demonstration of an enhancement in recognition performance when area averaging (blocking) and spatial frequency filtering are sequentially applied. Our goals were twofold: first, to determine if the existence of the phenomena could be confirmed and replicated in a parametric study; second, to determine if the new results supported the critical band masking theory originally proposed by Harmon and Julesz. We confirmed the presence of the phenomenon for stimuli subtending approximately six deg of visual angle vertically, but observed a surprisingly different pattern of results for smaller stimuli subtending approximately one deg. These and other recent findings from other laboratories raise questions about their masking theory as a complete explanation of the phenomena.

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

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

Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V., E-mail: Yu.Kuyanov@gmail.com

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description ofmore » data are schematically shown. The DaMoScope codes are freely available.« less

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.

Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging.

PubMed

Cheng, Xiaoyin; Li, Zhoulei; Liu, Zhen; Navab, Nassir; Huang, Sung-Cheng; Keller, Ulrich; Ziegler, Sibylle; Shi, Kuangyu

2015-02-12

The separation of multiple PET tracers within an overlapping scan based on intrinsic differences of tracer pharmacokinetics is challenging, due to limited signal-to-noise ratio (SNR) of PET measurements and high complexity of fitting models. In this study, we developed a direct parametric image reconstruction (DPIR) method for estimating kinetic parameters and recovering single tracer information from rapid multi-tracer PET measurements. This is achieved by integrating a multi-tracer model in a reduced parameter space (RPS) into dynamic image reconstruction. This new RPS model is reformulated from an existing multi-tracer model and contains fewer parameters for kinetic fitting. Ordered-subsets expectation-maximization (OSEM) was employed to approximate log-likelihood function with respect to kinetic parameters. To incorporate the multi-tracer model, an iterative weighted nonlinear least square (WNLS) method was employed. The proposed multi-tracer DPIR (MTDPIR) algorithm was evaluated on dual-tracer PET simulations ([18F]FDG and [11C]MET) as well as on preclinical PET measurements ([18F]FLT and [18F]FDG). The performance of the proposed algorithm was compared to the indirect parameter estimation method with the original dual-tracer model. The respective contributions of the RPS technique and the DPIR method to the performance of the new algorithm were analyzed in detail. For the preclinical evaluation, the tracer separation results were compared with single [18F]FDG scans of the same subjects measured 2 days before the dual-tracer scan. The results of the simulation and preclinical studies demonstrate that the proposed MT-DPIR method can improve the separation of multiple tracers for PET image quantification and kinetic parameter estimations.

Automatic Extraction of Myocardial Mass and Volume Using Parametric Images from Dynamic Nongated PET.

PubMed

Harms, Hendrik Johannes; Stubkjær Hansson, Nils Henrik; Tolbod, Lars Poulsen; Kim, Won Yong; Jakobsen, Steen; Bouchelouche, Kirsten; Wiggers, Henrik; Frøkiaer, Jørgen; Sörensen, Jens

2016-09-01

Dynamic cardiac PET is used to quantify molecular processes in vivo. However, measurements of left ventricular (LV) mass and volume require electrocardiogram-gated PET data. The aim of this study was to explore the feasibility of measuring LV geometry using nongated dynamic cardiac PET. Thirty-five patients with aortic-valve stenosis and 10 healthy controls underwent a 27-min (11)C-acetate PET/CT scan and cardiac MRI (CMR). The controls were scanned twice to assess repeatability. Parametric images of uptake rate K1 and the blood pool were generated from nongated dynamic data. Using software-based structure recognition, the LV wall was automatically segmented from K1 images to derive functional assessments of LV mass (mLV) and wall thickness. End-systolic and end-diastolic volumes were calculated using blood pool images and applied to obtain stroke volume and LV ejection fraction (LVEF). PET measurements were compared with CMR. High, linear correlations were found for LV mass (r = 0.95), end-systolic volume (r = 0.93), and end-diastolic volume (r = 0.90), and slightly lower correlations were found for stroke volume (r = 0.74), LVEF (r = 0.81), and thickness (r = 0.78). Bland-Altman analyses showed significant differences for mLV and thickness only and an overestimation for LVEF at lower values. Intra- and interobserver correlations were greater than 0.95 for all PET measurements. PET repeatability accuracy in the controls was comparable to CMR. LV mass and volume are accurately and automatically generated from dynamic (11)C-acetate PET without electrocardiogram gating. This method can be incorporated in a standard routine without any additional workload and can, in theory, be extended to other PET tracers. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Volumetric Contrast-Enhanced Ultrasound Imaging to Assess Early Response to Apoptosis-Inducing Anti–Death Receptor 5 Antibody Therapy in a Breast Cancer Animal Model

PubMed Central

Hoyt, Kenneth; Sorace, Anna; Saini, Reshu

2013-01-01

Objectives The objective of this study was to determine whether volumetric contrast-enhanced ultrasound (US) imaging could detect early tumor response to anti–death receptor 5 antibody (TRA-8) therapy alone or in combination with chemotherapy in a preclinical triple-negative breast cancer animal model. Methods Animal experiments had Institutional Animal Care and Use Committee approval. Thirty breast tumor–bearing mice were administered Abraxane (paclitaxel; Celgene Corporation, Summit, NJ), TRA-8, TRA-8 + Abraxane, or saline as a control on days 0, 3, 7, 10, 14, and 17. Volumetric contrast-enhanced US imaging was performed on days 0, 1, 3, and 7 before dosing. Changes in parametric maps of tumor perfusion were compared with the tumor volume and immunohistologic findings. Results Therapeutic efficacy was detected within 7 days after drug administration using parametric volumetric contrast-enhanced US imaging. Decreased tumor perfusion was observed in both the TRA-8-alone– and TRA-8 + Abraxane–dosed animals compared to control tumors (P = .17; P = .001, respectively). The reduction in perfusion observed in the TRA-8 + Abraxane group was matched with a corresponding regression in tumor size over the same period. Survival curves illustrate that the combination of TRA-8 + Abraxane improves drug efficacy compared to the same drugs administered alone. Immunohistologic analysis revealed increased levels of apoptotic activity in the TRA-8-dosed tumors, confirming enhanced antitumor effects. Conclusions Preliminary results are encouraging, and volumetric contrast-enhanced US-based tumor perfusion imaging may prove clinically feasible for detecting and monitoring the early antitumor effects in response to combination TRA-8 + Abraxane therapy. PMID:23091246

Whole-body diffusion kurtosis imaging: initial experience on non-Gaussian diffusion in various organs.

PubMed

Filli, Lukas; Wurnig, Moritz; Nanz, Daniel; Luechinger, Roger; Kenkel, David; Boss, Andreas

2014-12-01

Diffusion kurtosis imaging (DKI) is based on a non-Gaussian diffusion model that should inherently better account for restricted water diffusion within the complex microstructure of most tissues than the conventional diffusion-weighted imaging (DWI), which presumes Gaussian distributed water molecule displacement probability. The aim of this investigation was to test the technical feasibility of in vivo whole-body DKI, probe for organ-specific differences, and compare whole-body DKI and DWI results. Eight healthy subjects underwent whole-body DWI on a clinical 3.0 T magnetic resonance imaging system. Echo-planar images in the axial orientation were acquired at b-values of 0, 150, 300, 500, and 800 mm²/s. Parametrical whole-body maps of the diffusion coefficient (D), the kurtosis (K), and the traditional apparent diffusion coefficient (ADC) were generated. Goodness of fit was compared between DKI and DWI fits using the sums of squared residuals. Data groups were tested for significant differences of the mean by paired Student t tests. Good-quality parametrical whole-body maps of D, K, and ADC could be computed. Compared with ADC values, D values were significantly higher in the cerebral gray matter (by 30%) and white matter (27%), renal cortex (23%) and medulla (21%), spleen (101%), as well as erector spinae muscle (34%) (each P value <0.001). No significant differences between D and ADC were found in the cerebrospinal fluid (P = 0.08) and in the liver (P = 0.13). Curves of DKI fitted the measurement points significantly better than DWI curves did in most organs. Whole-body DKI is technically feasible and may reflect tissue microstructure more meaningfully than whole-body DWI.

Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

2013-07-01

This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.

Enhanced detection and visualization of anomalies in spectral imagery

NASA Astrophysics Data System (ADS)

Basener, William F.; Messinger, David W.

2009-05-01

Anomaly detection algorithms applied to hyperspectral imagery are able to reliably identify man-made objects from a natural environment based on statistical/geometric likelyhood. The process is more robust than target identification, which requires precise prior knowledge of the object of interest, but has an inherently higher false alarm rate. Standard anomaly detection algorithms measure deviation of pixel spectra from a parametric model (either statistical or linear mixing) estimating the image background. The topological anomaly detector (TAD) creates a fully non-parametric, graph theory-based, topological model of the image background and measures deviation from this background using codensity. In this paper we present a large-scale comparative test of TAD against 80+ targets in four full HYDICE images using the entire canonical target set for generation of ROC curves. TAD will be compared against several statistics-based detectors including local RX and subspace RX. Even a perfect anomaly detection algorithm would have a high practical false alarm rate in most scenes simply because the user/analyst is not interested in every anomalous object. To assist the analyst in identifying and sorting objects of interest, we investigate coloring of the anomalies with principle components projections using statistics computed from the anomalies. This gives a very useful colorization of anomalies in which objects of similar material tend to have the same color, enabling an analyst to quickly sort and identify anomalies of highest interest.

Clinical multiphoton and CARS microscopy

NASA Astrophysics Data System (ADS)

Breunig, H. G.; Weinigel, M.; Darvin, M. E.; Lademann, J.; König, K.

2012-03-01

We report on clinical CARS imaging of human skin in vivo with the certified hybrid multiphoton tomograph CARSDermaInspect. The CARS-DermaInspect provides simultaneous imaging of non-fluorescent intradermal lipid and water as well as imaging of two-photon excited fluorescence from intrinsic molecules. Two different excitation schemes for CARS imaging have been realized: In the first setup, a combination of fs oscillator and optical parametric oscillator provided fs-CARS pump and Stokes pulses, respectively. In the second setup a fs oscillator was combined with a photonic crystal fiber which provided a broadband spectrum. A spectral range out of the broadband-spectrum was selected and used for CARS excitation in combination with the residual fs-oscillator output. In both setups, in addition to CARS, single-beam excitation was used for imaging of two-photon excited fluorescence and second harmonic generation signals. Both CARS-excitation systems were successfully used for imaging of lipids inside the skin in vivo.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

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.

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.

Acoustically modulated magnetic resonance imaging of gas-filled protein nanostructures

NASA Astrophysics Data System (ADS)

Lu, George J.; Farhadi, Arash; Szablowski, Jerzy O.; Lee-Gosselin, Audrey; Barnes, Samuel R.; Lakshmanan, Anupama; Bourdeau, Raymond W.; Shapiro, Mikhail G.

2018-05-01

Non-invasive biological imaging requires materials capable of interacting with deeply penetrant forms of energy such as magnetic fields and sound waves. Here, we show that gas vesicles (GVs), a unique class of gas-filled protein nanostructures with differential magnetic susceptibility relative to water, can produce robust contrast in magnetic resonance imaging (MRI) at sub-nanomolar concentrations, and that this contrast can be inactivated with ultrasound in situ to enable background-free imaging. We demonstrate this capability in vitro, in cells expressing these nanostructures as genetically encoded reporters, and in three model in vivo scenarios. Genetic variants of GVs, differing in their magnetic or mechanical phenotypes, allow multiplexed imaging using parametric MRI and differential acoustic sensitivity. Additionally, clustering-induced changes in MRI contrast enable the design of dynamic molecular sensors. By coupling the complementary physics of MRI and ultrasound, this nanomaterial gives rise to a distinct modality for molecular imaging with unique advantages and capabilities.

Segmentation and Tracking of Cytoskeletal Filaments Using Open Active Contours

PubMed Central

Smith, Matthew B.; Li, Hongsheng; Shen, Tian; Huang, Xiaolei; Yusuf, Eddy; Vavylonis, Dimitrios

2010-01-01

We use open active contours to quantify cytoskeletal structures imaged by fluorescence microscopy in two and three dimensions. We developed an interactive software tool for segmentation, tracking, and visualization of individual fibers. Open active contours are parametric curves that deform to minimize the sum of an external energy derived from the image and an internal bending and stretching energy. The external energy generates (i) forces that attract the contour toward the central bright line of a filament in the image, and (ii) forces that stretch the active contour toward the ends of bright ridges. Images of simulated semiflexible polymers with known bending and torsional rigidity are analyzed to validate the method. We apply our methods to quantify the conformations and dynamics of actin in two examples: actin filaments imaged by TIRF microscopy in vitro, and actin cables in fission yeast imaged by spinning disk confocal microscopy. PMID:20814909

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

A mixture model for robust registration in Kinect sensor

NASA Astrophysics Data System (ADS)

Peng, Li; Zhou, Huabing; Zhu, Shengguo

2018-03-01

The Microsoft Kinect sensor has been widely used in many applications, but it suffers from the drawback of low registration precision between color image and depth image. In this paper, we present a robust method to improve the registration precision by a mixture model that can handle multiply images with the nonparametric model. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS).The estimation is performed by the EM algorithm which by also estimating the variance of the prior model is able to obtain good estimates. We illustrate the proposed method on the public available dataset. The experimental results show that our approach outperforms the baseline methods.

Comparison of scalar measures used in magnetic resonance diffusion tensor imaging.

PubMed

Bahn, M M

1999-07-01

The tensors derived from diffusion tensor imaging describe complex diffusion in tissues. However, it is difficult to compare tensors directly or to produce images that contain all of the information of the tensor. Therefore, it is convenient to produce scalar measures that extract desired aspects of the tensor. These measures map the three-dimensional eigenvalues of the diffusion tensor into scalar values. The measures impose an order on eigenvalue space. Many invariant scalar measures have been introduced in the literature. In the present manuscript, a general approach for producing invariant scalar measures is introduced. Because it is often difficult to determine in clinical practice which of the many measures is best to apply to a given situation, two formalisms are introduced for the presentation, definition, and comparison of measures applied to eigenvalues: (1) normalized eigenvalue space, and (2) parametric eigenvalue transformation plots. All of the anisotropy information contained in the three eigenvalues can be retained and displayed in a two-dimensional plot, the normalized eigenvalue plot. An example is given of how to determine the best measure to use for a given situation by superimposing isometric contour lines from various anisotropy measures on plots of actual measured eigenvalue data points. Parametric eigenvalue transformation plots allow comparison of how different measures impose order on normalized eigenvalue space to determine whether the measures are equivalent and how the measures differ. These formalisms facilitate the comparison of scalar invariant measures for diffusion tensor imaging. Normalized eigenvalue space allows presentation of eigenvalue anisotropy information. Copyright 1999 Academic Press.

LORETA imaging of P300 in schizophrenia with individual MRI and 128-channel EEG.

PubMed

Pae, Ji Soo; Kwon, Jun Soo; Youn, Tak; Park, Hae-Jeong; Kim, Myung Sun; Lee, Boreom; Park, Kwang Suk

2003-11-01

We investigated the characteristics of P300 generators in schizophrenics by using voxel-based statistical parametric mapping of current density images. P300 generators, produced by a rare target tone of 1500 Hz (15%) under a frequent nontarget tone of 1000 Hz (85%), were measured in 20 right-handed schizophrenics and 21 controls. Low-resolution electromagnetic tomography (LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Three-dimensional current density images were reconstructed from the LORETA intensity maps that covered the whole cortical gray matter. Spatial normalization and intensity normalization of the smoothed current density images were used to reduce anatomical variance and subject-specific global activity and statistical parametric mapping (SPM) was applied for the statistical analysis. We found that the sources of P300 were consistently localized at the left superior parietal area in normal subjects, while those of schizophrenics were diversely distributed. Upon statistical comparison, schizophrenics, with globally reduced current densities, showed a significant P300 current density reduction in the left medial temporal area and in the left inferior parietal area, while both left prefrontal and right orbitofrontal areas were relatively activated. The left parietotemporal area was found to correlate negatively with Positive and Negative Syndrome Scale total scores of schizophrenic patients. In conclusion, the reduced and increased areas of current density in schizophrenic patients suggest that the medial temporal and frontal areas contribute to the pathophysiology of schizophrenia, the frontotemporal circuitry abnormality.

Pig brain stereotaxic standard space: mapping of cerebral blood flow normative values and effect of MPTP-lesioning.

PubMed

Andersen, Flemming; Watanabe, Hideaki; Bjarkam, Carsten; Danielsen, Erik H; Cumming, Paul

2005-07-15

The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies of minipig brain, we calculated cerebral blood flow (CBF) maps from normal minipigs and from minipigs with a syndrome of parkisonism induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-poisoning. These maps were transformed from the native space into the common stereotaxic space. After global normalization of these maps, an undirected search for differences between the groups was then performed using statistical parametric mapping. Using this method, we detected a statistically significant focal increase in CBF in the left cerebellum of the MPTP-lesioned group. We expect the present approach to be of general use in the statistical parametric mapping of CBF and other physiological parameters in living pig brain.

A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

PubMed

Wallis, Thomas S A; Funke, Christina M; Ecker, Alexander S; Gatys, Leon A; Wichmann, Felix A; Bethge, Matthias

2017-10-01

Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important for texture perception, we psychophysically compare a recent parametric model of texture appearance (convolutional neural network [CNN] model) that uses the features encoded by a deep CNN (VGG-19) with two other models: the venerable Portilla and Simoncelli model and an extension of the CNN model in which the power spectrum is additionally matched. Observers discriminated model-generated textures from original natural textures in a spatial three-alternative oddity paradigm under two viewing conditions: when test patches were briefly presented to the near-periphery ("parafoveal") and when observers were able to make eye movements to all three patches ("inspection"). Under parafoveal viewing, observers were unable to discriminate 10 of 12 original images from CNN model images, and remarkably, the simpler Portilla and Simoncelli model performed slightly better than the CNN model (11 textures). Under foveal inspection, matching CNN features captured appearance substantially better than the Portilla and Simoncelli model (nine compared to four textures), and including the power spectrum improved appearance matching for two of the three remaining textures. None of the models we test here could produce indiscriminable images for one of the 12 textures under the inspection condition. While deep CNN (VGG-19) features can often be used to synthesize textures that humans cannot discriminate from natural textures, there is currently no uniformly best model for all textures and viewing conditions.

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

PubMed Central

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-01-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate Ki as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting Ki images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit Ki bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source Software for Tomographic Image Reconstruction (STIR) platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced Ki target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D vs. the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10–20 sub-iterations. Moreover, systematic reduction in Ki % bias and improved TBR were observed for gPatlak vs. sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior Ki CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging. PMID:27383991

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-08-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were observed for gPatlak versus sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior K i CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging.

User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation. [input to three dimensional computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gibson, S. G.

1983-01-01

A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

Laser produced nanocavities in silica and sapphire: a parametric study

NASA Astrophysics Data System (ADS)

Hallo, L.; Bourgeade, A.; Travaillé, G.; Tikhonchuk, V. T.; Nkonga, B.; Breil, J.

2008-05-01

We present a model, that describes a sub-micron cavity formation in a transparent dielectric under a tight focusing of a ultra-short laser pulse. The model solves the full set of Maxwell's equations in the three-dimensional geometry along with non-linear propagation phenomenons. This allows us to initialize hydrodynamic simulations of the sub-micron cavity formation. Cavity characteristics, which depend on 3D energy release and non linear effects, have been investigated and compared with experimental results. For this work, we want to deeply acknowledge the numerical support provided by the CEA Centre de Calcul Recherche et Technologie, whose help guaranteed the achievement of this study.

Evaluation of Water Injection Effect on NO(x) Formation for a Staged Gas Turbine Combustor

NASA Technical Reports Server (NTRS)

Fan, L.; Yang, S. L.; Kundu, K. P.

1996-01-01

NO(x) emission control by water injection on a staged turbine combustor (STC) was modeled using the KIVA-2 code with modification. Water is injected into the rich-burn combustion zone of the combustor by a single nozzle. Parametric study for different water injection patterns was performed. Results show NO(x) emission will decrease after water being injected. Water nozzle location also has significant effect for NO formation and fuel ignition. The chemical kinetic model is also sensitive to the excess water. Through this study, a better understanding of the physics and chemical kinetics is obtained, this will enhance the STC design process.

Large scale surface flow generation in driven suspensions of magnetic microparticles: Experiment, theoretical model and simulations

NASA Astrophysics Data System (ADS)

Belkin, Maxim; Snezhko, Alexey; Aranson, Igor

2007-03-01

Nontrivially ordered dynamic self-assembled snake-like structures are formed in an ensemble of magnetic microparticles suspended over a fluid surface and energized by an external alternating magnetic field. Formation and existence of such structures is always accompanied by flows which form vortices. These large-scale vortices can be very fast and are crucial for snake formation/destruction. We introduce theoretical model based on Ginzburg-Landau equation for parametrically excited surface waves coupled to conservation law for particle density and Navier-Stokes equation for water flows. The developed model successfully describes snake generation, accounts for flows and reproduces most experimental results observed.

Comparative study on the performance of textural image features for active contour segmentation.

PubMed

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

Non-parametric analysis of LANDSAT maps using neural nets and parallel computers

NASA Technical Reports Server (NTRS)

Salu, Yehuda; Tilton, James

1991-01-01

Nearest neighbor approaches and a new neural network, the Binary Diamond, are used for the classification of images of ground pixels obtained by LANDSAT satellite. The performances are evaluated by comparing classifications of a scene in the vicinity of Washington DC. The problem of optimal selection of categories is addressed as a step in the classification process.

Up Periscope! Designing a New Perceptual Metric for Imaging System Performance

NASA Technical Reports Server (NTRS)

Watson, Andrew B.

2016-01-01

Modern electronic imaging systems include optics, sensors, sampling, noise, processing, compression, transmission and display elements, and are viewed by the human eye. Many of these elements cannot be assessed by traditional imaging system metrics such as the MTF. More complex metrics such as NVTherm do address these elements, but do so largely through parametric adjustment of an MTF-like metric. The parameters are adjusted through subjective testing of human observers identifying specific targets in a set of standard images. We have designed a new metric that is based on a model of human visual pattern classification. In contrast to previous metrics, ours simulates the human observer identifying the standard targets. One application of this metric is to quantify performance of modern electronic periscope systems on submarines.

Direct Bio-printing with Heterogeneous Topology Design.

PubMed

Ahsan, Amm Nazmul; Xie, Ruinan; Khoda, Bashir

2017-01-01

Bio-additive manufacturing is a promising tool to fabricate porous scaffold structures for expediting the tissue regeneration processes. Unlike the most traditional bulk material objects, the microstructures of tissue and organs are mostly highly anisotropic, heterogeneous, and porous in nature. However, modelling the internal heterogeneity of tissues/organs structures in the traditional CAD environment is difficult and oftentimes inaccurate. Besides, the de facto STL conversion of bio-models introduces loss of information and piles up more errors in each subsequent step (build orientation, slicing, tool-path planning) of the bio-printing process plan. We are proposing a topology based scaffold design methodology to accurately represent the heterogeneous internal architecture of tissues/organs. An image analysis technique is used that digitizes the topology information contained in medical images of tissues/organs. A weighted topology reconstruction algorithm is implemented to represent the heterogeneity with parametric functions. The parametric functions are then used to map the spatial material distribution. The generated information is directly transferred to the 3D bio-printer and heterogeneous porous tissue scaffold structure is manufactured without STL file. The proposed methodology is implemented to verify the effectiveness of the approach and the designed example structure is bio-fabricated with a deposition based bio-additive manufacturing system.

Ultrasound-aided Multi-parametric Photoacoustic Microscopy of the Mouse Brain.

PubMed

Ning, Bo; Sun, Naidi; Cao, Rui; Chen, Ruimin; Kirk Shung, K; Hossack, John A; Lee, Jin-Moo; Zhou, Qifa; Hu, Song

2015-12-21

High-resolution quantitative imaging of cerebral oxygen metabolism in mice is crucial for understanding brain functions and formulating new strategies to treat neurological disorders, but remains a challenge. Here, we report on our newly developed ultrasound-aided multi-parametric photoacoustic microscopy (PAM), which enables simultaneous quantification of the total concentration of hemoglobin (CHb), the oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF) at the microscopic level and through the intact mouse skull. The three-dimensional skull and vascular anatomies delineated by the dual-contrast (i.e., ultrasonic and photoacoustic) system provide important guidance for dynamically focused contour scan and vessel orientation-dependent correction of CBF, respectively. Moreover, bi-directional raster scan allows determining the direction of blood flow in individual vessels. Capable of imaging all three hemodynamic parameters at the same spatiotemporal scale, our ultrasound-aided PAM fills a critical gap in preclinical neuroimaging and lays the foundation for high-resolution mapping of the cerebral metabolic rate of oxygen (CMRO2)-a quantitative index of cerebral oxygen metabolism. This technical innovation is expected to shed new light on the mechanism and treatment of a broad spectrum of neurological disorders, including Alzheimer's disease and ischemic stroke.

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

Modeling and Simulation of a Parametrically Resonant Micromirror With Duty-Cycled Excitation

PubMed Central

Shahid, Wajiha; Qiu, Zhen; Duan, Xiyu; Li, Haijun; Wang, Thomas D.; Oldham, Kenn R.

2014-01-01

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. PMID:25506188

Star formation history of the Galactic bulge from deep HST imaging of low reddening windows

NASA Astrophysics Data System (ADS)

Bernard, Edouard J.; Schultheis, Mathias; Di Matteo, Paola; Hill, Vanessa; Haywood, Misha; Calamida, Annalisa

2018-07-01

Despite the huge amount of photometric and spectroscopic efforts targeting the Galactic bulge over the past few years, its age distribution remains controversial owing to both the complexity of determining the age of individual stars and the difficult observing conditions. Taking advantage of the recent release of very deep, proper-motion-cleaned colour-magnitude diagrams (CMDs) of four low reddening windows obtained with the Hubble Space Telescope (HST), we used the CMD-fitting technique to calculate the star formation history (SFH) of the bulge at -2° > b > -4° along the minor axis. We find that over 80 per cent of the stars formed before 8 Gyr ago, but that a significant fraction of the super-solar metallicity stars are younger than this age. Considering only the stars that are within reach of the current generation of spectrographs (i.e. V≲ 21), we find that 10 per cent of the bulge stars are younger than 5 Gyr, while this fraction rises to 20-25 per cent in the metal-rich peak. The age-metallicity relation is well parametrized by a linear fit, implying an enrichment rate of dZ/dt ˜ 0.005 Gyr-1. Our metallicity distribution function accurately reproduces that observed by several spectroscopic surveys of Baade's window, with the bulk of stars having metal content in the range [Fe/H]˜-0.7 to ˜0.6, along with a sparse tail to much lower metallicities.

Star formation history of the Galactic bulge from deep HST imaging of low reddening windows

NASA Astrophysics Data System (ADS)

Bernard, Edouard J.; Schultheis, Mathias; Di Matteo, Paola; Hill, Vanessa; Haywood, Misha; Calamida, Annalisa

2018-04-01

Despite the huge amount of photometric and spectroscopic efforts targetting the Galactic bulge over the past few years, its age distribution remains controversial owing to both the complexity of determining the age of individual stars and the difficult observing conditions. Taking advantage of the recent release of very deep, proper-motion-cleaned colour-magnitude diagrams (CMDs) of four low reddening windows obtained with the Hubble Space Telescope (HST), we used the CMD-fitting technique to calculate the star formation history (SFH) of the bulge at -2° > b > -4° along the minor axis. We find that over 80 percent of the stars formed before 8 Gyr ago, but that a significant fraction of the super-solar metallicity stars are younger than this age. Considering only the stars that are within reach of the current generation of spectrographs (i.e. V≲ 21), we find that 10 percent of the bulge stars are younger than 5 Gyr, while this fraction rises to 20-25 percent in the metal-rich peak. The age-metallicity relation is well parametrized by a linear fit implying an enrichment rate of dZ/dt ˜ 0.005 Gyr-1. Our metallicity distribution function accurately reproduces that observed by several spectroscopic surveys of Baade's window, with the bulk of stars having metal-content in the range [Fe/H]˜-0.7 to ˜0.6, along with a sparse tail to much lower metallicities.

Comparing an optical parametric oscillator (OPO) as a viable alternative for mid-infrared tissue ablation with a free electron laser (FEL).

PubMed

Mackanos, Mark A; Simanovskii, Dmitrii M; Contag, Christopher H; Kozub, John A; Jansen, E Duco

2012-11-01

Beneficial medical laser ablation removes material efficiently with minimal collateral damage. A Mark-III free electron laser (FEL), at a wavelength of 6.45 μm has demonstrated minimal damage and high ablation yield in ocular and neural tissues. While this wavelength has shown promise for surgical applications, further advances are limited by the high overhead for FEL use. Alternative mid-infrared sources are needed for further development. We compared the FEL with a 5-μs pulse duration with a Q-switched ZGP-OPO with a 100-ns pulse duration at mid-infrared wavelengths. There were no differences in the ablation threshold of water and mouse dermis with these two sources in spite of the difference in their pulse structures. There was a significant difference in crater depth between the ZGP:OPO and the FEL. At 6.1 μm, the OPO craters are eight times the depth of the FEL craters. The OPO craters at 6.45 and 6.73 μm were six and five times the depth of the FEL craters, respectively. Bright-field (pump-probe) images showed the classic ablation mechanism from formation of a plume through collapse and recoil. The crater formation, ejection, and collapse phases occurred on a faster time-scale with the OPO than with the FEL. This research showed that a ZGP-OPO laser could be a viable alternative to FEL for clinical applications.

Distributed attitude synchronization of formation flying via consensus-based virtual structure

NASA Astrophysics Data System (ADS)

Cong, Bing-Long; Liu, Xiang-Dong; Chen, Zhen

2011-06-01

This paper presents a general framework for synchronized multiple spacecraft rotations via consensus-based virtual structure. In this framework, attitude control systems for formation spacecrafts and virtual structure are designed separately. Both parametric uncertainty and external disturbance are taken into account. A time-varying sliding mode control (TVSMC) algorithm is designed to improve the robustness of the actual attitude control system. As for the virtual attitude control system, a behavioral consensus algorithm is presented to accomplish the attitude maneuver of the entire formation and guarantee a consistent attitude among the local virtual structure counterparts during the attitude maneuver. A multiple virtual sub-structures (MVSSs) system is introduced to enhance current virtual structure scheme when large amounts of spacecrafts are involved in the formation. The attitude of spacecraft is represented by modified Rodrigues parameter (MRP) for its non-redundancy. Finally, a numerical simulation with three synchronization situations is employed to illustrate the effectiveness of the proposed strategy.

Formation of molecules in an expanding Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Yurovsky, Vladimir; Ben-Reuven, Abraham

2004-05-01

A mean field theory [1] is extended to an inhomogeneous case of expanding hybrid atom-molecule Bose-Einstein condensates. This theory is applied to the recent MPI experiments [2] on ^87Rb demonstrating the formation of ultracold molecules due to Feshbach resonance. The subsequent dissociation of the molecules is treated using a non-mean-field parametric approximation [3]. The latter method is also used in determining optimal conditions for the formation of molecular BEC. [1] V. A. Yurovsky, A. Ben-Reuven, P. S. Julienne and C. J. Williams, Phys. Rev. A 60, R765 (1999); Phys. Rev. A 62, 043605 (2000). [2] S. Dürr, T. Volz, A. Marte, and G. Rempe, Phys. Rev. Lett. 92, 020406 (2004). [3] V. A. Yurovsky and A. Ben-Reuven, Phys. Rev. A 67, 043611 (2003).

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Strategies for the generation of parametric images of [11C]PIB with plasma input functions considering discriminations and reproducibility.

PubMed

Edison, Paul; Brooks, David J; Turkheimer, Federico E; Archer, Hilary A; Hinz, Rainer

2009-11-01

Pittsburgh compound B or [11C]PIB is an amyloid imaging agent which shows a clear differentiation between subjects with Alzheimer's disease (AD) and controls. However the observed signal difference in other forms of dementia such as dementia with Lewy bodies (DLB) is smaller, and mild cognitively impaired (MCI) subjects and some healthy elderly normals may show intermediate levels of [11C]PIB binding. The cerebellum, a commonly used reference region for non-specific tracer uptake in [11C]PIB studies in AD may not be valid in Prion disorders or monogenic forms of AD. The aim of this work was to: 1-compare methods for generating parametric maps of [11C]PIB retention in tissue using a plasma input function in respect of their ability to discriminate between AD subjects and controls and 2-estimate the test-retest reproducibility in AD subjects. 12 AD subjects (5 of which underwent a repeat scan within 6 weeks) and 10 control subjects had 90 minute [11C]PIB dynamic PET scans, and arterial plasma input functions were measured. Parametric maps were generated with graphical analysis of reversible binding (Logan plot), irreversible binding (Patlak plot), and spectral analysis. Between group differentiation was calculated using Student's t-test and comparisons between different methods were made using p values. Reproducibility was assessed by intraclass correlation coefficients (ICC). We found that the 75 min value of the impulse response function showed the best group differentiation and had a higher ICC than volume of distribution maps generated from Logan and spectral analysis. Patlak analysis of [11C]PIB binding was the least reproducible.

Fission properties of Po isotopes in different macroscopic-microscopic models

NASA Astrophysics Data System (ADS)

Bartel, J.; Pomorski, K.; Nerlo-Pomorska, B.; Schmitt, Ch

2015-11-01

Fission-barrier heights of nuclei in the Po isotopic chain are investigated in several macroscopic-microscopic models. Using the Yukawa-folded single-particle potential, the Lublin-Strasbourg drop (LSD) model, the Strutinsky shell-correction method to yield the shell corrections and the BCS theory for the pairing contributions, fission-barrier heights are calculated and found in quite good agreement with the experimental data. This turns out, however, to be only the case when the underlying macroscopic, liquid-drop (LD) type, theory is well chosen. Together with the LSD approach, different LD parametrizations proposed by Moretto et al are tested. Four deformation parameters describing respectively elongation, neck-formation, reflectional-asymmetric, and non-axiality of the nuclear shape thus defining the so called modified Funny Hills shape parametrization are used in the calculation. The present study clearly demonstrates that nuclear fission-barrier heights constitute a challenging and selective tool to discern between such different macroscopic approaches.

Dynamics of multiple double layers in high pressure glow discharge in a simple torus

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

Kumar Paul, Manash, E-mail: manashkr@gmail.com; Sharma, P. K.; Thakur, A.

2014-06-15

Parametric characterization of multiple double layers is done during high pressure glow discharge in a toroidal vessel of small aspect ratio. Although glow discharge (without magnetic field) is known to be independent of device geometry, but the toroidal boundary conditions are conducive to plasma growth and eventually the plasma occupy the toroidal volume partially. At higher anode potential, the visibly glowing spots on the body of spatially extended anode transform into multiple intensely luminous spherical plasma blob structures attached to the tip of the positive electrode. Dynamics of multiple double layers are observed in argon glow discharge plasma in presencemore » of toroidal magnetic field. The radial profiles of plasma parameters measured at various toroidal locations show signatures of double layer formation in our system. Parametric dependence of double layer dynamics in presence of toroidal magnetic field is presented here.« less

Test data from small solid propellant rocket motor plume measurements (FA-21)

NASA Technical Reports Server (NTRS)

Hair, L. M.; Somers, R. E.

1976-01-01

A program is described for obtaining a reliable, parametric set of measurements in the exhaust plumes of solid propellant rocket motors. Plume measurements included pressures, temperatures, forces, heat transfer rates, particle sampling, and high-speed movies. Approximately 210,000 digital data points and 15,000 movie frames were acquired. Measurements were made at points in the plumes via rake-mounted probes, and on the surface of a large plate impinged by the exhaust plume. Parametric variations were made in pressure altitude, propellant aluminum loading, impinged plate incidence angle and distance from nozzle exit to plate or rake. Reliability was incorporated by continual use of repeat runs. The test setup of the various hardware items is described along with an account of test procedures. Test results and data accuracy are discussed. Format of the data presentation is detailed. Complete data are included in the appendix.

SPH/N-Body simulations of small (D = 10km) asteroidal breakups and improved parametric relations for Monte-Carlo collisional models

NASA Astrophysics Data System (ADS)

Ševeček, P.; Brož, M.; Nesvorný, D.; Enke, B.; Durda, D.; Walsh, K.; Richardson, D. C.

2017-11-01

We report on our study of asteroidal breakups, i.e. fragmentations of targets, subsequent gravitational reaccumulation and formation of small asteroid families. We focused on parent bodies with diameters Dpb = 10km . Simulations were performed with a smoothed-particle hydrodynamics (SPH) code combined with an efficient N-body integrator. We assumed various projectile sizes, impact velocities and impact angles (125 runs in total). Resulting size-frequency distributions are significantly different from scaled-down simulations with Dpb = 100km targets (Durda et al., 2007). We derive new parametric relations describing fragment distributions, suitable for Monte-Carlo collisional models. We also characterize velocity fields and angular distributions of fragments, which can be used as initial conditions for N-body simulations of small asteroid families. Finally, we discuss a number of uncertainties related to SPH simulations.

Modeling of Fuel Film Cooling on Chamber Hot Wall

DTIC Science & Technology

2014-07-01

downstream, when the film has been depleted of its cooling and coking capacities, a second slot is needed to inject fresh cool fuel. All of these...pyrolysis and oxidation. 7. As discussed in the introductory section, sooting and coking are notoriously complex topics. Well- validated global...accurate models for soot formation and deposition. Instead, the potential impact of the coke layer is evaluated parametrically by representing the

Formation of magmatic brine lenses via focussed fluid-flow beneath volcanoes

NASA Astrophysics Data System (ADS)

Afanasyev, Andrey; Blundy, Jon; Melnik, Oleg; Sparks, Steve

2018-03-01

Many active or dormant volcanoes show regions of high electrical conductivity at depths of a few kilometres beneath the edifice. We explore the possibility that these regions represent lenses of high-salinity brine separated from a single-phase magmatic fluid containing H2O and NaCl. Since chloride-bearing fluids are highly conductive and have an exceptional capacity to transport metals, these regions can be an indication of an active hydrothermal ore-formation beneath volcanoes. To investigate this possibility we have performed hydrodynamic simulations of magma degassing into permeable rock. In our models the magma source is located at 7 km depth and the fluid salinity approximates that expected for fluids released from typical arc magmas. Our model differs from previous models of a similar process because it is (a) axisymmetric and (b) includes a static high-permeability pathway that links the magma source to the surface. This pathway simulates the presence of a volcanic conduit and/or plexus of feeder dykes that are typical of most volcanic systems. The presence of the conduit leads to a number of important hydrodynamic consequences, not observed in previous models. Importantly, we show that an annular brine lens capped by crystallised halite is likely to form above an actively degassing sub-volcanic magma body and can persist for more than 250 kyr after degassing ceases. Parametric analysis shows that brine lenses are more prevalent when the fluid is released at temperatures above the wet granite solidus, when magmatic fluid salinity is high, and when the high-permeability pathway is narrow. The calculated depth, form and electrical conductivity of our modelled system shares many features with published magnetotelluric images of volcano subsurfaces. The formation and persistence of sub-volcanic brine lenses has implications for geothermal systems and hydrothermal ore formation, although these features are not explored in the presented model.

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Weighted-density functionals for cavity formation and dispersion energies in continuum solvation models

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

Sundararaman, Ravishankar; Gunceler, Deniz; Arias, T. A.

2014-10-07

Continuum solvation models enable efficient first principles calculations of chemical reactions in solution, but require extensive parametrization and fitting for each solvent and class of solute systems. Here, we examine the assumptions of continuum solvation models in detail and replace empirical terms with physical models in order to construct a minimally-empirical solvation model. Specifically, we derive solvent radii from the nonlocal dielectric response of the solvent from ab initio calculations, construct a closed-form and parameter-free weighted-density approximation for the free energy of the cavity formation, and employ a pair-potential approximation for the dispersion energy. We show that the resulting modelmore » with a single solvent-independent parameter: the electron density threshold (n c), and a single solvent-dependent parameter: the dispersion scale factor (s 6), reproduces solvation energies of organic molecules in water, chloroform, and carbon tetrachloride with RMS errors of 1.1, 0.6 and 0.5 kcal/mol, respectively. We additionally show that fitting the solvent-dependent s 6 parameter to the solvation energy of a single non-polar molecule does not substantially increase these errors. Parametrization of this model for other solvents, therefore, requires minimal effort and is possible without extensive databases of experimental solvation free energies.« less

Weighted-density functionals for cavity formation and dispersion energies in continuum solvation models

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

Sundararaman, Ravishankar; Gunceler, Deniz; Arias, T. A.

2014-10-07

Continuum solvation models enable efficient first principles calculations of chemical reactions in solution, but require extensive parametrization and fitting for each solvent and class of solute systems. Here, we examine the assumptions of continuum solvation models in detail and replace empirical terms with physical models in order to construct a minimally-empirical solvation model. Specifically, we derive solvent radii from the nonlocal dielectric response of the solvent from ab initio calculations, construct a closed-form and parameter-free weighted-density approximation for the free energy of the cavity formation, and employ a pair-potential approximation for the dispersion energy. We show that the resulting modelmore » with a single solvent-independent parameter: the electron density threshold (n{sub c}), and a single solvent-dependent parameter: the dispersion scale factor (s{sub 6}), reproduces solvation energies of organic molecules in water, chloroform, and carbon tetrachloride with RMS errors of 1.1, 0.6 and 0.5 kcal/mol, respectively. We additionally show that fitting the solvent-dependent s{sub 6} parameter to the solvation energy of a single non-polar molecule does not substantially increase these errors. Parametrization of this model for other solvents, therefore, requires minimal effort and is possible without extensive databases of experimental solvation free energies.« less

TU-CD-BRB-09: Prediction of Chemo-Radiation Outcome for Rectal Cancer Based On Radiomics of Tumor Clinical Characteristics and Multi-Parametric MRI

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

Nie, K; Yue, N; Shi, L

2015-06-15

Purpose: To evaluate the tumor clinical characteristics and quantitative multi-parametric MR imaging features for prediction of response to chemo-radiation treatment (CRT) in locally advanced rectal cancer (LARC). Methods: Forty-three consecutive patients (59.7±6.9 years, from 09/2013 – 06/2014) receiving neoadjuvant CRT followed by surgery were enrolled. All underwent MRI including anatomical T1/T2, Dynamic Contrast Enhanced (DCE)-MRI and Diffusion-Weighted MRI (DWI) prior to the treatment. A total of 151 quantitative features, including morphology/Gray Level Co-occurrence Matrix (GLCM) texture from T1/T2, enhancement kinetics and the voxelized distribution from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, along with clinical information (carcinoembryonic antigen CEA level,more » TNM staging etc.), were extracted for each patient. Response groups were separated based on down-staging, good response and pathological complete response (pCR) status. Logistic regression analysis (LRA) was used to select the best predictors to classify different groups and the predictive performance were calculated using receiver operating characteristic (ROC) analysis. Results: Individual imaging category or clinical charateristics might yield certain level of power in assessing the response. However, the combined model outperformed than any category alone in prediction. With selected features as Volume, GLCM AutoCorrelation (T2), MaxEnhancementProbability (DCE-MRI), and MeanADC (DWI), the down-staging prediciton accuracy (area under the ROC curve, AUC) could be 0.95, better than individual tumor metrics with AUC from 0.53–0.85. While for the pCR prediction, the best set included CEA (clinical charateristics), Homogeneity (DCE-MRI) and MeanADC (DWI) with an AUC of 0.89, more favorable compared to conventional tumor metrics with an AUC ranging from 0.511–0.79. Conclusion: Through a systematic analysis of multi-parametric MR imaging features, we are able to build models with improved predictive value over conventional imaging or clinical metrics. This is encouraging, suggesting the wealth of imaging radiomics should be further explored to help tailor the treatment into the era of personalized medicine. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

A CONSTANT LIMITING MASS SCALE FOR FLAT EARLY-TYPE GALAXIES FROM z {approx} 1 TO z = 0: DENSITY EVOLVES BUT SHAPES DO NOT

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

Holden, Bradford P.; Van der Wel, Arjen; Rix, Hans-Walter

2012-04-20

We measure the evolution in the intrinsic shape distribution of early-type galaxies from z {approx} 1 to z {approx} 0 by analyzing their projected axis-ratio distributions. We extract a low-redshift sample (0.04 < z < 0.08) of early-type galaxies with very low star formation rates from the Sloan Digital Sky Survey, based on a color-color selection scheme and verified through the absence of emission lines in the spectra. The inferred intrinsic shape distribution of these early-type galaxies is strongly mass dependent: the typical short-to-long intrinsic axis ratio of high-mass early-type galaxies (>10{sup 11} M{sub Sun }) is 2:3, whereas atmore » masses below 10{sup 11} M{sub Sun} this ratio narrows to 1:3, or more flattened galaxies. In an entirely analogous manner, we select a high-redshift sample (0.6 < z < 0.8) from two deep-field surveys with multi-wavelength and Hubble Space Telescope/Advanced Camera for Surveys imaging: GEMS and COSMOS. We find a seemingly universal mass of {approx}10{sup 11} M{sub Sun} for highly flattened early-type systems at all redshifts. This implies that the process that grows an early-type galaxy above this ceiling mass, irrespective of cosmic epoch, involves forming round systems. Using both parametric and non-parametric tests, we find no evolution in the projected axis-ratio distribution for galaxies with masses >3 Multiplication-Sign 10{sup 10} M{sub Sun} with redshift. At the same time, our samples imply an increase of 2-3 Multiplication-Sign in comoving number density for early-type galaxies at masses >3 Multiplication-Sign 10{sup 10} M{sub Sun }, in agreement with previous studies. Given the direct connection between the axis-ratio distribution and the underlying bulge-to-disk ratio distribution, our findings imply that the number density evolution of early-type galaxies is not exclusively driven by the emergence of either bulge- or disk-dominated galaxies, but rather by a balanced mix that depends only on the stellar mass of the galaxy. The challenge for galaxy formation models is to reproduce this overall non-evolving ratio of flattened to round early-type galaxies in the context of a continually growing population.« less

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.

Reconstructing Star Formation Histories to Reveal the Origin and Evolution of the SFR-M* Correlation

NASA Astrophysics Data System (ADS)

Gawiser, Eric

2016-10-01

Correlations have played an important role in advancing our knowledge of astrophysics, from the Schmidt-Kennicutt law to the black hole-bulge mass relation. A surprisingly tight correlation between galaxy star formation rates (SFR) and stellar masses (M*) was discovered in 2007, and models of galaxy formation and evolution can be constrained by studying the evolution of this SFR-M* correlation and its intrinsic scatter. At present, such investigations are weakened by the need to assume a simple parametric form for the star formation history, typically constant or exponentially declining.We propose to use our new dense basis method to reconstruct star-formation histories (SFHs) through SED fitting using multi-band photometry of >10,000 galaxies in the 3D-HST and CANDELS catalogs. Armed with these reconstructed SFHs, we will then:1. Better measure the SFR-M* correlation (aka star-forming sequence) in several redshift bins at 0.5

Piezoelectrically driven vertical cavity acoustic transducers for the convective transport and rapid detection of DNA and protein binding to DNA microarrays with SPR imaging--a parametric study.

PubMed

Okabe, Yuka; Chen, Yulin; Purohit, Rishi; Corn, Robert M; Lee, Abraham P

2012-05-15

Mixing within the microdomain is limited because convective mixing cannot be achieved since diffusion dominates as the main form of transport. Hence microassays can take on the order of 1 to 72 h, without the aid of a passive or active mixer to shorten the time of transport of a target molecule to a probe (Lai et al., 2004). Liu et al. (2002, 2003) developed a low cost cavitation microstreaming based mixer which is easy to implement and use, but no comprehensive study has been done to optimize such a mixer for various applications. We present a study of the effects of various frequencies and cavity parameters on mixing using dye and surface based assays with protein, DNA, and nanoparticles to obtain an optimum mixing frequency and configuration for a wide range of assay applications. We present a novel method to monitor real time binding using surface plasmon resonance imaging (SPRI) coupled with a vertical cavity acoustic transducer (VCAT) micromixer for various biomolecule surface assays. The combination of VCAT and SPRI allows assay signal saturation within one minute while conserving reagent volume. The kinetic rate constant for adsorption (k(a)) and desorption (k(d)) as well as the limit of detection (LOD) of 5 nM for the DNA duplex formation are reported using this VCAT micromixer. Copyright © 2012 Elsevier B.V. All rights reserved.

Java Image I/O for VICAR, PDS, and ISIS

NASA Technical Reports Server (NTRS)

Deen, Robert G.; Levoe, Steven R.

2011-01-01

This library, written in Java, supports input and output of images and metadata (labels) in the VICAR, PDS image, and ISIS-2 and ISIS-3 file formats. Three levels of access exist. The first level comprises the low-level, direct access to the file. This allows an application to read and write specific image tiles, lines, or pixels and to manipulate the label data directly. This layer is analogous to the C-language "VICAR Run-Time Library" (RTL), which is the image I/O library for the (C/C++/Fortran) VICAR image processing system from JPL MIPL (Multimission Image Processing Lab). This low-level library can also be used to read and write labeled, uncompressed images stored in formats similar to VICAR, such as ISIS-2 and -3, and a subset of PDS (image format). The second level of access involves two codecs based on Java Advanced Imaging (JAI) to provide access to VICAR and PDS images in a file-format-independent manner. JAI is supplied by Sun Microsystems as an extension to desktop Java, and has a number of codecs for formats such as GIF, TIFF, JPEG, etc. Although Sun has deprecated the codec mechanism (replaced by IIO), it is still used in many places. The VICAR and PDS codecs allow any program written using the JAI codec spec to use VICAR or PDS images automatically, with no specific knowledge of the VICAR or PDS formats. Support for metadata (labels) is included, but is format-dependent. The PDS codec, when processing PDS images with an embedded VIAR label ("dual-labeled images," such as used for MER), presents the VICAR label in a new way that is compatible with the VICAR codec. The third level of access involves VICAR, PDS, and ISIS Image I/O plugins. The Java core includes an "Image I/O" (IIO) package that is similar in concept to the JAI codec, but is newer and more capable. Applications written to the IIO specification can use any image format for which a plug-in exists, with no specific knowledge of the format itself.

Model-independent and model-based local lensing properties of CL0024+1654 from multiply imaged galaxies

NASA Astrophysics Data System (ADS)

Wagner, Jenny; Liesenborgs, Jori; Tessore, Nicolas

2018-04-01

Context. Local gravitational lensing properties, such as convergence and shear, determined at the positions of multiply imaged background objects, yield valuable information on the smaller-scale lensing matter distribution in the central part of galaxy clusters. Highly distorted multiple images with resolved brightness features like the ones observed in CL0024 allow us to study these local lensing properties and to tighten the constraints on the properties of dark matter on sub-cluster scale. Aim. We investigate to what precision local magnification ratios, J, ratios of convergences, f, and reduced shears, g = (g1, g2), can be determined independently of a lens model for the five resolved multiple images of the source at zs = 1.675 in CL0024. We also determine if a comparison to the respective results obtained by the parametric modelling tool Lenstool and by the non-parametric modelling tool Grale can detect biases in the models. For these lens models, we analyse the influence of the number and location of the constraints from multiple images on the lens properties at the positions of the five multiple images of the source at zs = 1.675. Methods: Our model-independent approach uses a linear mapping between the five resolved multiple images to determine the magnification ratios, ratios of convergences, and reduced shears at their positions. With constraints from up to six multiple image systems, we generate Lenstool and Grale models using the same image positions, cosmological parameters, and number of generated convergence and shear maps to determine the local values of J, f, and g at the same positions across all methods. Results: All approaches show strong agreement on the local values of J, f, and g. We find that Lenstool obtains the tightest confidence bounds even for convergences around one using constraints from six multiple-image systems, while the best Grale model is generated only using constraints from all multiple images with resolved brightness features and adding limited small-scale mass corrections. Yet, confidence bounds as large as the values themselves can occur for convergences close to one in all approaches. Conclusions: Our results agree with previous findings, support the light-traces-mass assumption, and the merger hypothesis for CL0024. Comparing the different approaches can detect model biases. The model-independent approach determines the local lens properties to a comparable precision in less than one second.

Comparisons between conventional optical imaging and parametric indirect microscopic imaging on human skin detection

NASA Astrophysics Data System (ADS)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

We report a new method, polarization parameters indirect microscopic imaging with a high transmission infrared light source, to detect the morphology and component of human skin. A conventional reflection microscopic system is used as the basic optical system, into which a polarization-modulation mechanics is inserted and a high transmission infrared light source is utilized. The near-field structural characteristics of human skin can be delivered by infrared waves and material coupling. According to coupling and conduction physics, changes of the optical wave parameters can be calculated and curves of the intensity of the image can be obtained. By analyzing the near-field polarization parameters in nanoscale, we can finally get the inversion images of human skin. Compared with the conventional direct optical microscope, this method can break diffraction limit and achieve a super resolution of sub-100nm. Besides, the method is more sensitive to the edges, wrinkles, boundaries and impurity particles.

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Using deep learning in image hyper spectral segmentation, classification, and detection

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Su, Zhenyu

2018-02-01

Recent years have shown that deep learning neural networks are a valuable tool in the field of computer vision. Deep learning method can be used in applications like remote sensing such as Land cover Classification, Detection of Vehicle in Satellite Images, Hyper spectral Image classification. This paper addresses the use of the deep learning artificial neural network in Satellite image segmentation. Image segmentation plays an important role in image processing. The hue of the remote sensing image often has a large hue difference, which will result in the poor display of the images in the VR environment. Image segmentation is a pre processing technique applied to the original images and splits the image into many parts which have different hue to unify the color. Several computational models based on supervised, unsupervised, parametric, probabilistic region based image segmentation techniques have been proposed. Recently, one of the machine learning technique known as, deep learning with convolution neural network has been widely used for development of efficient and automatic image segmentation models. In this paper, we focus on study of deep neural convolution network and its variants for automatic image segmentation rather than traditional image segmentation strategies.

Drawing dynamical and parameters planes of iterative families and methods.

PubMed

Chicharro, Francisco I; Cordero, Alicia; Torregrosa, Juan R

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones).

Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

NASA Technical Reports Server (NTRS)

Amador, Jose J (Inventor)

2007-01-01

A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.

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.

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.

RLE (Research Laboratory of Electronics) Progress Report Number 125.

DTIC Science & Technology

1983-01-01

Optical Communications 32 7.3 Picosecond Optics 35 7.4 Ultrashort Pulse Formation 37 7.5 Femtosecond Laser System 37 7.6 Parametric Scattering with...Figure 3-2: The cross section for 4 photon ionization of atomic hydrogen as calculated by 10 Reinhardt for a single frequency laser . To facilitate...profiles produced by laser intensity I* and at five times that intensity 11 510. As the laser intensity is increased, the ionization profile becomes

Electrical resistivity imaging in transmission between surface and underground tunnel for fault characterization

NASA Astrophysics Data System (ADS)

Lesparre, N.; Boyle, A.; Grychtol, B.; Cabrera, J.; Marteau, J.; Adler, A.

2016-05-01

Electrical resistivity images supply information on sub-surface structures and are classically performed to characterize faults geometry. Here we use the presence of a tunnel intersecting a regional fault to inject electrical currents between surface and the tunnel to improve the image resolution at depth. We apply an original methodology for defining the inversion parametrization based on pilot points to better deal with the heterogeneous sounding of the medium. An increased region of high spatial resolution is shown by analysis of point spread functions as well as inversion of synthetics. Such evaluations highlight the advantages of using transmission measurements by transferring a few electrodes from the main profile to increase the sounding depth. Based on the resulting image we propose a revised structure for the medium surrounding the Cernon fault supported by geological observations and muon flux measurements.

77 FR 59692 - 2014 Diversity Immigrant Visa Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-28

... the E-DV system. The entry will not be accepted and must be resubmitted. Group or family photographs... must be in the Joint Photographic Experts Group (JPEG) format. Image File Size: The maximum file size...). Image File Format: The image must be in the Joint Photographic Experts Group (JPEG) format. Image File...

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.

Experiments in encoding multilevel images as quadtrees

NASA Technical Reports Server (NTRS)

Lansing, Donald L.

1987-01-01

Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.

K-edge ratio method for identification of multiple nanoparticulate contrast agents by spectral CT imaging

PubMed Central

Ghadiri, H; Ay, M R; Shiran, M B; Soltanian-Zadeh, H

2013-01-01

Objective: Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT. Methods: The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents. Results: We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used. Conclusion: The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents. Advances in knowledge: A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs. PMID:23934964

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

Iterative-Transform Phase Retrieval Using Adaptive Diversity

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

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.

Model-independent fit to Planck and BICEP2 data

NASA Astrophysics Data System (ADS)

Barranco, Laura; Boubekeur, Lotfi; Mena, Olga

2014-09-01

Inflation is the leading theory to describe elegantly the initial conditions that led to structure formation in our Universe. In this paper, we present a novel phenomenological fit to the Planck, WMAP polarization (WP) and the BICEP2 data sets using an alternative parametrization. Instead of starting from inflationary potentials and computing the inflationary observables, we use a phenomenological parametrization due to Mukhanov, describing inflation by an effective equation of state, in terms of the number of e-folds and two phenomenological parameters α and β. Within such a parametrization, which captures the different inflationary models in a model-independent way, the values of the scalar spectral index ns, its running and the tensor-to-scalar ratio r are predicted, given a set of parameters (α ,β). We perform a Markov Chain Monte Carlo analysis of these parameters, and we show that the combined analysis of Planck and WP data favors the Starobinsky and Higgs inflation scenarios. Assuming that the BICEP2 signal is not entirely due to foregrounds, the addition of this last data set prefers instead the ϕ2 chaotic models. The constraint we get from Planck and WP data alone on the derived tensor-to-scalar ratio is r <0.18 at 95% C.L., value which is consistent with the one quoted from the BICEP2 Collaboration analysis, r =0.16-0.05+0-06, after foreground subtraction. This is not necessarily at odds with the 2σ tension found between Planck and BICEP2 measurements when analyzing data in terms of the usual ns and r parameters, given that the parametrization used here, for the preferred value ns≃0.96, allows only for a restricted parameter space in the usual (ns,r) plane.

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

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

PubMed Central

Toure, Sory I.; Stow, Douglas A.; Weeks, John R.; Kumar, Sunil

2013-01-01

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

Non-Parametric Blur Map Regression for Depth of Field Extension.

PubMed

D'Andres, Laurent; Salvador, Jordi; Kochale, Axel; Susstrunk, Sabine

2016-04-01

Real camera systems have a limited depth of field (DOF) which may cause an image to be degraded due to visible misfocus or too shallow DOF. In this paper, we present a blind deblurring pipeline able to restore such images by slightly extending their DOF and recovering sharpness in regions slightly out of focus. To address this severely ill-posed problem, our algorithm relies first on the estimation of the spatially varying defocus blur. Drawing on local frequency image features, a machine learning approach based on the recently introduced regression tree fields is used to train a model able to regress a coherent defocus blur map of the image, labeling each pixel by the scale of a defocus point spread function. A non-blind spatially varying deblurring algorithm is then used to properly extend the DOF of the image. The good performance of our algorithm is assessed both quantitatively, using realistic ground truth data obtained with a novel approach based on a plenoptic camera, and qualitatively with real images.

CLASSIFYING MEDICAL IMAGES USING MORPHOLOGICAL APPEARANCE MANIFOLDS.

PubMed

Varol, Erdem; Gaonkar, Bilwaj; Davatzikos, Christos

2013-12-31

Input features for medical image classification algorithms are extracted from raw images using a series of pre processing steps. One common preprocessing step in computational neuroanatomy and functional brain mapping is the nonlinear registration of raw images to a common template space. Typically, the registration methods used are parametric and their output varies greatly with changes in parameters. Most results reported previously perform registration using a fixed parameter setting and use the results as input to the subsequent classification step. The variation in registration results due to choice of parameters thus translates to variation of performance of the classifiers that depend on the registration step for input. Analogous issues have been investigated in the computer vision literature, where image appearance varies with pose and illumination, thereby making classification vulnerable to these confounding parameters. The proposed methodology addresses this issue by sampling image appearances as registration parameters vary, and shows that better classification accuracies can be obtained this way, compared to the conventional approach.

Entanglement-seeded, dual, optical parametric amplification: Applications to quantum imaging and metrology

NASA Astrophysics Data System (ADS)

Glasser, Ryan T.; Cable, Hugo; Dowling, Jonathan P.; de Martini, Francesco; Sciarrino, Fabio; Vitelli, Chiara

2008-07-01

The study of optical parametric amplifiers (OPAs) has been successful in describing and creating nonclassical light for use in fields such as quantum metrology and quantum lithography [Agarwal , J. Opt. Soc. Am. B 24, 2 (2007)]. In this paper we present the theory of an OPA scheme utilizing an entangled state input. The scheme involves two identical OPAs seeded with the maximally path-entangled ∣N00N⟩ state (∣2,0⟩+∣0,2⟩)/2 . The stimulated amplification results in output state probability amplitudes that have a dependence on the number of photons in each mode, which differs greatly from two-mode squeezed vacuum. A large family of entangled output states are found. Specific output states allow for the heralded creation of N=4 N00N states, which may be used for quantum lithography, to write sub-Rayleigh fringe patterns, and for quantum interferometry, to achieve Heisenberg-limited phase measurement sensitivity.

Orbital angular momentum modes of high-gain parametric down-conversion

NASA Astrophysics Data System (ADS)

Beltran, Lina; Frascella, Gaetano; Perez, Angela M.; Fickler, Robert; Sharapova, Polina R.; Manceau, Mathieu; Tikhonova, Olga V.; Boyd, Robert W.; Leuchs, Gerd; Chekhova, Maria V.

2017-04-01

Light beams with orbital angular momentum (OAM) are convenient carriers of quantum information. They can also be used for imparting rotational motion to particles and providing high resolution in imaging. Due to the conservation of OAM in parametric down-conversion (PDC), signal and idler photons generated at low gain have perfectly anti-correlated OAM values. It is interesting to study the OAM properties of high-gain PDC, where the same OAM modes can be populated with large, but correlated, numbers of photons. Here we investigate the OAM spectrum of high-gain PDC and show that the OAM mode content can be controlled by varying the pump power and the configuration of the source. In our experiment, we use a source consisting of two nonlinear crystals separated by an air gap. We discuss the OAM properties of PDC radiation emitted by this source and suggest possible modifications.

Rapid prototyping and parametric optimization of plastic acoustofluidic devices for blood-bacteria separation.

PubMed

Silva, R; Dow, P; Dubay, R; Lissandrello, C; Holder, J; Densmore, D; Fiering, J

2017-09-01

Acoustic manipulation has emerged as a versatile method for microfluidic separation and concentration of particles and cells. Most recent demonstrations of the technology use piezoelectric actuators to excite resonant modes in silicon or glass microchannels. Here, we focus on acoustic manipulation in disposable, plastic microchannels in order to enable a low-cost processing tool for point-of-care diagnostics. Unfortunately, the performance of resonant acoustofluidic devices in plastic is hampered by a lack of a predictive model. In this paper, we build and test a plastic blood-bacteria separation device informed by a design of experiments approach, parametric rapid prototyping, and screening by image-processing. We demonstrate that the new device geometry can separate bacteria from blood while operating at 275% greater flow rate as well as reduce the power requirement by 82%, while maintaining equivalent separation performance and resolution when compared to the previously published plastic acoustofluidic separation device.

Bim from Laser SCANS… not Just for Buildings: Nurbs-Based Parametric Modeling of a Medieval Bridge

NASA Astrophysics Data System (ADS)

Barazzetti, L.; Banfi, F.; Brumana, R.; Previtali, M.; Roncoroni, F.

2016-06-01

Building Information Modelling is not limited to buildings. BIM technology includes civil infrastructures such as roads, dams, bridges, communications networks, water and wastewater networks and tunnels. This paper describes a novel methodology for the generation of a detailed BIM of a complex medieval bridge. The use of laser scans and images coupled with the development of algorithms able to handle irregular shapes allowed the creation of advanced parametric objects, which were assembled to obtain an accurate BIM. The lack of existing object libraries required the development of specific families for the different structural elements of the bridge. Finally, some applications aimed at assessing the stability and safety of the bridge are illustrated and discussed. The BIM of the bridge can incorporate this information towards a new "BIMonitoring" concept to preserve the geometric complexity provided by point clouds, obtaining a detailed BIM with object relationships and attributes.

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

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.

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.

Drawing Dynamical and Parameters Planes of Iterative Families and Methods

PubMed Central

Chicharro, Francisco I.

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones). PMID:24376386

Effects of Breast Cancer Chemotherapy Agents on Brain Activity in Rats: Functional Imaging Studies

DTIC Science & Technology

2011-04-29

and in a small region of the striatum. Visual stimulation produced bilateral activation of the superior colliculus, lateral geniculate and a small...pattern was seen in the lateral geniculate . These results demonstrate the feasibility of using brain activation by parametric sensory stimulation as...both the right and left lateral geniculate functional ROIs (25% and 29%, respectively). There were smaller but not statistically significant decreases

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.

Testing light-traces-mass in Hubble Frontier Fields Cluster MACS-J0416.1-2403

DOE PAGES

Sebesta, Kevin; Williams, Liliya L. R.; Mohammed, Irshad; ...

2016-06-17

Here, we reconstruct the projected mass distribution of a massive merging Hubble Frontier Fields cluster MACSJ0416 using the genetic algorithm based free-form technique called Grale. The reconstructions are constrained by 149 lensed images identified by Jauzac et al. using HFF data. No information about cluster galaxies or light is used, which makes our reconstruction unique in this regard. Using visual inspection of the maps, as well as galaxy-mass correlation functions we conclude that overall light does follow mass. Furthermore, the fact that brighter galaxies are more strongly clustered with mass is an important confirmation of the standard biasing scenario inmore » galaxy clusters. On the smallest scales, approximately less than a few arcseconds, the resolution afforded by 149 images is still not sufficient to confirm or rule out galaxy-mass offsets of the kind observed in ACO 3827. We also compare the mass maps of MACSJ0416 obtained by three different groups: Grale, and two parametric Lenstool reconstructions from the CATS and Sharon/Johnson teams. Overall, the three agree well; one interesting discrepancy between Grale and Lenstool galaxy-mass correlation functions occurs on scales of tens of kpc and may suggest that cluster galaxies are more biased tracers of mass than parametric methods generally assume.« less

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

PubMed

Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing

2013-01-01

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Testing light-traces-mass in Hubble Frontier Fields Cluster MACS-J0416.1-2403

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

Sebesta, Kevin; Williams, Liliya L. R.; Mohammed, Irshad

Here, we reconstruct the projected mass distribution of a massive merging Hubble Frontier Fields cluster MACSJ0416 using the genetic algorithm based free-form technique called Grale. The reconstructions are constrained by 149 lensed images identified by Jauzac et al. using HFF data. No information about cluster galaxies or light is used, which makes our reconstruction unique in this regard. Using visual inspection of the maps, as well as galaxy-mass correlation functions we conclude that overall light does follow mass. Furthermore, the fact that brighter galaxies are more strongly clustered with mass is an important confirmation of the standard biasing scenario inmore » galaxy clusters. On the smallest scales, approximately less than a few arcseconds, the resolution afforded by 149 images is still not sufficient to confirm or rule out galaxy-mass offsets of the kind observed in ACO 3827. We also compare the mass maps of MACSJ0416 obtained by three different groups: Grale, and two parametric Lenstool reconstructions from the CATS and Sharon/Johnson teams. Overall, the three agree well; one interesting discrepancy between Grale and Lenstool galaxy-mass correlation functions occurs on scales of tens of kpc and may suggest that cluster galaxies are more biased tracers of mass than parametric methods generally assume.« less

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.

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.

78 FR 59743 - Bureau of Consular Affairs; Registration for the Diversity Immigrant (DV-2015) Visa Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-27

... already a U.S. citizen or a Lawful Permanent Resident, but you will not be penalized if you do. Group... specifications: Image File Format: The miage must be in the Joint Photographic Experts Group (JPEG) format. Image... in the Joint Photographic Experts Group (JPEG) format. Image File Size: The maximum image file size...

Aging in deep gray matter and white matter revealed by diffusional kurtosis imaging.

PubMed

Gong, Nan-Jie; Wong, Chun-Sing; Chan, Chun-Chung; Leung, Lam-Ming; Chu, Yiu-Ching

2014-10-01

Diffusion tensor imaging has already been extensively used to probe microstructural alterations in white matter tracts, and scarcely, in deep gray matter. However, results in literature regarding age-related degenerative mechanisms in white matter tracts and parametric changes in the putamen are inconsistent. Diffusional kurtosis imaging is a mathematical extension of diffusion tensor imaging, which could more comprehensively mirror microstructure, particularly in isotropic tissues such as gray matter. In this study, we used the diffusional kurtosis imaging method and a white-matter model that provided metrics of explicit neurobiological interpretations in healthy participants (58 in total, aged from 25 to 84 years). Tract-based whole-brain analyses and regions-of-interest (anterior and posterior limbs of the internal capsule, cerebral peduncle, fornix, genu and splenium of corpus callosum, globus pallidus, substantia nigra, red nucleus, putamen, caudate nucleus, and thalamus) analyses were performed to examine parametric differences across regions and correlations with age. In white matter tracts, evidence was found supportive for anterior-posterior gradient and not completely supportive for retrogenesis theory. Age-related degenerations appeared to be broadly driven by axonal loss. Demyelination may also be a major driving mechanism, although confined to the anterior brain. In terms of deep gray matter, higher mean kurtosis and fractional anisotropy in the globus pallidus, substantia nigra, and red nucleus reflected higher microstructural complexity and directionality compared with the putamen, caudate nucleus, and thalamus. In particular, the unique age-related positive correlations for fractional anisotropy, mean kurtosis, and radial kurtosis in the putamen opposite to those in other regions call for further investigation of exact underlying mechanisms. In summary, the results suggested that diffusional kurtosis can provide measurements in a new dimension that were complementary to diffusivity metrics. Kurtosis together with diffusivity can more comprehensively characterize microstructural compositions and age-related changes than diffusivity alone. Combined with proper model, it may also assist in providing neurobiological interpretations of the identified alterations. Copyright © 2014 Elsevier Inc. All rights reserved.

Design and Characterization of a Three-Dimensional Positron Annihilation Spectroscopy System Using a Low-Energy Positron Beam

DTIC Science & Technology

2012-03-22

66 Appendix A. PHDs Imager Software Data Format Comparison...57 4. Imager Raw Energy Event Data Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 5. Imager...Energy Filtered Event Data Format . . . . . . . . . . . . . . . . . . . . . . . . 70 6. Water Cooling Estimates Assuming 22◦C Water

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

A parametric study of various synthetic aperture telescope configurations for coherent imaging applications

NASA Technical Reports Server (NTRS)

Harvey, James E.; Wissinger, Alan B.; Bunner, Alan N.

1986-01-01

The comparative advantages of synthetic aperture telescopes (SATs) of segmented primary mirror and common secondary mirror type, on the one hand, and on the other those employing an array of independent telescopes, are discussed. The diffraction-limited optical performance of both redundant and nonredundant subaperture configurations are compared in terms of point spread function characteristics and encircled energy plots. Coherent imaging with afocal telescope SATs involves a pupil-mapping operation followed by a Fourier transform one. A quantitative analysis of the off-axis optical performance degradation due to pupil-mapping errors is presented, together with the field-dependent effects of residual design aberrations of independent telescopes.

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

High energy-density liquid rocket fuel performance

NASA Technical Reports Server (NTRS)

Rapp, Douglas C.

1990-01-01

A fuel performance database of liquid hydrocarbons and aluminum-hydrocarbon fuels was compiled using engine parametrics from the Space Transportation Engine Program as a baseline. Propellant performance parameters are introduced. General hydrocarbon fuel performance trends are discussed with respect to hydrogen-to-carbon ratio and heat of formation. Aluminum-hydrocarbon fuel performance is discussed with respect to aluminum metal loading. Hydrocarbon and aluminum-hydrocarbon fuel performance is presented with respect to fuel density, specific impulse, and propellant density specific impulse.

Research Laboratory of Electronics Annual Report Number 125.

DTIC Science & Technology

1983-01-01

Picosecond Optics 35 7.4 Ultrashort Pulse Formation 37 7.5 Ferntosecond Laser System 37 7.6 Parametric Scattering with Femtosecond Pulses 38 7.7 Near-IR...ionization of atomic hydrogen as calculated by 10 Reinhardt for a single frequency laser . To facilitate comparison, the cross section has been divided by 13...As the intensity increases, the peaks shift to the blue and become broader. Figure 3-3: Ionization profiles produced by laser intensity 10 and at five

On the Chaotic Vibrations of Electrostatically Actuated Arch Micro/Nano Resonators: A Parametric Study

NASA Astrophysics Data System (ADS)

Tajaddodianfar, Farid; Hairi Yazdi, Mohammad Reza; Pishkenari, Hossein Nejat

Motivated by specific applications, electrostatically actuated bistable arch shaped micro-nano resonators have attracted growing attention in the research community in recent years. Nevertheless, some issues relating to their nonlinear dynamics, including the possibility of chaos, are still not well known. In this paper, we investigate the chaotic vibrations of a bistable resonator comprised of a double clamped initially curved microbeam under combined harmonic AC and static DC distributed electrostatic actuation. A reduced order equation obtained by the application of the Galerkin method to the nonlinear partial differential equation of motion, given in the framework of Euler-Bernoulli beam theory, is used for the investigation in this paper. We numerically integrate the obtained equation to study the chaotic vibrations of the proposed system. Moreover, we investigate the effects of various parameters including the arch curvature, the actuation parameters and the quality factor of the resonator, which are effective in the formation of both static and dynamic behaviors of the system. Using appropriate numerical tools, including Poincaré maps, bifurcation diagrams, Fourier spectrum and Lyapunov exponents we scrutinize the effects of various parameters on the formation of chaotic regions in the parametric space of the resonator. Results of this work provide better insight into the problem of nonlinear dynamics of the investigated family of bistable micro/nano resonators, and facilitate the design of arch resonators for applications such as filters.

Reporting requirements for skeletal digital radiography: comparison of soft-copy and hard-copy presentation.

PubMed

O'Connor, P J; Davies, A G; Fowler, R C; Lintott, D J; Bury, R F; Parkin, G J; Martinez, D; Saifuddin, A; Cowen, A R

1998-04-01

To assess diagnostic performance and reader preference when reporting results from digital hard-copy and two soft-copy formats of skeletal digital radiography. The data comprised hand radiographs of patients undergoing renal dialysis. Normal hand radiographs obtained in trauma patients were assessed as control images. One hundred fifteen images acquired with a photostimulable-phosphor computed radiography system were analyzed. Image selection and initial assessment were by consensus of two experienced radiologists, who graded the radiographic changes of hyperparathyroidism with the Ritz scoring system. The images were then presented to four readers in three formats: hard-copy output and soft-copy presentations at 2K2 and 1K2 resolutions. These readers scored pathologic change and image preference. The results were analyzed with the receiver operating characteristic technique. There was a significant improvement in diagnostic performance for both soft-copy formats relative to the hard-copy format (P < .001). No significant difference in diagnostic performance was found between the two soft-copy formats. There was a significant preference for both soft-copy formats relative to the hard-copy format (P < .01), with the 2K2 soft-copy images preferred to the 1K2 images (P < .01). Soft-copy reporting can provide superior diagnostic performance even for images viewed at a modest (1K2) resolution. The lack of difference between the two soft-copy formats has important economic implications with respect to departmental hardware requirements.

Simbol-X Formation Flight and Image Reconstruction

NASA Astrophysics Data System (ADS)

Civitani, M.; Djalal, S.; Le Duigou, J. M.; La Marle, O.; Chipaux, R.

2009-05-01

Simbol-X is the first operational mission relying on two satellites flying in formation. The dynamics of the telescope, due to the formation flight concept, raises a variety of problematic, like image reconstruction, that can be better evaluated via a simulation tools. We present here the first results obtained with Simulos, simulation tool aimed to study the relative spacecrafts navigation and the weight of the different parameters in image reconstruction and telescope performance evaluation. The simulation relies on attitude and formation flight sensors models, formation flight dynamics and control, mirror model and focal plane model, while the image reconstruction is based on the Line of Sight (LOS) concept.

Advanced imaging techniques in brain tumors

PubMed Central

2009-01-01

Abstract Perfusion, permeability and magnetic resonance spectroscopy (MRS) are now widely used in the research and clinical settings. In the clinical setting, qualitative, semi-quantitative and quantitative approaches such as review of color-coded maps to region of interest analysis and analysis of signal intensity curves are being applied in practice. There are several pitfalls with all of these approaches. Some of these shortcomings are reviewed, such as the relative low sensitivity of metabolite ratios from MRS and the effect of leakage on the appearance of color-coded maps from dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging and what correction and normalization methods can be applied. Combining and applying these different imaging techniques in a multi-parametric algorithmic fashion in the clinical setting can be shown to increase diagnostic specificity and confidence. PMID:19965287

Aircraft geometry verification with enhanced computer generated displays

NASA Technical Reports Server (NTRS)

Cozzolongo, J. V.

1982-01-01

A method for visual verification of aerodynamic geometries using computer generated, color shaded images is described. The mathematical models representing aircraft geometries are created for use in theoretical aerodynamic analyses and in computer aided manufacturing. The aerodynamic shapes are defined using parametric bi-cubic splined patches. This mathematical representation is then used as input to an algorithm that generates a color shaded image of the geometry. A discussion of the techniques used in the mathematical representation of the geometry and in the rendering of the color shaded display is presented. The results include examples of color shaded displays, which are contrasted with wire frame type displays. The examples also show the use of mapped surface pressures in terms of color shaded images of V/STOL fighter/attack aircraft and advanced turboprop aircraft.

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

(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.

CLASH-VLT: A highly precise strong lensing model of the galaxy cluster RXC J2248.7-4431 (Abell S1063) and prospects for cosmography

NASA Astrophysics Data System (ADS)

Caminha, G. B.; Grillo, C.; Rosati, P.; Balestra, I.; Karman, W.; Lombardi, M.; Mercurio, A.; Nonino, M.; Tozzi, P.; Zitrin, A.; Biviano, A.; Girardi, M.; Koekemoer, A. M.; Melchior, P.; Meneghetti, M.; Munari, E.; Suyu, S. H.; Umetsu, K.; Annunziatella, M.; Borgani, S.; Broadhurst, T.; Caputi, K. I.; Coe, D.; Delgado-Correal, C.; Ettori, S.; Fritz, A.; Frye, B.; Gobat, R.; Maier, C.; Monna, A.; Postman, M.; Sartoris, B.; Seitz, S.; Vanzella, E.; Ziegler, B.

2016-03-01

Aims: We perform a comprehensive study of the total mass distribution of the galaxy cluster RXC J2248.7-4431 (z = 0.348) with a set of high-precision strong lensing models, which take advantage of extensive spectroscopic information on many multiply lensed systems. In the effort to understand and quantify inherent systematics in parametric strong lensing modelling, we explore a collection of 22 models in which we use different samples of multiple image families, different parametrizations of the mass distribution and cosmological parameters. Methods: As input information for the strong lensing models, we use the Cluster Lensing And Supernova survey with Hubble (CLASH) imaging data and spectroscopic follow-up observations, with the VIsible Multi-Object Spectrograph (VIMOS) and Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT), to identify and characterize bona fide multiple image families and measure their redshifts down to mF814W ≃ 26. A total of 16 background sources, over the redshift range 1.0-6.1, are multiply lensed into 47 images, 24 of which are spectroscopically confirmed and belong to ten individual sources. These also include a multiply lensed Lyman-α blob at z = 3.118. The cluster total mass distribution and underlying cosmology in the models are optimized by matching the observed positions of the multiple images on the lens plane. Bayesian Markov chain Monte Carlo techniques are used to quantify errors and covariances of the best-fit parameters. Results: We show that with a careful selection of a large sample of spectroscopically confirmed multiple images, the best-fit model can reproduce their observed positions with a rms scatter of 0.̋3 in a fixed flat ΛCDM cosmology, whereas the lack of spectroscopic information or the use of inaccurate photometric redshifts can lead to biases in the values of the model parameters. We find that the best-fit parametrization for the cluster total mass distribution is composed of an elliptical pseudo-isothermal mass distribution with a significant core for the overall cluster halo and truncated pseudo-isothermal mass profiles for the cluster galaxies. We show that by adding bona fide photometric-selected multiple images to the sample of spectroscopic families, one can slightly improve constraints on the model parameters. In particular, we find that the degeneracy between the lens total mass distribution and the underlying geometry of the Universe, which is probed via angular diameter distance ratios between the lens and sources and the observer and sources, can be partially removed. Allowing cosmological parameters to vary together with the cluster parameters, we find (at 68% confidence level) Ωm = 0.25+ 0.13-0.16 and w = -1.07+ 0.16-0.42 for a flat ΛCDM model, and Ωm = 0.31+ 0.12-0.13 and ΩΛ = 0.38+ 0.38-0.27 for a Universe with w = -1 and free curvature. Finally, using toy models mimicking the overall configuration of multiple images and cluster total mass distribution, we estimate the impact of the line-of-sight mass structure on the positional rms to be 0.̋3 ± 0. We argue that the apparent sensitivity of our lensing model to cosmography is due to the combination of the regular potential shape of RXC J2248, a large number of bona fide multiple images out to z = 6.1, and a relatively modest presence of intervening large-scale structure, as revealed by our spectroscopic survey.

Disjunctive Normal Shape and Appearance Priors with Applications to Image Segmentation.

PubMed

Mesadi, Fitsum; Cetin, Mujdat; Tasdizen, Tolga

2015-10-01

The use of appearance and shape priors in image segmentation is known to improve accuracy; however, existing techniques have several drawbacks. Active shape and appearance models require landmark points and assume unimodal shape and appearance distributions. Level set based shape priors are limited to global shape similarity. In this paper, we present a novel shape and appearance priors for image segmentation based on an implicit parametric shape representation called disjunctive normal shape model (DNSM). DNSM is formed by disjunction of conjunctions of half-spaces defined by discriminants. We learn shape and appearance statistics at varying spatial scales using nonparametric density estimation. Our method can generate a rich set of shape variations by locally combining training shapes. Additionally, by studying the intensity and texture statistics around each discriminant of our shape model, we construct a local appearance probability map. Experiments carried out on both medical and natural image datasets show the potential of the proposed method.

Clinical feasibility study of combined opto-acoustic and ultrasonic imaging modality providing coregistered functional and anatomical maps of breast tumors

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Smith, Remie J.; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Ermilov, Sergey; Conjusteau, André; Tsyboulski, Dmitri; Oraevsky, Alexander A.; Kist, Kenneth; Dornbluth, N. C.; Otto, Pamela

2013-03-01

We report on findings from the clinical feasibility study of the ImagioTM. Breast Imaging System, which acquires two-dimensional opto-acoustic (OA) images co-registered with conventional ultrasound using a specialized duplex hand-held probe. Dual-wavelength opto-acoustic technology is used to generate parametric maps based upon total hemoglobin and its oxygen saturation in breast tissues. This may provide functional diagnostic information pertaining to tumor metabolism and microvasculature, which is complementary to morphological information obtained with conventional gray-scale ultrasound. We present co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical feasibility study. The clinical results illustrate that the technology may have the capability to improve the efficacy of breast tumor diagnosis. In doing so, it may have the potential to reduce biopsies and to characterize cancers that were not seen well with conventional gray-scale ultrasound alone.

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.

Image-Based Reverse Engineering and Visual Prototyping of Woven Cloth.

PubMed

Schroder, Kai; Zinke, Arno; Klein, Reinhard

2015-02-01

Realistic visualization of cloth has many applications in computer graphics. An ongoing research problem is how to best represent and capture cloth models, specifically when considering computer aided design of cloth. Previous methods produce highly realistic images, however, they are either difficult to edit or require the measurement of large databases to capture all variations of a cloth sample. We propose a pipeline to reverse engineer cloth and estimate a parametrized cloth model from a single image. We introduce a geometric yarn model, integrating state-of-the-art textile research. We present an automatic analysis approach to estimate yarn paths, yarn widths, their variation and a weave pattern. Several examples demonstrate that we are able to model the appearance of the original cloth sample. Properties derived from the input image give a physically plausible basis that is fully editable using a few intuitive parameters.

Regularization Reconstruction Method for Imaging Problems in Electrical Capacitance Tomography

NASA Astrophysics Data System (ADS)

Chu, Pan; Lei, Jing

2017-11-01

The electrical capacitance tomography (ECT) is deemed to be a powerful visualization measurement technique for the parametric measurement in a multiphase flow system. The inversion task in the ECT technology is an ill-posed inverse problem, and seeking for an efficient numerical method to improve the precision of the reconstruction images is important for practical measurements. By the introduction of the Tikhonov regularization (TR) methodology, in this paper a loss function that emphasizes the robustness of the estimation and the low rank property of the imaging targets is put forward to convert the solution of the inverse problem in the ECT reconstruction task into a minimization problem. Inspired by the split Bregman (SB) algorithm, an iteration scheme is developed for solving the proposed loss function. Numerical experiment results validate that the proposed inversion method not only reconstructs the fine structures of the imaging targets, but also improves the robustness.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Young star clusters in nearby molecular clouds

NASA Astrophysics Data System (ADS)

Getman, K. V.; Kuhn, M. A.; Feigelson, E. D.; Broos, P. S.; Bate, M. R.; Garmire, G. P.

2018-06-01

The SFiNCs (Star Formation in Nearby Clouds) project is an X-ray/infrared study of the young stellar populations in 22 star-forming regions with distances ≲ 1 kpc designed to extend our earlier MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) survey of more distant clusters. Our central goal is to give empirical constraints on cluster formation mechanisms. Using parametric mixture models applied homogeneously to the catalogue of SFiNCs young stars, we identify 52 SFiNCs clusters and 19 unclustered stellar structures. The procedure gives cluster properties including location, population, morphology, association with molecular clouds, absorption, age (AgeJX), and infrared spectral energy distribution (SED) slope. Absorption, SED slope, and AgeJX are age indicators. SFiNCs clusters are examined individually, and collectively with MYStIX clusters, to give the following results. (1) SFiNCs is dominated by smaller, younger, and more heavily obscured clusters than MYStIX. (2) SFiNCs cloud-associated clusters have the high ellipticities aligned with their host molecular filaments indicating morphology inherited from their parental clouds. (3) The effect of cluster expansion is evident from the radius-age, radius-absorption, and radius-SED correlations. Core radii increase dramatically from ˜0.08 to ˜0.9 pc over the age range 1-3.5 Myr. Inferred gas removal time-scales are longer than 1 Myr. (4) Rich, spatially distributed stellar populations are present in SFiNCs clouds representing early generations of star formation. An appendix compares the performance of the mixture models and non-parametric minimum spanning tree to identify clusters. This work is a foundation for future SFiNCs/MYStIX studies including disc longevity, age gradients, and dynamical modelling.

Data Sets and Data Services at the Northern California Earthquake Data Center

NASA Astrophysics Data System (ADS)

Neuhauser, D. S.; Zuzlewski, S.; Allen, R. M.

2014-12-01

The Northern California Earthquake Data Center (NCEDC) houses a unique and comprehensive data archive and provides real-time services for a variety of seismological and geophysical data sets that encompass northern and central California. We have over 80 terabytes of continuous and event-based time series data from broadband, short-period, strong motion, and strain sensors as well as continuous and campaign GPS data at both standard and high sample rates in both raw and RINEX format. The Northen California Seismic System (NCSS), operated by UC Berkeley and USGS Menlo Park, has recorded over 890,000 events from 1984 to the present, and the NCEDC provides catalog, parametric information, moment tensors and first motion mechanisms, and time series data for these events. We also host and provide event catalogs, parametric information, and event waveforms for DOE enhanced geothermal system monitoring in northern California and Nevada. The NCEDC provides a variety of ways for users to access these data. The most recent development are web services, which provide interactive, command-line, or program-based workflow access to data. Web services use well-established server and client protocols and RESTful software architecture that allow users to easily submit queries and receive the requested data in real-time rather than through batch or email-based requests. Data are returned to the user in the appropriate format such as XML, RESP, simple text, or MiniSEED depending on the service and selected output format. The NCEDC supports all FDSN-defined web services as well as a number of IRIS-defined and NCEDC-defined services. We also continue to support older email-based and browser-based access to data. NCEDC data and web services can be found at http://www.ncedc.org and http://service.ncedc.org.

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.

Lossless data embedding for all image formats

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav; Du, Rui

2002-04-01

Lossless data embedding has the property that the distortion due to embedding can be completely removed from the watermarked image without accessing any side channel. This can be a very important property whenever serious concerns over the image quality and artifacts visibility arise, such as for medical images, due to legal reasons, for military images or images used as evidence in court that may be viewed after enhancement and zooming. We formulate two general methodologies for lossless embedding that can be applied to images as well as any other digital objects, including video, audio, and other structures with redundancy. We use the general principles as guidelines for designing efficient, simple, and high-capacity lossless embedding methods for three most common image format paradigms - raw, uncompressed formats (BMP), lossy or transform formats (JPEG), and palette formats (GIF, PNG). We close the paper with examples of how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of non-trivial tasks, including elegant lossless authentication using fragile watermarks. Note on terminology: some authors coined the terms erasable, removable, reversible, invertible, and distortion-free for the same concept.

Metadata requirements for results of diagnostic imaging procedures: a BIIF profile to support user applications

NASA Astrophysics Data System (ADS)

Brown, Nicholas J.; Lloyd, David S.; Reynolds, Melvin I.; Plummer, David L.

2002-05-01

A visible digital image is rendered from a set of digital image data. Medical digital image data can be stored as either: (a) pre-rendered format, corresponding to a photographic print, or (b) un-rendered format, corresponding to a photographic negative. The appropriate image data storage format and associated header data (metadata) required by a user of the results of a diagnostic procedure recorded electronically depends on the task(s) to be performed. The DICOM standard provides a rich set of metadata that supports the needs of complex applications. Many end user applications, such as simple report text viewing and display of a selected image, are not so demanding and generic image formats such as JPEG are sometimes used. However, these are lacking some basic identification requirements. In this paper we make specific proposals for minimal extensions to generic image metadata of value in various domains, which enable safe use in the case of two simple healthcare end user scenarios: (a) viewing of text and a selected JPEG image activated by a hyperlink and (b) viewing of one or more JPEG images together with superimposed text and graphics annotation using a file specified by a profile of the ISO/IEC Basic Image Interchange Format (BIIF).

A label-free immunoassay for Flavivirus detection by the Reflective Phantom Interface technology.

PubMed

Tagliabue, Giovanni; Faoro, Valentina; Rizzo, Serena; Sblattero, Daniele; Saccani, Andrea; Riccio, Gabriele; Bellini, Tommaso; Salina, Matteo; Buscaglia, Marco; Marcello, Alessandro

2017-10-28

Flaviviruses are widespread and cause clinically relevant arboviral diseases that impact locally and as imported travel-related infections. Direct detection of viraemia is limited, being typically undetectable at onset of symptoms. Therefore, diagnosis is primarily based on serology, which is complicated by high cross-reactivity across different species. The overlapping geographical distribution of the vectors in areas with a weak healthcare system, the increase of international travel and the similarity of symptoms highlight the need for rapid and reliable multi-parametric diagnostic tests in point-of-care formats. To this end we developed a bi-parametric serological microarray using recombinant NS1 proteins from Tick-borne encephalitis virus and West Nile virus coupled to a low-cost, label-free detection device based on the Reflective Phantom Interface (RPI) principle. Specific sequential detection of antibodies in solution demonstrates the feasibility of the approach for the surveillance and diagnosis of Flaviviruses. Copyright © 2017 Elsevier Inc. All rights reserved.

Dual-quaternion based fault-tolerant control for spacecraft formation flying with finite-time convergence.

PubMed

Dong, Hongyang; Hu, Qinglei; Ma, Guangfu

2016-03-01

Study results of developing control system for spacecraft formation proximity operations between a target and a chaser are presented. In particular, a coupled model using dual quaternion is employed to describe the proximity problem of spacecraft formation, and a nonlinear adaptive fault-tolerant feedback control law is developed to enable the chaser spacecraft to track the position and attitude of the target even though its actuator occurs fault. Multiple-task capability of the proposed control system is further demonstrated in the presence of disturbances and parametric uncertainties as well. In addition, the practical finite-time stability feature of the closed-loop system is guaranteed theoretically under the designed control law. Numerical simulation of the proposed method is presented to demonstrate the advantages with respect to interference suppression, fast tracking, fault tolerant and practical finite-time stability. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Improved modification for the density-functional theory calculation of thermodynamic properties for C-H-O composite compounds.

PubMed

Liu, Min Hsien; Chen, Cheng; Hong, Yaw Shun

2005-02-08

A three-parametric modification equation and the least-squares approach are adopted to calibrating hybrid density-functional theory energies of C(1)-C(10) straight-chain aldehydes, alcohols, and alkoxides to accurate enthalpies of formation DeltaH(f) and Gibbs free energies of formation DeltaG(f), respectively. All calculated energies of the C-H-O composite compounds were obtained based on B3LYP6-311++G(3df,2pd) single-point energies and the related thermal corrections of B3LYP6-31G(d,p) optimized geometries. This investigation revealed that all compounds had 0.05% average absolute relative error (ARE) for the atomization energies, with mean value of absolute error (MAE) of just 2.1 kJ/mol (0.5 kcal/mol) for the DeltaH(f) and 2.4 kJ/mol (0.6 kcal/mol) for the DeltaG(f) of formation.

Scaling images using their background ratio. An application in statistical comparisons of images.

PubMed

Kalemis, A; Binnie, D; Bailey, D L; Flower, M A; Ott, R J

2003-06-07

Comparison of two medical images often requires image scaling as a pre-processing step. This is usually done with the scaling-to-the-mean or scaling-to-the-maximum techniques which, under certain circumstances, in quantitative applications may contribute a significant amount of bias. In this paper, we present a simple scaling method which assumes only that the most predominant values in the corresponding images belong to their background structure. The ratio of the two images to be compared is calculated and its frequency histogram is plotted. The scaling factor is given by the position of the peak in this histogram which belongs to the background structure. The method was tested against the traditional scaling-to-the-mean technique on simulated planar gamma-camera images which were compared using pixelwise statistical parametric tests. Both sensitivity and specificity for each condition were measured over a range of different contrasts and sizes of inhomogeneity for the two scaling techniques. The new method was found to preserve sensitivity in all cases while the traditional technique resulted in significant degradation of sensitivity in certain cases.

Method for Separation of Blood Vessels on the Three-Color Images of Biological Tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2017-07-01

A new technology was developed to improve the visibility of blood vessels on images of tissues of hollow human organs(the alimentary tract and respiratory system) based on the relation between the color components of the image, the scattering properties of the tissue, and its hemoglobin content. A statistical operator was presented to convert the three-color image of the tissue into a parametric map objectively characterizing the concentration of hemoglobin in the tissue regardless of the illumination and shooting conditions. An algorithm for obtaining conversion parameters for image systems with known spectral characteristics was presented. An image of a multilayer multiple-scattering medium modeling bronchial tissue was synthesized and was used to evaluate the efficiency of the proposed conversion system. It was shown that the conversion made it possible to increase the contrast of the blood vessels by almost two orders of magnitude, to significantly improve the clarity of the display of their borders, and to eliminate almost completely the influence of background and nonuniform illumination of the medium in comparison with the original image.

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.

Sci—Fri PM: Topics — 06: The influence of regional dose sensitivity on salivary loss and recovery in the parotid gland

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

Clark, H; BC Cancer Agency, Surrey, B.C.; BC Cancer Agency, Vancouver, B.C.

Purpose: The Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC 2010) survey of radiation dose-volume effects on salivary gland function has called for improved understanding of intragland dose sensitivity and the effectiveness of partial sparing in salivary glands. Regional dose susceptibility of sagittally- and coronally-sub-segmented parotid gland has been studied. Specifically, we examine whether individual consideration of sub-segments leads to improved prediction of xerostomia compared with whole parotid mean dose. Methods: Data from 102 patients treated for head-and-neck cancers at the BC Cancer Agency were used in this study. Whole mouth stimulated saliva was collected before (baseline), threemore » months, and one year after cessation of radiotherapy. Organ volumes were contoured using treatment planning CT images and sub-segmented into regional portions. Both non-parametric (local regression) and parametric (mean dose exponential fitting) methods were employed. A bootstrap technique was used for reliability estimation and cross-comparison. Results: Salivary loss is described well using non-parametric and mean dose models. Parametric fits suggest a significant distinction in dose response between medial-lateral and anterior-posterior aspects of the parotid (p<0.01). Least-squares and least-median squares estimates differ significantly (p<0.00001), indicating fits may be skewed by noise or outliers. Salivary recovery exhibits a weakly arched dose response: the highest recovery is seen at intermediate doses. Conclusions: Salivary function loss is strongly dose dependent. In contrast no useful dose dependence was observed for function recovery. Regional dose dependence was observed, but may have resulted from a bias in dose distributions.« less

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.

Non-parametric combination and related permutation tests for neuroimaging.

PubMed

Winkler, Anderson M; Webster, Matthew A; Brooks, Jonathan C; Tracey, Irene; Smith, Stephen M; Nichols, Thomas E

2016-04-01

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Intravoxel Incoherent Motion MR Imaging in the Differentiation of Benign and Malignant Sinonasal Lesions: Comparison with Conventional Diffusion-Weighted MR Imaging.

PubMed

Xiao, Z; Tang, Z; Qiang, J; Wang, S; Qian, W; Zhong, Y; Wang, R; Wang, J; Wu, L; Tang, W; Zhang, Z

2018-01-25

Intravoxel incoherent motion is a promising method for the differentiation of sinonasal lesions. This study aimed to evaluate the value of intravoxel incoherent motion in the differentiation of benign and malignant sinonasal lesions and to compare the diagnostic performance of intravoxel incoherent motion with that of conventional DWI. One hundred thirty-one patients with histologically proved solid sinonasal lesions (56 benign and 75 malignant) who underwent conventional DWI and intravoxel incoherent motion were recruited in this study. The diffusion coefficient ( D ), pseudodiffusion coefficient ( D *), and perfusion fraction ( f ) values derived from intravoxel incoherent motion and ADC values derived from conventional DWI were measured and compared between the 2 groups using the Student t test. Receiver operating characteristic curve analysis, logistic regression analysis, and 10-fold cross-validation were performed to evaluate the diagnostic performance of single-parametric and multiparametric models. The mean ADC and D values were significantly lower in malignant sinonasal lesions than in benign sinonasal lesions (both P < .001). The mean f value was higher in malignant lesions than in benign lesions ( P = .003). Multiparametric models can significantly improve the cross-validated areas under the curve for the differentiation of sinonasal lesions compared with single-parametric models (all corrected P < .05 except the D value). The model of D + f provided a better diagnostic performance than the ADC value (corrected P < .001). Intravoxel incoherent motion appears to be a more effective MR imaging technique than conventional DWI in the differentiation of benign and malignant sinonasal lesions. © 2018 by American Journal of Neuroradiology.