Geodesic regression for image time-series.

PubMed

Niethammer, Marc; Huang, Yang; Vialard, François-Xavier

2011-01-01

Registration of image-time series has so far been accomplished (i) by concatenating registrations between image pairs, (ii) by solving a joint estimation problem resulting in piecewise geodesic paths between image pairs, (iii) by kernel based local averaging or (iv) by augmenting the joint estimation with additional temporal irregularity penalties. Here, we propose a generative model extending least squares linear regression to the space of images by using a second-order dynamic formulation for image registration. Unlike previous approaches, the formulation allows for a compact representation of an approximation to the full spatio-temporal trajectory through its initial values. The method also opens up possibilities to design image-based approximation algorithms. The resulting optimization problem is solved using an adjoint method.

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

NASA Astrophysics Data System (ADS)

Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

Using dynamic interferometric synthetic aperature radar (InSAR) to image fast-moving surface waves

DOEpatents

Vincent, Paul

2005-06-28

A new differential technique and system for imaging dynamic (fast moving) surface waves using Dynamic Interferometric Synthetic Aperture Radar (InSAR) is introduced. This differential technique and system can sample the fast-moving surface displacement waves from a plurality of moving platform positions in either a repeat-pass single-antenna or a single-pass mode having a single-antenna dual-phase receiver or having dual physically separate antennas, and reconstruct a plurality of phase differentials from a plurality of platform positions to produce a series of desired interferometric images of the fast moving waves.

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames. Experimental results show that the improved automatic threshold processing has special application value for the recognition of dynamic target with low contrast.

Local contrast-enhanced MR images via high dynamic range processing.

PubMed

Chandra, Shekhar S; Engstrom, Craig; Fripp, Jurgen; Neubert, Ales; Jin, Jin; Walker, Duncan; Salvado, Olivier; Ho, Charles; Crozier, Stuart

2018-09-01

To develop a local contrast-enhancing and feature-preserving high dynamic range (HDR) image processing algorithm for multichannel and multisequence MR images of multiple body regions and tissues, and to evaluate its performance for structure visualization, bias field (correction) mitigation, and automated tissue segmentation. A multiscale-shape and detail-enhancement HDR-MRI algorithm is applied to data sets of multichannel and multisequence MR images of the brain, knee, breast, and hip. In multisequence 3T hip images, agreement between automatic cartilage segmentations and corresponding synthesized HDR-MRI series were computed for mean voxel overlap established from manual segmentations for a series of cases. Qualitative comparisons between the developed HDR-MRI and standard synthesis methods were performed on multichannel 7T brain and knee data, and multisequence 3T breast and knee data. The synthesized HDR-MRI series provided excellent enhancement of fine-scale structure from multiple scales and contrasts, while substantially reducing bias field effects in 7T brain gradient echo, T 1 and T 2 breast images and 7T knee multichannel images. Evaluation of the HDR-MRI approach on 3T hip multisequence images showed superior outcomes for automatic cartilage segmentations with respect to manual segmentation, particularly around regions with hyperintense synovial fluid, across a set of 3D sequences. The successful combination of multichannel/sequence MR images into a single-fused HDR-MR image format provided consolidated visualization of tissues within 1 omnibus image, enhanced definition of thin, complex anatomical structures in the presence of variable or hyperintense signals, and improved tissue (cartilage) segmentation outcomes. © 2018 International Society for Magnetic Resonance in Medicine.

DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING

EPA Science Inventory

The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...

Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis

PubMed Central

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A.; Gombos, Eva

2013-01-01

Purpose Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise and fitting algorithms. To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Methods We modeled the underlying dynamics of the tumor by a LDS and use the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist’s segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). Results The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared to the radiologist’s segmentation and 82.1% accuracy and 100% sensitivity when compared to the CADstream output. The overlap of the algorithm output with the radiologist’s segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72 respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC=0.95. Conclusion The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. PMID:24115175

LINKING IN SITU TIME SERIES FOREST CANOPY LAI AND PHENOLOGY METRICS WITH MODIS AND LANDSAT NDVI AND LAI PRODUCTS

EPA Science Inventory

The subject of this presentation is forest vegetation dynamics as observed by the TERRA spacecraft's Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper, and complimentary in situ time series measurements of forest canopy metrics related to Leaf Area...

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Real-time fusion of endoscopic views with dynamic 3-D cardiac images: a phantom study.

PubMed

Szpala, Stanislaw; Wierzbicki, Marcin; Guiraudon, Gerard; Peters, Terry M

2005-09-01

Minimally invasive robotically assisted cardiac surgical systems currently do not routinely employ 3-D image guidance. However, preoperative magnetic resonance and computed tomography (CT) images have the potential to be used in this role, if appropriately registered with the patient anatomy and animated synchronously with the motion of the actual heart. This paper discusses the fusion of optical images of a beating heart phantom obtained from an optically tracked endoscope, with volumetric images of the phantom created from a dynamic CT dataset. High quality preoperative dynamic CT images are created by first extracting the motion parameters of the heart from the series of temporal frames, and then applying this information to animate a high-quality heart image acquired at end systole. Temporal synchronization of the endoscopic and CT model is achieved by selecting the appropriate CT image from the dynamic set, based on an electrocardiographic trigger signal. The spatial error between the optical and virtual images is 1.4 +/- 1.1 mm, while the time discrepancy is typically 50-100 ms. Index Terms-Image guidance, image warping, minimally invasive cardiac surgery, virtual endoscopy, virtual reality.

Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images

NASA Astrophysics Data System (ADS)

Fujiki, Shogoro; Okada, Kei-ichi; Nishio, Shogo; Kitayama, Kanehiro

2016-09-01

We developed a new method to estimate stand ages of secondary vegetation in the Bornean montane zone, where local people conduct traditional shifting cultivation and protected areas are surrounded by patches of recovering secondary vegetation of various ages. Identifying stand ages at the landscape level is critical to improve conservation policies. We combined a high-resolution satellite image (WorldView-2) with time-series Landsat images. We extracted stand ages (the time elapsed since the most recent slash and burn) from a change-detection analysis with Landsat time-series images and superimposed the derived stand ages on the segments classified by object-based image analysis using WorldView-2. We regarded stand ages as a response variable, and object-based metrics as independent variables, to develop regression models that explain stand ages. Subsequently, we classified the vegetation of the target area into six age units and one rubber plantation unit (1-3 yr, 3-5 yr, 5-7 yr, 7-30 yr, 30-50 yr, >50 yr and 'rubber plantation') using regression models and linear discriminant analyses. Validation demonstrated an accuracy of 84.3%. Our approach is particularly effective in classifying highly dynamic pioneer vegetation younger than 7 years into 2-yr intervals, suggesting that rapid changes in vegetation canopies can be detected with high accuracy. The combination of a spectral time-series analysis and object-based metrics based on high-resolution imagery enabled the classification of dynamic vegetation under intensive shifting cultivation and yielded an informative land cover map based on stand ages.

United States forest disturbance trends observed with landsat time series

Treesearch

Jeffrey G. Masek; Samuel N. Goward; Robert E. Kennedy; Warren B. Cohen; Gretchen G. Moisen; Karen Schleweiss; Chengquan Huang

2013-01-01

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest...

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

ANALYSIS OF YEAR 2002 SEASONAL FOREST DYNAMICS USING TIME SERIES IN SITU LAI MEASUREMENTS AND MODIS LAI SATELLITE PRODUCTS

EPA Science Inventory

Multitemporal satellite images are the standard basis for regional-scale land-cover (LC) change detection. However, embedded in the data are the confounding effects of vegetation dynamics (phenology). As photosynthetic vegetation progresses through its annual cycle, the spectral ...

NeuroRhythmics: software for analyzing time-series measurements of saltatory movements in neuronal processes.

PubMed

Kerlin, Aaron M; Lindsley, Tara A

2008-08-15

Time-lapse imaging of living neurons both in vivo and in vitro has revealed that the growth of axons and dendrites is highly dynamic and characterized by alternating periods of extension and retraction. These growth dynamics are associated with important features of neuronal development and are differentially affected by experimental treatments, but the underlying cellular mechanisms are poorly understood. NeuroRhythmics was developed to semi-automate specific quantitative tasks involved in analysis of two-dimensional time-series images of processes that exhibit saltatory elongation. This software provides detailed information on periods of growth and nongrowth that it identifies by transitions in elongation (i.e. initiation time, average rate, duration) and information regarding the overall pattern of saltatory growth (i.e. time of pattern onset, frequency of transitions, relative time spent in a state of growth vs. nongrowth). Plots and numeric output are readily imported into other applications. The user has the option to specify criteria for identifying transitions in growth behavior, which extends the potential application of the software to neurons of different types or developmental stage and to other time-series phenomena that exhibit saltatory dynamics. NeuroRhythmics will facilitate mechanistic studies of periodic axonal and dendritic growth in neurons.

The study on the parallel processing based time series correlation analysis of RBC membrane flickering in quantitative phase imaging

NASA Astrophysics Data System (ADS)

Lee, Minsuk; Won, Youngjae; Park, Byungjun; Lee, Seungrag

2017-02-01

Not only static characteristics but also dynamic characteristics of the red blood cell (RBC) contains useful information for the blood diagnosis. Quantitative phase imaging (QPI) can capture sample images with subnanometer scale depth resolution and millisecond scale temporal resolution. Various researches have been used QPI for the RBC diagnosis, and recently many researches has been developed to decrease the process time of RBC information extraction using QPI by the parallel computing algorithm, however previous studies are interested in the static parameters such as morphology of the cells or simple dynamic parameters such as root mean square (RMS) of the membrane fluctuations. Previously, we presented a practical blood test method using the time series correlation analysis of RBC membrane flickering with QPI. However, this method has shown that there is a limit to the clinical application because of the long computation time. In this study, we present an accelerated time series correlation analysis of RBC membrane flickering using the parallel computing algorithm. This method showed consistent fractal scaling exponent results of the surrounding medium and the normal RBC with our previous research.

STRUCTURE AND DYNAMICS OF THE 2012 NOVEMBER 13/14 ECLIPSE WHITE-LIGHT CORONA

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

Pasachoff, J. M.; Rušin, V.; Saniga, M.

2015-02-20

Continuing our series of observations of coronal motion and dynamics over the solar-activity cycle, we observed from sites in Queensland, Australia, during the 2012 November 13 (UT)/14 (local time) total solar eclipse. The corona took the low-ellipticity shape typical of solar maximum (flattening index ε = 0.01), a change from the composite coronal images we observed and analyzed in this journal and elsewhere for the 2006 and 2008-2010 eclipses. After crossing the northeast Australian coast, the path of totality was over the ocean, so further totality was seen only by shipborne observers. Our results include velocities of a coronal massmore » ejection (CME; during the 36 minutes of passage from the Queensland coast to a ship north of New Zealand, we measured 413 km s{sup –1}) and we analyze its dynamics. We discuss the shapes and positions of several types of coronal features seen on our higher-resolution composite Queensland coronal images, including many helmet streamers, very faint bright and dark loops at the bases of helmet streamers, voids, and radially oriented thin streamers. We compare our eclipse observations with models of the magnetic field, confirming the validity of the predictions, and relate the eclipse phenomenology seen with the near-simultaneous images from NASA's Solar Dynamics Observatory (SDO/AIA), NASA's Extreme Ultraviolet Imager on Solar Terrestrial Relations Observatory, ESA/Royal Observatory of Belgium's Sun Watcher with Active Pixels and Image Processing (SWAP) on PROBA2, and Naval Research Laboratory's Large Angle and Spectrometric Coronagraph Experiment on ESA's Solar and Heliospheric Observatory. For example, the southeastern CME is related to the solar flare whose origin we trace with a SWAP series of images.« less

Multi-Satellite Scheduling Approach for Dynamic Areal Tasks Triggered by Emergent Disasters

NASA Astrophysics Data System (ADS)

Niu, X. N.; Zhai, X. J.; Tang, H.; Wu, L. X.

2016-06-01

The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

A tool for NDVI time series extraction from wide-swath remotely sensed images

NASA Astrophysics Data System (ADS)

Li, Zhishan; Shi, Runhe; Zhou, Cong

2015-09-01

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Detailed magnetic resonance imaging features of a case series of primary gliosarcoma.

PubMed

Sampaio, Luísa; Linhares, Paulo; Fonseca, José

2017-12-01

Objective We aimed to characterise the magnetic resonance imaging (MRI) features of a case series of primary gliosarcoma, with the inclusion of diffusion-weighted imaging and perfusion imaging with dynamic susceptibility contrast MRI. Materials and methods We conducted a retrospective study of cases of primary gliosarcoma from the Pathology Department database from January 2006 to December 2014. Clinical and demographic data were obtained. Two neuroradiologists, blinded to diagnosis, assessed tumour location, signal intensity in T1 and T2-weighted images, pattern of enhancement, diffusion-weighted imaging and dynamic susceptibility contrast MRI studies on preoperative MRI. Results Seventeen patients with primary gliosarcomas had preoperative MRI study: seven men and 10 women, with a mean age of 59 years (range 27-74). All lesions were well demarcated, supratentorial and solitary (frontal n = 5, temporal n = 4, parietal n = 3); 13 tumours abutted the dural surface (8/13 with dural enhancement); T1 and T2-weighted imaging patterns were heterogeneous and the majority of lesions (12/17) showed a rim-like enhancement pattern with focal nodularities/irregular thickness. Restricted diffusion (mean apparent diffusion coefficient values 0.64 × 10 -3 mm 2 /s) in the more solid/thick components was present in eight out of 11 patients with diffusion-weighted imaging study. Dynamic susceptibility contrast MRI study ( n = 8) consistently showed hyperperfusion in non-necrotic/cystic components on relative cerebral volume maps. Conclusions The main distinguishing features of primary gliosarcoma are supratentorial and peripheral location, well-defined boundaries and a rim-like pattern of enhancement with an irregular thick wall. Diffusion-weighted imaging and relative cerebral volume map analysis paralleled primary gliosarcoma with high-grade gliomas, thus proving helpful in differential diagnosis.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

Reconfigurable metasurface aperture for security screening and microwave imaging

NASA Astrophysics Data System (ADS)

Sleasman, Timothy; Imani, Mohammadreza F.; Boyarsky, Michael; Pulido-Mancera, Laura; Reynolds, Matthew S.; Smith, David R.

2017-05-01

Microwave imaging systems have seen growing interest in recent decades for applications ranging from security screening to space/earth observation. However, hardware architectures commonly used for this purpose have not seen drastic changes. With the advent of metamaterials a wealth of opportunities have emerged for honing metasurface apertures for microwave imaging systems. Recent thrusts have introduced dynamic reconfigurability directly into the aperture layer, providing powerful capabilities from a physical layer with considerable simplicity. The waveforms generated from such dynamic metasurfaces make them suitable for application in synthetic aperture radar (SAR) and, more generally, computational imaging. In this paper, we investigate a dynamic metasurface aperture capable of performing microwave imaging in the K-band (17.5-26.5 GHz). The proposed aperture is planar and promises an inexpensive fabrication process via printed circuit board techniques. These traits are further augmented by the tunability of dynamic metasurfaces, which provides the dexterity necessary to generate field patterns ranging from a sequence of steered beams to a series of uncorrelated radiation patterns. Imaging is experimentally demonstrated with a voltage-tunable metasurface aperture. We also demonstrate the aperture's utility in real-time measurements and perform volumetric SAR imaging. The capabilities of a prototype are detailed and the future prospects of general dynamic metasurface apertures are discussed.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

NASA Astrophysics Data System (ADS)

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging.

PubMed

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-02

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

PubMed Central

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-01-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers. PMID:26626047

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

PubMed Central

Fransson, Peter

2016-01-01

Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

PubMed

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Penetration kinetics of dimethyl sulphoxide and glycerol in dynamic optical clearing of porcine skin tissue in vitro studied by Fourier transform infrared spectroscopic imaging.

PubMed

Jiang, Jingying; Boese, Matthias; Turner, Paul; Wang, Ruikang K

2008-01-01

By use of a Fourier transform infrared (FTIR) spectroscopic imaging technique, we examine the dynamic optical clearing processes occurring in hyperosmotically biocompatible agents penetrating into skin tissue in vitro. The sequential collection of images in a time series provides an opportunity to assess penetration kinetics of dimethyl sulphoxide (DMSO) and glycerol beneath the surface of skin tissue over time. From 2-D IR spectroscopic images and 3-D false color diagrams, we show that glycerol takes at least 30 min to finally penetrate the layer of epidermis, while DMSO can be detected in epidermis after only 4 min of being topically applied over stratum corneum sides of porcine skin. The results demonstrate the potential of a FTIR spectroscopic imaging technique as an analytical tool for the study of dynamic optical clearing effects when the bio-tissue is impregnated by hyperosmotically biocompatible agents such as glycerol and DMSO.

Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram

NASA Astrophysics Data System (ADS)

Paul, F.

2015-04-01

Although animated images are very popular on the Internet, they have so far found only limited use for glaciological applications. With long time-series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable for a wide public. For this study animated image sequences were created from freely available image quick-looks of orthorectified Landsat scenes for four regions in the central Karakoram mountain range. The animations play automatically in a web-browser and might help to demonstrate glacier flow dynamics for educational purposes. The animations revealed highly complex patterns of glacier flow and surge dynamics over a 15-year time period (1998-2013). In contrast to other regions, surging glaciers in the Karakoram are often small (around 10 km2), steep, debris free, and advance for several years at comparably low annual rates (a few hundred m a-1). The advance periods of individual glaciers are generally out of phase, indicating a limited climatic control on their dynamics. On the other hand, nearly all other glaciers in the region are either stable or slightly advancing, indicating balanced or even positive mass budgets over the past few years to decades.

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Analysis of Supergranule Sizes and Velocities Using Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) and Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) Dopplergrams

NASA Technical Reports Server (NTRS)

Williams, Peter E.; Pesnell, W. Dean; Beck, John G.; Lee, Shannon

2013-01-01

Co-temporal Doppler images from Solar and Heliospheric Observatory (SOHO)/ Michelson Doppler Imager (MDI) and Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) have been analyzed to extract quantitative information about global properties of the spatial and temporal characteristics of solar supergranulation. Preliminary comparisons show that supergranules appear to be smaller and have stronger horizontal velocity flows within HMI data than was measured with MDI. There appears to be no difference in their evolutionary timescales. Supergranule sizes and velocities were analyzed over a ten-day time period at a 15-minute cadence. While the averages of the time-series retain the aforementioned differences, fluctuations of these parameters first observed in MDI data were seen in both MDI and HMI time-series, exhibiting a strong cross-correlation. This verifies that these fluctuations are not instrumental, but are solar in origin. The observed discrepancies between the averaged values from the two sets of data are a consequence of instrument resolution. The lower spatial resolution of MDI results in larger observed structures with lower velocities than is seen in HMI. While these results offer a further constraint on the physical nature of supergranules, they also provide a level of calibration between the two instruments.

Measurement of cardiac output from dynamic pulmonary circulation time CT

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

Yee, Seonghwan, E-mail: Seonghwan.Yee@Beaumont.edu; Scalzetti, Ernest M.

Purpose: To introduce a method of estimating cardiac output from the dynamic pulmonary circulation time CT that is primarily used to determine the optimal time window of CT pulmonary angiography (CTPA). Methods: Dynamic pulmonary circulation time CT series, acquired for eight patients, were retrospectively analyzed. The dynamic CT series was acquired, prior to the main CTPA, in cine mode (1 frame/s) for a single slice at the level of the main pulmonary artery covering the cross sections of ascending aorta (AA) and descending aorta (DA) during the infusion of iodinated contrast. The time series of contrast changes obtained for DA,more » which is the downstream of AA, was assumed to be related to the time series for AA by the convolution with a delay function. The delay time constant in the delay function, representing the average time interval between the cross sections of AA and DA, was determined by least square error fitting between the convoluted AA time series and the DA time series. The cardiac output was then calculated by dividing the volume of the aortic arch between the cross sections of AA and DA (estimated from the single slice CT image) by the average time interval, and multiplying the result by a correction factor. Results: The mean cardiac output value for the six patients was 5.11 (l/min) (with a standard deviation of 1.57 l/min), which is in good agreement with the literature value; the data for the other two patients were too noisy for processing. Conclusions: The dynamic single-slice pulmonary circulation time CT series also can be used to estimate cardiac output.« less

High Dynamic Velocity Range Particle Image Velocimetry Using Multiple Pulse Separation Imaging

PubMed Central

Persoons, Tim; O’Donovan, Tadhg S.

2011-01-01

The dynamic velocity range of particle image velocimetry (PIV) is determined by the maximum and minimum resolvable particle displacement. Various techniques have extended the dynamic range, however flows with a wide velocity range (e.g., impinging jets) still challenge PIV algorithms. A new technique is presented to increase the dynamic velocity range by over an order of magnitude. The multiple pulse separation (MPS) technique (i) records series of double-frame exposures with different pulse separations, (ii) processes the fields using conventional multi-grid algorithms, and (iii) yields a composite velocity field with a locally optimized pulse separation. A robust criterion determines the local optimum pulse separation, accounting for correlation strength and measurement uncertainty. Validation experiments are performed in an impinging jet flow, using laser-Doppler velocimetry as reference measurement. The precision of mean flow and turbulence quantities is significantly improved compared to conventional PIV, due to the increase in dynamic range. In a wide range of applications, MPS PIV is a robust approach to increase the dynamic velocity range without restricting the vector evaluation methods. PMID:22346564

Molecule-specific darkfield and multiphoton imaging using gold nanocages

NASA Astrophysics Data System (ADS)

Powless, Amy J.; Jenkins, Samir V.; McKay, Mary Lee; Chen, Jingyi; Muldoon, Timothy J.

2015-03-01

Due to their robust optical properties, biological inertness, and readily adjustable surface chemistry, gold nanostructures have been demonstrated as contrast agents in a variety of biomedical imaging applications. One application is dynamic imaging of live cells using bioconjugated gold nanoparticles to monitor molecule trafficking mechanisms within cells; for instance, the regulatory pathway of epidermal growth factor receptor (EGFR) undergoing endocytosis. In this paper, we have demonstrated a method to track endocytosis of EGFR in MDA-MB-468 breast adenocarcinoma cells using bioconjugated gold nanocages (AuNCs) and multiphoton microscopy. Dynamic imaging was performed using a time series capture of 4 images every minute for one hour. Specific binding and internalization of the bioconjugated AuNCs was observed while the two control groups showed non-specific binding at fewer surface sites, leading to fewer bound AuNCs and no internalization.

Early warning by near-real time disturbance monitoring (Invited)

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Zeileis, A.; Herold, M.

2013-12-01

Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information illustrating how to apply the method on satellite image time series are available at http://bfast.R-Forge.R-project.org/ and the example section of the bfastmonitor() function within the BFAST package.

Global Fiducials Program Imagery: New Opportunities for Geospatial Research, Outreach, and Education

NASA Astrophysics Data System (ADS)

Price, S. D.

2012-12-01

MOLNIA, Bruce F., PRICE, Susan D. and, KING, Stephen E., U.S. Geological Survey (USGS), 562 National Center, Reston, VA 20192, sprice@usgs.gov The Civil Applications Committee (CAC), operated by the U.S. Geological Survey (USGS), is the Federal interagency committee that facilitates Federal civil agency access to U.S. National Systems space-based electro-optical (EO) imagery for natural disaster response; global change investigations; ecosystem monitoring; mapping, charting, and geodesy; and related topics. The CAC's Global Fiducials Program (GFP) has overseen the systematic collection of high-resolution imagery to provide geospatial data time series spanning a decade or more at carefully selected sites to study and monitor changes, and to facilitate a comprehensive understanding of dynamic and sensitive areas of our planet. Since 2008, more than 4,500 one-meter resolution EO images which comprise time series from 85 GFP sites have been released for unrestricted public use. Initial site selections were made by Federal and academic scientists based on each site's unique history, susceptibility, or environmental value. For each site, collection strategies were carefully defined to maximize information extraction capabilities. This consistency enhances our ability to understand Earth's dynamic processes and long-term trends. Individual time series focus on Arctic sea ice change; temperate glacier behavior; mid-continent wetland dynamics; barrier island response to hurricanes; coastline evolution; wildland fire recovery; Long-Term Ecological Resource (LTER) site processes; and many other topics. The images are available from a USGS website at no cost, in an orthorectified GeoTIFF format with supporting metadata, making them ideal for use in Earth science education and GIS projects. New on-line tools provide enhanced analysis of these time-series imagery. For additional information go to http://gfp.usgs.gov or http://gfl.usgs.gov.Bering Glacier is the largest and longest glacier in continental North America, with a length of 190 km, a width of 40 km, and an area of about 5,000 km2. In the nine years between the 1996 image and the 2005 image, parts of the terminus retreated by more than 5 km and thinned by as much as 100 m. Long-term monitoring of Bering Glacier will enable scientists to better understand the dynamics of surging glaciers as well as how changing Alaska climate is affecting temperate glacier environments.

Coherent diffractive imaging of time-evolving samples with improved temporal resolution

DOE PAGES

Ulvestad, A.; Tripathi, A.; Hruszkewycz, S. O.; ...

2016-05-19

Bragg coherent x-ray diffractive imaging is a powerful technique for investigating dynamic nanoscale processes in nanoparticles immersed in reactive, realistic environments. Its temporal resolution is limited, however, by the oversampling requirements of three-dimensional phase retrieval. Here, we show that incorporating the entire measurement time series, which is typically a continuous physical process, into phase retrieval allows the oversampling requirement at each time step to be reduced, leading to a subsequent improvement in the temporal resolution by a factor of 2-20 times. The increased time resolution will allow imaging of faster dynamics and of radiation-dose-sensitive samples. Furthermore, this approach, which wemore » call "chrono CDI," may find use in improving the time resolution in other imaging techniques.« less

Dynamic imaging in mild traumatic brain injury: support for the theory of medial temporal vulnerability.

PubMed

Umile, Eric M; Sandel, M Elizabeth; Alavi, Abass; Terry, Charles M; Plotkin, Rosette C

2002-11-01

To determine whether patients with mild traumatic brain injury (TBI) and persistent postconcussive symptoms have evidence of temporal lobe injury on dynamic imaging. Case series. An academic medical center. Twenty patients with a clinical diagnosis of mild TBI and persistent postconcussive symptoms were referred for neuropsychologic evaluation and dynamic imaging. Fifteen (75%) had normal magnetic resonance imaging (MRI) and/or computed tomography (CT) scans at the time of injury. Neuropsychologic testing, positron-emission tomography (PET), and single-photon emission-computed tomography (SPECT). Temporal lobe findings on static imaging (MRI, CT) and dynamic imaging (PET, SPECT); neuropsychologic test findings on measures of verbal and visual memory. Testing documented neurobehavioral deficits in 19 patients (95%). Dynamic imaging documented abnormal findings in 18 patients (90%). Fifteen patients (75%) had temporal lobe abnormalities on PET and SPECT (primarily in medial temporal regions); abnormal findings were bilateral in 10 patients (50%) and unilateral in 5 (25%). Six patients (30%) had frontal abnormalities, and 8 (40%) had nonfrontotemporal abnormalities. Correlations between neuropsychologic testing and dynamic imaging could be established but not consistently across the whole group. Patients with mild TBI and persistent postconcussive symptoms have a high incidence of temporal lobe injury (presumably involving the hippocampus and related structures), which may explain the frequent finding of memory disorders in this population. The abnormal temporal lobe findings on PET and SPECT in humans may be analogous to the neuropathologic evidence of medial temporal injury provided by animal studies after mild TBI. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Global sampling of the seasonal changes in vegetation biophysical properties and associated carbon flux dynamics: using the synergy of information captured by spectral time series

NASA Astrophysics Data System (ADS)

Campbell, P. K. E.; Huemmrich, K. F.; Middleton, E.; Voorhis, S.; Landis, D.

2016-12-01

Spatial heterogeneity and seasonal dynamics in vegetation function contribute significantly to the uncertainties in regional and global CO2 budgets. High spectral resolution imaging spectroscopy ( 10 nm, 400-2500 nm) provides an efficient tool for synoptic evaluation of the factors significantly affecting the ability of the vegetation to sequester carbon and to reflect radiation, due to changes in vegetation chemical and structural composition. EO-1 Hyperion has collected more than 15 years of repeated observations for vegetation studies, and currently Hyperion time series are available for study of vegetation carbon dynamics at a number of FLUX sites. This study presents results from the analysis of EO-1 Hyperion and FLUX seasonal composites for a range of ecosystems across the globe. Spectral differences and seasonal trends were evaluated for each vegetation type and specific phenology. Evaluating the relationships between CO2 flux parameters (e.g., Net ecosystem production - NEP; Gross Ecosystem Exchange - GEE, CO2 flux, μmol m-2 s-1) and spectral parameters for these very different ecosystems, high correlations were established to parameters associated with canopy water and chlorophyll content for deciduous, and photosynthetic function for conifers. Imaging spectrometry provided high spatial resolution maps of CO2 fluxes absorbed by vegetation, and was efficient in tracing seasonal flux dynamics. This study will present examples for key ecosystem tipes to demonstrate the ability of imaging spectrometry and EO-1 Hyperion to map and compare CO2 flux dynamics across the globe.

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

PubMed

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Kalman Filter Techniques for Accelerated Cartesian Dynamic Cardiac Imaging

PubMed Central

Feng, Xue; Salerno, Michael; Kramer, Christopher M.; Meyer, Craig H.

2012-01-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories, because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and SNR. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. PMID:22926804

Informatics in radiology (infoRAD): navigating the fifth dimension: innovative interface for multidimensional multimodality image navigation.

PubMed

Rosset, Antoine; Spadola, Luca; Pysher, Lance; Ratib, Osman

2006-01-01

The display and interpretation of images obtained by combining three-dimensional data acquired with two different modalities (eg, positron emission tomography and computed tomography) in the same subject require complex software tools that allow the user to adjust the image parameters. With the current fast imaging systems, it is possible to acquire dynamic images of the beating heart, which add a fourth dimension of visual information-the temporal dimension. Moreover, images acquired at different points during the transit of a contrast agent or during different functional phases add a fifth dimension-functional data. To facilitate real-time image navigation in the resultant large multidimensional image data sets, the authors developed a Digital Imaging and Communications in Medicine-compliant software program. The open-source software, called OsiriX, allows the user to navigate through multidimensional image series while adjusting the blending of images from different modalities, image contrast and intensity, and the rate of cine display of dynamic images. The software is available for free download at http://homepage.mac.com/rossetantoine/osirix. (c) RSNA, 2006.

Cyberpark 2000: Protected Areas Management Pilot Project. Satellite time series vegetation monitoring

NASA Astrophysics Data System (ADS)

Monteleone, M.; Lanorte, A.; Lasaponara, R.

2009-04-01

Cyberpark 2000 is a project funded by the UE Regional Operating Program of the Apulia Region (2000-2006). The main objective of the Cyberpark 2000 project is to develop a new assessment model for the management and monitoring of protected areas in Foggia Province (Apulia Region) based on Information and Communication Technologies. The results herein described are placed inside the research activities finalized to develop an environmental monitoring system knowledge based on the use of satellite time series. This study include: - A- satellite time series of high spatial resolution data for supporting the analysis of fire static risk factors through land use mapping and spectral/quantitative characterization of vegetation fuels; - B- satellite time series of MODIS for supporting fire dynamic risk evaluation of study area - Integrated fire detection by using thermal imaging cameras placed on panoramic view-points; - C - integrated high spatial and high temporal satellite time series for supporting studies in change detection factors or anomalies in vegetation covers; - D - satellite time-series for monitoring: (i) post fire vegetation recovery and (ii) spatio/temporal vegetation dynamics in unburned and burned vegetation covers.

Readout models for BaFBr0.85I0.15:Eu image plates

NASA Astrophysics Data System (ADS)

Stoeckl, M.; Solodov, A. A.

2018-06-01

The linearity of the photostimulated luminescence process makes repeated image-plate scanning a viable technique to extract a more dynamic range. In order to obtain a response estimate, two semi-empirical models for the readout fading of an image plate are introduced; they relate the depth distribution of activated photostimulated luminescence centers within an image plate to the recorded signal. Model parameters are estimated from image-plate scan series with BAS-MS image plates and the Typhoon FLA 7000 scanner for the hard x-ray image-plate diagnostic over a collection of experiments providing x-ray energy spectra whose approximate shape is a double exponential.

IPET and FETR: Experimental Approach for Studying Molecular Structure Dynamics by Cryo-Electron Tomography of a Single-Molecule Structure

PubMed Central

Zhang, Lei; Ren, Gang

2012-01-01

The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (<400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a “focused electron tomography reconstruction” (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single “snapshot” molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules. PMID:22291925

High order magnetic optics for high dynamic range proton radiography at a kinetic energy of 800 MeV

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

Sjue, S. K. L., E-mail: sjue@lanl.gov; Mariam, F. G.; Merrill, F. E.

2016-01-15

Flash radiography with 800 MeV kinetic energy protons at Los Alamos National Laboratory is an important experimental tool for investigations of dynamic material behavior driven by high explosives or pulsed power. The extraction of quantitative information about density fields in a dynamic experiment from proton generated images requires a high fidelity model of the proton imaging process. It is shown that accurate calculations of the transmission through the magnetic lens system require terms beyond second order for protons far from the tune energy. The approach used integrates the correlated multiple Coulomb scattering distribution simultaneously over the collimator and the imagemore » plane. Comparison with a series of static calibration images demonstrates the model’s accurate reproduction of both the transmission and blur over a wide range of tune energies in an inverse identity lens that consists of four quadrupole electromagnets.« less

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

PubMed Central

Manning, Cerys; Rattray, Magnus

2017-01-01

Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package. PMID:28493880

Get Close to Glaciers with Satellite Imagery.

ERIC Educational Resources Information Center

Hall, Dorothy K.

1986-01-01

Discusses the use of remote sensing from satellites to monitor glaciers. Discusses efforts to use remote sensing satellites of the Landsat series for examining the global distribution, mass, balance, movements, and dynamics of the world's glaciers. Includes several Landsat images of various glaciers. (TW)

Application of the Virtual Fields Method to a relaxation behaviour of rubbers

NASA Astrophysics Data System (ADS)

Yoon, Sung-ho; Siviour, Clive R.

2018-07-01

This paper presents the application of the Virtual Fields Method (VFM) for the characterization of viscoelastic behaviour of rubbers. The relaxation behaviour of the rubbers following a dynamic loading event is characterized using the dynamic VFM in which full-field (two dimensional) strain and acceleration data, obtained from high-speed imaging, are analysed by the principle of virtual work without traction force data, instead using the acceleration fields in the specimen to provide stress information. Two (silicone and nitrile) rubbers were tested in tension using a drop-weight apparatus. It is assumed that the dynamic behaviour is described by the combination of hyperelastic and Prony series models. A VFM based procedure is designed and used to produce the identification of the modulus term of a hyperelastic model and the Prony series parameters within a time scale determined by two experimental factors: imaging speed and loading duration. Then, the time range of the data is extended using experiments at different temperatures combined with the time-temperature superposition principle. Prior to these experimental analyses, finite element simulations were performed to validate the application of the proposed VFM analysis. Therefore, for the first time, it has been possible to identify relaxation behaviour of a material following dynamic loading, using a technique that can be applied to both small and large deformations.

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

PubMed

Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2017-09-01

Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

Sentinel-2 ArcGIS Tool for Environmental Monitoring

NASA Astrophysics Data System (ADS)

Plesoianu, Alin; Cosmin Sandric, Ionut; Anca, Paula; Vasile, Alexandru; Calugaru, Andreea; Vasile, Cristian; Zavate, Lucian

2017-04-01

This paper addresses one of the biggest challenges regarding Sentinel-2 data, related to the need of an efficient tool to access and process the large collection of images that are available. Consequently, developing a tool for the automation of Sentinel-2 data analysis is the most immediate need. We developed a series of tools for the automation of Sentinel-2 data download and processing for vegetation health monitoring. The tools automatically perform the following operations: downloading image tiles from ESA's Scientific Hub or other venders (Amazon), pre-processing of the images to extract the 10-m bands, creating image composites, applying a series of vegetation indexes (NDVI, OSAVI, etc.) and performing change detection analyses on different temporal data sets. All of these tools run in a dynamic way in the ArcGIS Platform, without the need of creating intermediate datasets (rasters, layers), as the images are processed on-the-fly in order to avoid data duplication. Finally, they allow complete integration with the ArcGIS environment and workflows

Standardized principal components for vegetation variability monitoring across space and time

NASA Astrophysics Data System (ADS)

Mathew, T. R.; Vohora, V. K.

2016-08-01

Vegetation at any given location changes through time and in space. In what quantity it changes, where and when can help us in identifying sources of ecosystem stress, which is very useful for understanding changes in biodiversity and its effect on climate change. Such changes known for a region are important in prioritizing management. The present study considers the dynamics of savanna vegetation in Kruger National Park (KNP) through the use of temporal satellite remote sensing images. Spatial variability of vegetation is a key characteristic of savanna landscapes and its importance to biodiversity has been demonstrated by field-based studies. The data used for the study were sourced from the U.S. Agency for International Development where AVHRR derived Normalized Difference Vegetation Index (NDVI) images available at spatial resolutions of 8 km and at dekadal scales. The study area was extracted from these images for the time-period 1984-2002. Maximum value composites were derived for individual months resulting in an image dataset of 216 NDVI images. Vegetation dynamics across spatio-temporal domains were analyzed using standardized principal components analysis (SPCA) on the NDVI time-series. Each individual image variability in the time-series is considered. The outcome of this study demonstrated promising results - the variability of vegetation change in the area across space and time, and also indicated changes in landscape on 6 individual principal components (PCs) showing differences not only in magnitude, but also in pattern, of different selected eco-zones with constantly changing and evolving ecosystem.

Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification.

PubMed

Lee, Benjamin C; Moody, Jonathan B; Poitrasson-Rivière, Alexis; Melvin, Amanda C; Weinberg, Richard L; Corbett, James R; Ficaro, Edward P; Murthy, Venkatesh L

2018-03-23

Patient motion can lead to misalignment of left ventricular volumes of interest and subsequently inaccurate quantification of myocardial blood flow (MBF) and flow reserve (MFR) from dynamic PET myocardial perfusion images. We aimed to identify the prevalence of patient motion in both blood and tissue phases and analyze the effects of this motion on MBF and MFR estimates. We selected 225 consecutive patients that underwent dynamic stress/rest rubidium-82 chloride ( 82 Rb) PET imaging. Dynamic image series were iteratively reconstructed with 5- to 10-second frame durations over the first 2 minutes for the blood phase and 10 to 80 seconds for the tissue phase. Motion shifts were assessed by 3 physician readers from the dynamic series and analyzed for frequency, magnitude, time, and direction of motion. The effects of this motion isolated in time, direction, and magnitude on global and regional MBF and MFR estimates were evaluated. Flow estimates derived from the motion corrected images were used as the error references. Mild to moderate motion (5-15 mm) was most prominent in the blood phase in 63% and 44% of the stress and rest studies, respectively. This motion was observed with frequencies of 75% in the septal and inferior directions for stress and 44% in the septal direction for rest. Images with blood phase isolated motion had mean global MBF and MFR errors of 2%-5%. Isolating blood phase motion in the inferior direction resulted in mean MBF and MFR errors of 29%-44% in the RCA territory. Flow errors due to tissue phase isolated motion were within 1%. Patient motion was most prevalent in the blood phase and MBF and MFR errors increased most substantially with motion in the inferior direction. Motion correction focused on these motions is needed to reduce MBF and MFR errors.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

NASA Technical Reports Server (NTRS)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

An automated detection for axonal boutons in vivo two-photon imaging of mouse

NASA Astrophysics Data System (ADS)

Li, Weifu; Zhang, Dandan; Xie, Qiwei; Chen, Xi; Han, Hua

2017-02-01

Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.

Oscillatory dynamics in the dorsal and ventral attention networks during the reorienting of attention.

PubMed

Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wiesman, Alex I; McDermott, Timothy J; Wilson, Tony W

2018-05-01

The ability to reorient attention within the visual field is central to daily functioning, and numerous fMRI studies have shown that the dorsal and ventral attention networks (DAN, VAN) are critical to such processes. However, despite the instantaneous nature of attentional shifts, the dynamics of oscillatory activity serving attentional reorientation remain poorly characterized. In this study, we utilized magnetoencephalography (MEG) and a Posner task to probe the dynamics of attentional reorienting in 29 healthy adults. MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Voxel time series were then extracted from peak voxels in the functional beamformer images. These time series were used to quantify the dynamics of attentional reorienting, and to compute dynamic functional connectivity. Our results indicated strong increases in theta and decreases in alpha and beta activity across many nodes in the DAN and VAN. Interestingly, theta responses were generally stronger during trials that required attentional reorienting relative to those that did not, while alpha and beta oscillations were more dynamic, with many regions exhibiting significantly stronger responses during non-reorienting trials initially, and the opposite pattern during later processing. Finally, stronger functional connectivity was found following target presentation (575-700 ms) between bilateral superior parietal lobules during attentional reorienting. In sum, these data show that visual attention is served by multiple cortical regions within the DAN and VAN, and that attentional reorienting processes are often associated with spectrally-specific oscillations that have largely distinct spatiotemporal dynamics. © 2018 Wiley Periodicals, Inc.

Crop Identification Using Time Series of Landsat-8 and Radarsat-2 Images: Application in a Groundwater Irrigated Region, South India

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Hubert-Moy, L.; Betbederet, J.; Ruiz, L.; Sekhar, M.; Corgne, S.

2016-08-01

Monitoring land use and land cover and more particularly irrigated cropland dynamics is of great importance for water resources management and land use planning. The objective of this study was to evaluate the combined use of multi-temporal optical and radar data with a high spatial resolution in order to improve the precision of irrigated crop identification by taking into account information on crop phenological stages. SAR and optical parameters were derived from time- series of seven quad-pol RADARSAT-2 and four Landsat-8 images which were acquired on the Berambadi catchment, South India, during the monsoon crop season at the growth stages of turmeric crop. To select the best parameter to discriminate turmeric crops, an analysis of covariance (ANCOVA) was applied on all the time-series parameters and the most discriminant ones were classified using the Support Vector Machine (SVM) technique. Results show that in absence of optical images, polarimetric parameters derived from SAR time-series can be used for the turmeric area estimates and that the combined use of SAR and optical parameters can improve the classification accuracy to identify turmeric.

Observing Bridge Dynamic Deflection in Green Time by Information Technology

NASA Astrophysics Data System (ADS)

Yu, Chengxin; Zhang, Guojian; Zhao, Yongqian; Chen, Mingzhi

2018-01-01

As traditional surveying methods are limited to observe bridge dynamic deflection; information technology is adopted to observe bridge dynamic deflection in Green time. Information technology used in this study means that we use digital cameras to photograph the bridge in red time as a zero image. Then, a series of successive images are photographed in green time. Deformation point targets are identified and located by Hough transform. With reference to the control points, the deformation values of these deformation points are obtained by differencing the successive images with a zero image, respectively. Results show that the average measurement accuracies of C0 are 0.46 pixels, 0.51 pixels and 0.74 pixels in X, Z and comprehensive direction. The average measurement accuracies of C1 are 0.43 pixels, 0.43 pixels and 0.67 pixels in X, Z and comprehensive direction in these tests. The maximal bridge deflection is 44.16mm, which is less than 75mm (Bridge deflection tolerance value). Information technology in this paper can monitor bridge dynamic deflection and depict deflection trend curves of the bridge in real time. It can provide data support for the site decisions to the bridge structure safety.

Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI.

PubMed

Johansson, Adam; Balter, James; Cao, Yue

2018-03-01

Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast-enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra-image motion blur remains after alignment and can alter the shape of contrast-agent uptake curves. We introduce a method to correct for inter- and intra-image motion during image reconstruction. Sixteen liver dynamic contrast-enhanced MRI examinations of nine subjects were performed using a golden-angle stack-of-stars sequence. For each examination, an image time series with high temporal resolution but severe streak artifacts was reconstructed. Images were aligned using region-limited rigid image registration within a region of interest covering the liver. The transformations resulting from alignment were used to correct raw data for motion by modulating and rotating acquired lines in k-space. The corrected data were then reconstructed using view sharing. Portal-venous input functions extracted from motion-corrected images had significantly greater peak signal enhancements (mean increase: 16%, t-test, P <  0.001) than those from images aligned using image registration after reconstruction. In addition, portal-venous perfusion maps estimated from motion-corrected images showed fewer artifacts close to the edge of the liver. Motion-corrected image reconstruction restores uptake curves distorted by motion. Motion correction also reduces motion artifacts in estimated perfusion parameter maps. Magn Reson Med 79:1345-1353, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Diffusion, Perfusion, and Histopathologic Characteristics of Desmoplastic Infantile Ganglioglioma.

PubMed

Ho, Chang Y; Gener, Melissa; Bonnin, Jose; Kralik, Stephen F

2016-07-01

We present a case series of a rare tumor, the desmoplastic infantile ganglioglioma (DIG) with MRI diffusion and perfusion imaging quantification as well as histopathologic characterization. Four cases with pathologically-proven DIG had diffusion weighted imaging (DWI) and two of the four had dynamic susceptibility contrast imaging. All four tumors demonstrate DWI findings compatible with low-grade pediatric tumors. For the two cases with perfusion imaging, a higher relative cerebral blood volume was associated with higher proliferation index on histopathology for one of the cases. Our results are discussed in conjunction with a literature review.

Diffusion, Perfusion, and Histopathologic Characteristics of Desmoplastic Infantile Ganglioglioma

PubMed Central

Ho, Chang Y; Gener, Melissa; Bonnin, Jose; Kralik, Stephen F

2016-01-01

We present a case series of a rare tumor, the desmoplastic infantile ganglioglioma (DIG) with MRI diffusion and perfusion imaging quantification as well as histopathologic characterization. Four cases with pathologically-proven DIG had diffusion weighted imaging (DWI) and two of the four had dynamic susceptibility contrast imaging. All four tumors demonstrate DWI findings compatible with low-grade pediatric tumors. For the two cases with perfusion imaging, a higher relative cerebral blood volume was associated with higher proliferation index on histopathology for one of the cases. Our results are discussed in conjunction with a literature review. PMID:27761184

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.

Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT.

PubMed

Malinen, Eirik; Rødal, Jan; Knudtsen, Ingerid Skjei; Søvik, Åste; Skogmo, Hege Kippenes

2011-08-01

Molecular and functional imaging techniques such as dynamic positron emission tomography (DPET) and dynamic contrast enhanced computed tomography (DCECT) may provide improved characterization of tumors compared to conventional anatomic imaging. The purpose of the current work was to compare spatiotemporal uptake patterns in DPET and DCECT images. A PET/CT protocol comprising DCECT with an iodine based contrast agent and DPET with (18)F-fluorodeoxyglucose was set up. The imaging protocol was used for examination of three dogs with spontaneous tumors of the head and neck at sessions prior to and after fractionated radiotherapy. Software tools were developed for downsampling the DCECT image series to the PET image dimensions, for segmentation of tracer uptake pattern in the tumors and for spatiotemporal correlation analysis of DCECT and DPET images. DCECT images evaluated one minute post injection qualitatively resembled the DPET images at most imaging sessions. Segmentation by region growing gave similar tumor extensions in DCECT and DPET images, with a median Dice similarity coefficient of 0.81. A relatively high correlation (median 0.85) was found between temporal tumor uptake patterns from DPET and DCECT. The heterogeneity in tumor uptake was not significantly different in the DPET and DCECT images. The median of the spatial correlation was 0.72. DCECT and DPET gave similar temporal wash-in characteristics, and the images also showed a relatively high spatial correlation. Hence, if the limited spatial resolution of DPET is considered adequate, a single DPET scan only for assessing both tumor perfusion and metabolic activity may be considered. However, further work on a larger number of cases is needed to verify the correlations observed in the present study.

Experimental analysis of quasi-static and dynamic fracture initiation toughness of gy4 armor steel material

NASA Astrophysics Data System (ADS)

Ren, Peng; Guo, Zitao

Quasi-static and dynamic fracture initiation toughness of gy4 armour steel material are investigated using three point bend specimen. The modified split Hopkinson pressure bar (SHPB) apparatus with digital image correlation (DIC) system is applied to dynamic loading experiments. Full-field deformation measurements are obtained by using DIC to elucidate on the strain fields associated with the mechanical response. A series of experiments are conducted at different strain rate ranging from 10-3 s-1 to 103 s-1, and the loading rate on the fracture initiation toughness is investigated. Specially, the scanning electron microscope imaging technique is used to investigate the fracture failure micromechanism of fracture surfaces. The gy4 armour steel material fracture toughness is found to be sensitive to strain rate and higher for dynamic loading as compared to quasi-static loading. This work is supported by National Nature Science Foundation under Grant 51509115.

Interannual Change Detection of Mediterranean Seagrasses Using RapidEye Image Time Series

PubMed Central

Traganos, Dimosthenis; Reinartz, Peter

2018-01-01

Recent research studies have highlighted the decrease in the coverage of Mediterranean seagrasses due to mainly anthropogenic activities. The lack of data on the distribution of these significant aquatic plants complicates the quantification of their decreasing tendency. While Mediterranean seagrasses are declining, satellite remote sensing technology is growing at an unprecedented pace, resulting in a wealth of spaceborne image time series. Here, we exploit recent advances in high spatial resolution sensors and machine learning to study Mediterranean seagrasses. We process a multispectral RapidEye time series between 2011 and 2016 to detect interannual seagrass dynamics in 888 submerged hectares of the Thermaikos Gulf, NW Aegean Sea, Greece (eastern Mediterranean Sea). We assess the extent change of two Mediterranean seagrass species, the dominant Posidonia oceanica and Cymodocea nodosa, following atmospheric and analytical water column correction, as well as machine learning classification, using Random Forests, of the RapidEye time series. Prior corrections are necessary to untangle the initially weak signal of the submerged seagrass habitats from satellite imagery. The central results of this study show that P. oceanica seagrass area has declined by 4.1%, with a trend of −11.2 ha/yr, while C. nodosa seagrass area has increased by 17.7% with a trend of +18 ha/yr throughout the 5-year study period. Trends of change in spatial distribution of seagrasses in the Thermaikos Gulf site are in line with reported trends in the Mediterranean. Our presented methodology could be a time- and cost-effective method toward the quantitative ecological assessment of seagrass dynamics elsewhere in the future. From small meadows to whole coastlines, knowledge of aquatic plant dynamics could resolve decline or growth trends and accurately highlight key units for future restoration, management, and conservation. PMID:29467777

Interannual Change Detection of Mediterranean Seagrasses Using RapidEye Image Time Series.

PubMed

Traganos, Dimosthenis; Reinartz, Peter

2018-01-01

Recent research studies have highlighted the decrease in the coverage of Mediterranean seagrasses due to mainly anthropogenic activities. The lack of data on the distribution of these significant aquatic plants complicates the quantification of their decreasing tendency. While Mediterranean seagrasses are declining, satellite remote sensing technology is growing at an unprecedented pace, resulting in a wealth of spaceborne image time series. Here, we exploit recent advances in high spatial resolution sensors and machine learning to study Mediterranean seagrasses. We process a multispectral RapidEye time series between 2011 and 2016 to detect interannual seagrass dynamics in 888 submerged hectares of the Thermaikos Gulf, NW Aegean Sea, Greece (eastern Mediterranean Sea). We assess the extent change of two Mediterranean seagrass species, the dominant Posidonia oceanica and Cymodocea nodosa , following atmospheric and analytical water column correction, as well as machine learning classification, using Random Forests, of the RapidEye time series. Prior corrections are necessary to untangle the initially weak signal of the submerged seagrass habitats from satellite imagery. The central results of this study show that P. oceanica seagrass area has declined by 4.1%, with a trend of -11.2 ha/yr, while C. nodosa seagrass area has increased by 17.7% with a trend of +18 ha/yr throughout the 5-year study period. Trends of change in spatial distribution of seagrasses in the Thermaikos Gulf site are in line with reported trends in the Mediterranean. Our presented methodology could be a time- and cost-effective method toward the quantitative ecological assessment of seagrass dynamics elsewhere in the future. From small meadows to whole coastlines, knowledge of aquatic plant dynamics could resolve decline or growth trends and accurately highlight key units for future restoration, management, and conservation.

Integrated Modeling Activities for the James Webb Space Telescope: Optical Jitter Analysis

NASA Technical Reports Server (NTRS)

Hyde, T. Tupper; Ha, Kong Q.; Johnston, John D.; Howard, Joseph M.; Mosier, Gary E.

2004-01-01

This is a continuation of a series of papers on the integrated modeling activities for the James Webb Space Telescope(JWST). Starting with the linear optical model discussed in part one, and using the optical sensitivities developed in part two, we now assess the optical image motion and wavefront errors from the structural dynamics. This is often referred to as "jitter: analysis. The optical model is combined with the structural model and the control models to create a linear structural/optical/control model. The largest jitter is due to spacecraft reaction wheel assembly disturbances which are harmonic in nature and will excite spacecraft and telescope structural. The structural/optic response causes image quality degradation due to image motion (centroid error) as well as dynamic wavefront error. Jitter analysis results are used to predict imaging performance, improve the structural design, and evaluate the operational impact of the disturbance sources.

Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

PubMed

Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

2018-02-16

Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis.

PubMed

Feng, Qianjin; Zhou, Yujia; Li, Xueli; Mei, Yingjie; Lu, Zhentai; Zhang, Yu; Feng, Yanqiu; Liu, Yaqin; Yang, Wei; Chen, Wufan

2016-09-29

A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance.

Cloud masking and removal in remote sensing image time series

NASA Astrophysics Data System (ADS)

Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau

2017-01-01

Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.

Multiparametric evaluation of hindlimb ischemia using time-series indocyanine green fluorescence imaging.

PubMed

Guang, Huizhi; Cai, Chuangjian; Zuo, Simin; Cai, Wenjuan; Zhang, Jiulou; Luo, Jianwen

2017-03-01

Peripheral arterial disease (PAD) can further cause lower limb ischemia. Quantitative evaluation of the vascular perfusion in the ischemic limb contributes to diagnosis of PAD and preclinical development of new drug. In vivo time-series indocyanine green (ICG) fluorescence imaging can noninvasively monitor blood flow and has a deep tissue penetration. The perfusion rate estimated from the time-series ICG images is not enough for the evaluation of hindlimb ischemia. The information relevant to the vascular density is also important, because angiogenesis is an essential mechanism for post-ischemic recovery. In this paper, a multiparametric evaluation method is proposed for simultaneous estimation of multiple vascular perfusion parameters, including not only the perfusion rate but also the vascular perfusion density and the time-varying ICG concentration in veins. The target method is based on a mathematical model of ICG pharmacokinetics in the mouse hindlimb. The regression analysis performed on the time-series ICG images obtained from a dynamic reflectance fluorescence imaging system. The results demonstrate that the estimated multiple parameters are effective to quantitatively evaluate the vascular perfusion and distinguish hypo-perfused tissues from well-perfused tissues in the mouse hindlimb. The proposed multiparametric evaluation method could be useful for PAD diagnosis. The estimated perfusion rate and vascular perfusion density maps (left) and the time-varying ICG concentration in veins of the ankle region (right) of the normal and ischemic hindlimbs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery

NASA Astrophysics Data System (ADS)

Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L.

2016-12-01

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques.

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

PubMed

Buonaccorsi, Giovanni A; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; O'Connor, James P B; Davies, Karen; Jackson, Alan; Jayson, Gordon C; Parker, Geoff J M

2006-09-01

The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

Extended space expectation values in quantum dynamical system evolutions

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

Demiralp, Metin

2014-10-06

The time variant power series expansion for the expectation value of a given quantum dynamical operator is well-known and well-investigated issue in quantum dynamics. However, depending on the operator and Hamiltonian singularities this expansion either may not exist or may not converge for all time instances except the beginning of the evolution. This work focuses on this issue and seeks certain cures for the negativities. We work in the extended space obtained by adding all images of the initial wave function under the system Hamiltonian’s positive integer powers. This requires the introduction of certain appropriately defined weight operators. The resultingmore » better convergence in the temporal power series urges us to call the new defined entities “extended space expectation values” even though they are constructed over certain weight operators and are somehow pseudo expectation values.« less

Arterial spin labeling in combination with a look-locker sampling strategy: inflow turbo-sampling EPI-FAIR (ITS-FAIR).

PubMed

Günther, M; Bock, M; Schad, L R

2001-11-01

Arterial spin labeling (ASL) permits quantification of tissue perfusion without the use of MR contrast agents. With standard ASL techniques such as flow-sensitive alternating inversion recovery (FAIR) the signal from arterial blood is measured at a fixed inversion delay after magnetic labeling. As no image information is sampled during this delay, FAIR measurements are inefficient and time-consuming. In this work the FAIR preparation was combined with a Look-Locker acquisition to sample not one but a series of images after each labeling pulse. This new method allows monitoring of the temporal dynamics of blood inflow. To quantify perfusion, a theoretical model for the signal dynamics during the Look-Locker readout was developed and applied. Also, the imaging parameters of the new ITS-FAIR technique were optimized using an expression for the variance of the calculated perfusion. For the given scanner hardware the parameters were: temporal resolution 100 ms, 23 images, flip-angle 25.4 degrees. In a normal volunteer experiment with these parameters an average perfusion value of 48.2 +/- 12.1 ml/100 g/min was measured in the brain. With the ability to obtain ITS-FAIR time series with high temporal resolution arterial transit times in the range of -138 - 1054 ms were measured, where nonphysical negative values were found in voxels containing large vessels. Copyright 2001 Wiley-Liss, Inc.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram

NASA Astrophysics Data System (ADS)

Paul, F.

2015-11-01

Although animated images are very popular on the internet, they have so far found only limited use for glaciological applications. With long time series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable to the wider public. For this study, animated image sequences were created for four regions in the central Karakoram mountain range over a 25-year time period (1990-2015) from freely available image quick-looks of orthorectified Landsat scenes. The animations play automatically in a web browser and reveal highly complex patterns of glacier flow and surge dynamics that are difficult to obtain by other methods. In contrast to other regions, surging glaciers in the Karakoram are often small (10 km2 or less), steep, debris-free, and advance for several years to decades at relatively low annual rates (about 100 m a-1). These characteristics overlap with those of non-surge-type glaciers, making a clear identification difficult. However, as in other regions, the surging glaciers in the central Karakoram also show sudden increases of flow velocity and mass waves travelling down glacier. The surges of individual glaciers are generally out of phase, indicating a limited climatic control on their dynamics. On the other hand, nearly all other glaciers in the region are either stable or slightly advancing, indicating balanced or even positive mass budgets over the past few decades.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

NASA Astrophysics Data System (ADS)

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-04-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

Live-cell imaging for the assessment of the dynamics of autophagosome formation: focus on early steps.

PubMed

Karanasios, Eleftherios; Ktistakis, Nicholas T

2015-03-01

Autophagy is a cytosolic degradative pathway, which through a series of complicated membrane rearrangements leads to the formation of a unique double membrane vesicle, the autophagosome. The use of fluorescent proteins has allowed visualizing the autophagosome formation in live cells and in real time, almost 40 years after electron microscopy studies observed these structures for the first time. In the last decade, live-cell imaging has been extensively used to study the dynamics of autophagosome formation in cultured mammalian cells. Hereby we will discuss how the live-cell imaging studies have tried to settle the debate about the origin of the autophagosome membrane and how they have described the way different autophagy proteins coordinate in space and time in order to drive autophagosome formation. Copyright © 2014 Elsevier Inc. All rights reserved.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

PubMed Central

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-01-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics. PMID:24694686

Appearance of the canine meninges in subtraction magnetic resonance images.

PubMed

Lamb, Christopher R; Lam, Richard; Keenihan, Erin K; Frean, Stephen

2014-01-01

The canine meninges are not visible as discrete structures in noncontrast magnetic resonance (MR) images, and are incompletely visualized in T1-weighted, postgadolinium images, reportedly appearing as short, thin curvilinear segments with minimal enhancement. Subtraction imaging facilitates detection of enhancement of tissues, hence may increase the conspicuity of meninges. The aim of the present study was to describe qualitatively the appearance of canine meninges in subtraction MR images obtained using a dynamic technique. Images were reviewed of 10 consecutive dogs that had dynamic pre- and postgadolinium T1W imaging of the brain that was interpreted as normal, and had normal cerebrospinal fluid. Image-anatomic correlation was facilitated by dissection and histologic examination of two canine cadavers. Meningeal enhancement was relatively inconspicuous in postgadolinium T1-weighted images, but was clearly visible in subtraction images of all dogs. Enhancement was visible as faint, small-rounded foci compatible with vessels seen end on within the sulci, a series of larger rounded foci compatible with vessels of variable caliber on the dorsal aspect of the cerebral cortex, and a continuous thin zone of moderate enhancement around the brain. Superimposition of color-encoded subtraction images on pregadolinium T1- and T2-weighted images facilitated localization of the origin of enhancement, which appeared to be predominantly dural, with relatively few leptomeningeal structures visible. Dynamic subtraction MR imaging should be considered for inclusion in clinical brain MR protocols because of the possibility that its use may increase sensitivity for lesions affecting the meninges. © 2014 American College of Veterinary Radiology.

Smart align -- A new tool for robust non-rigid registration of scanning microscope data

DOE PAGES

Jones, Lewys; Yang, Hao; Pennycook, Timothy J.; ...

2015-07-10

Many microscopic investigations of materials may benefit from the recording of multiple successive images. This can include techniques common to several types of microscopy such as frame averaging to improve signal-to-noise ratios (SNR) or time series to study dynamic processes or more specific applications. In the scanning transmission electron microscope, this might include focal series for optical sectioning or aberration measurement, beam damage studies or camera-length series to study the effects of strain; whilst in the scanning tunnelling microscope, this might include bias voltage series to probe local electronic structure. Whatever the application, such investigations must begin with the carefulmore » alignment of these data stacks, an operation that is not always trivial. In addition, the presence of low-frequency scanning distortions can introduce intra-image shifts to the data. Here, we describe an improved automated method of performing non-rigid registration customised for the challenges unique to scanned microscope data specifically addressing the issues of low-SNR data, images containing a large proportion of crystalline material and/or local features of interest such as dislocations or edges. Careful attention has been paid to artefact testing of the non-rigid registration method used, and the importance of this registration for the quantitative interpretation of feature intensities and positions is evaluated.« less

Smart align -- A new tool for robust non-rigid registration of scanning microscope data

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

Jones, Lewys; Yang, Hao; Pennycook, Timothy J.

Many microscopic investigations of materials may benefit from the recording of multiple successive images. This can include techniques common to several types of microscopy such as frame averaging to improve signal-to-noise ratios (SNR) or time series to study dynamic processes or more specific applications. In the scanning transmission electron microscope, this might include focal series for optical sectioning or aberration measurement, beam damage studies or camera-length series to study the effects of strain; whilst in the scanning tunnelling microscope, this might include bias voltage series to probe local electronic structure. Whatever the application, such investigations must begin with the carefulmore » alignment of these data stacks, an operation that is not always trivial. In addition, the presence of low-frequency scanning distortions can introduce intra-image shifts to the data. Here, we describe an improved automated method of performing non-rigid registration customised for the challenges unique to scanned microscope data specifically addressing the issues of low-SNR data, images containing a large proportion of crystalline material and/or local features of interest such as dislocations or edges. Careful attention has been paid to artefact testing of the non-rigid registration method used, and the importance of this registration for the quantitative interpretation of feature intensities and positions is evaluated.« less

Improving the precision of dynamic forest parameter estimates using Landsat

Treesearch

Evan B. Brooks; John W. Coulston; Randolph H. Wynne; Valerie A. Thomas

2016-01-01

The use of satellite-derived classification maps to improve post-stratified forest parameter estimates is wellestablished.When reducing the variance of post-stratification estimates for forest change parameters such as forestgrowth, it is logical to use a change-related strata map. At the stand level, a time series of Landsat images is

Monitoring rangeland dynamics in Senegal with advanced very high resolution radiometer data

USGS Publications Warehouse

Tappan, G. Gray; Tyler, Dean J.; Wehde, M. E.; Moore, Donald G.

1992-01-01

Time‐series Normalized Difference Vegetation Index (NDVI) data, computed from Advanced Very High Resolution Radiometer data, are being used by regional and national programs in the African Sahel to monitor seasonal rangeland conditions. The data are often used as indicators of grazing conditions and drought. However, distinguishing rangelands from other vegetation cover types on NDVI images is difficult. A second complication is that rangeland types and their associated productivity vary geographically by soil type. To effectively assess rangeland conditions, seasonal fluctuations (due to climatic cycles) must be isolated from long‐term production characteristics associated with vegetation type and soil differences. Rangeland NDVI dynamics, including qualitative assessments of rangeland production, and the timing and length of the growing season in Senegal were examined by using 7.4‐km global area coverage satellite data. Analyses were based on 10‐day NDVI composite image data from 1982 through 1989. The NDVI image data were stratified by rangeland and soil polygons derived from locally available resource maps. Time‐series NDVI statistics were calculated from the resource polygons that had been interpreted into high, medium, and low production rangelands. Analysts monitoring rangeland conditions can better identify seasonal anomalies such as drought by comparing production potential within homogeneous; resource polygons with the current NDVI data.

Voxel-Wise Time-Series Analysis of Quantitative MRI in Relapsing-Remitting MS: Dynamic Imaging Metrics of Disease Activity Including Pre-Lesional Changes

DTIC Science & Technology

2015-12-01

other parameters match the previous simulation. A third simulation was performed to evaluate the effect of gradient and RF spoiling on the accuracy of...this increase also offers an opportunity to increase the length of the spoiler gradient and improve the accuracy of FA quanti - fication (27). To...Relaxation Pouria Mossahebi,1 Vasily L. Yarnykh,2 and Alexey Samsonov3* Purpose: Cross-relaxation imaging (CRI) is a family of quanti - tative

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery.

PubMed

Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L

2016-12-01

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques. Copyright © 2016 Elsevier Inc. All rights reserved.

Context-dependent JPEG backward-compatible high-dynamic range image compression

NASA Astrophysics Data System (ADS)

Korshunov, Pavel; Ebrahimi, Touradj

2013-10-01

High-dynamic range (HDR) imaging is expected, together with ultrahigh definition and high-frame rate video, to become a technology that may change photo, TV, and film industries. Many cameras and displays capable of capturing and rendering both HDR images and video are already available in the market. The popularity and full-public adoption of HDR content is, however, hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of low-dynamic range (LDR) displays that are unable to render HDR. To facilitate the wide spread of HDR usage, the backward compatibility of HDR with commonly used legacy technologies for storage, rendering, and compression of video and images are necessary. Although many tone-mapping algorithms are developed for generating viewable LDR content from HDR, there is no consensus of which algorithm to use and under which conditions. We, via a series of subjective evaluations, demonstrate the dependency of the perceptual quality of the tone-mapped LDR images on the context: environmental factors, display parameters, and image content itself. Based on the results of subjective tests, it proposes to extend JPEG file format, the most popular image format, in a backward compatible manner to deal with HDR images also. An architecture to achieve such backward compatibility with JPEG is proposed. A simple implementation of lossy compression demonstrates the efficiency of the proposed architecture compared with the state-of-the-art HDR image compression.

Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study.

PubMed

Olejarczyk, Elzbieta

2007-01-01

Functional magnetic resonance imaging (fMRI) allows to investigate the amplitude of activation in neural networks of brain. In this work we present the results of fMRI time-series analysis performed to identify the process of dysregulation of dynamic interaction between different limbic system regions in healthy adults in state of increased anxiety. The results obtain for 65 healthy adults using nonlinear dynamics methods like fractal dimension confirm the key roles of the bilateral amygdala, bilateral hippocampus, BA9 (dorsolateral prefrontal cortex), and BA45 (ventromedial prefrontal cortex) in modulating emotional response in healthy adults. For different regions of interest (ROIs) significant correlations were found not only for the neutral respective rest but also for fear and angry contrasts.

From fuzzy recurrence plots to scalable recurrence networks of time series

NASA Astrophysics Data System (ADS)

Pham, Tuan D.

2017-04-01

Recurrence networks, which are derived from recurrence plots of nonlinear time series, enable the extraction of hidden features of complex dynamical systems. Because fuzzy recurrence plots are represented as grayscale images, this paper presents a variety of texture features that can be extracted from fuzzy recurrence plots. Based on the notion of fuzzy recurrence plots, defuzzified, undirected, and unweighted recurrence networks are introduced. Network measures can be computed for defuzzified recurrence networks that are scalable to meet the demand for the network-based analysis of big data.

Dynamic contrast enhanced CT in nodule characterization: How we review and report.

PubMed

Qureshi, Nagmi R; Shah, Andrew; Eaton, Rosemary J; Miles, Ken; Gilbert, Fiona J

2016-07-18

Incidental indeterminate solitary pulmonary nodules (SPN) that measure less than 3 cm in size are an increasingly common finding on computed tomography (CT) worldwide. Once identified there are a number of imaging strategies that can be performed to help with nodule characterization. These include interval CT, dynamic contrast enhanced computed tomography (DCE-CT), (18)F-fluorodeoxyglucose positron emission tomography-computed tomography ((18)F-FDG-PET-CT). To date the most cost effective and efficient non-invasive test or combination of tests for optimal nodule characterization has yet to be determined.DCE-CT is a functional test that involves the acquisition of a dynamic series of images of a nodule before and following the administration of intravenous iodinated contrast medium. This article provides an overview of the current indications and limitations of DCE- CT in nodule characterization and a systematic approach to how to perform, analyse and interpret a DCE-CT scan.

PF-AR NW14, a new time-resolved diffraction/scattering beamline

NASA Astrophysics Data System (ADS)

Nozawa, Shunsuke; Adachi, Shin-ichi; Tazaki, Ryoko; Takahashi, Jun-ichi; Itatani, Jiro; Daimon, Masahiro; Mori, Takeharu; Sawa, Hiroshi; Kawata, Hiroshi; Koshihara, Shin-ya

2005-01-01

NW14 is a new insertion device beamline at the Photon Factory Advanced Ring (PF-AR), which is a unique ring with full-time single-bunched operation, aiming for timeresolved x-ray diffraction/scattering and XAFS experiments. The primary scientific goal of this beamline is to observe the ultrafast dynamics of condensed matter systems such as organic and inorganic crystals, biological systems and liquids triggered by optical pulses. With the large photon fluxes derived from the undulator, it should become possible to take a snapshoot an atomic-scale image of the electron density distribution. By combining a series of images it is possible to produce a movie of the photo-induced dynamics with 50-ps resolution. The construction of the beamline is being funded by the ERATO Koshihara Non-equilibrium Dynamics Project of the Japan Science and Technology Agency (JST), and the beamline will be operational from autumn 2005.

High order magnetic optics for high dynamic range proton radiography at a kinetic energy 800 MeV

DOE PAGES

Sjue, Sky K. L.; Morris, Christopher L.; Merrill, Frank Edward; ...

2016-01-14

Flash radiography with 800 MeV kinetic energy protons at Los Alamos National Laboratory is an important experimental tool for investigations of dynamic material behavior driven by high explosives or pulsed power. The extraction of quantitative information about density fields in a dynamic experiment from proton generated images requires a high fidelity model of the protonimaging process. It is shown that accurate calculations of the transmission through the magnetic lens system require terms beyond second order for protons far from the tune energy. The approach used integrates the correlated multiple Coulomb scattering distribution simultaneously over the collimator and the image plane.more » Furthermore, comparison with a series of static calibrationimages demonstrates the model’s accurate reproduction of both the transmission and blur over a wide range of tune energies in an inverse identity lens that consists of four quadrupole electromagnets.« less

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

Soft X-ray spectromicroscopy using ptychography with randomly phased illumination

NASA Astrophysics Data System (ADS)

Maiden, A. M.; Morrison, G. R.; Kaulich, B.; Gianoncelli, A.; Rodenburg, J. M.

2013-04-01

Ptychography is a form of scanning diffractive imaging that can successfully retrieve the modulus and phase of both the sample transmission function and the illuminating probe. An experimental difficulty commonly encountered in diffractive imaging is the large dynamic range of the diffraction data. Here we report a novel ptychographic experiment using a randomly phased X-ray probe to considerably reduce the dynamic range of the recorded diffraction patterns. Images can be reconstructed reliably and robustly from this setup, even when scatter from the specimen is weak. A series of ptychographic reconstructions at X-ray energies around the L absorption edge of iron demonstrates the advantages of this method for soft X-ray spectromicroscopy, which can readily provide chemical sensitivity without the need for optical refocusing. In particular, the phase signal is in perfect registration with the modulus signal and provides complementary information that can be more sensitive to changes in the local chemical environment.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

NASA Astrophysics Data System (ADS)

Brandt, C.; Thakur, S. C.; Tynan, G. R.

2016-04-01

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculations are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

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

Brandt, C.; Max-Planck-Institute for Plasma Physics, Wendelsteinstr. 1, D-17491 Greifswald; Thakur, S. C.

2016-04-15

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculationsmore » are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.« less

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

NASA Astrophysics Data System (ADS)

Adami, Marcos; Bernardes, Sérgio; Arai, Egidio; Freitas, Ramon M.; Shimabukuro, Yosio E.; Espírito-Santo, Fernando D. B.; Rudorff, Bernardo F. T.; Anderson, Liana O.

2018-07-01

The development, implementation and enforcement of policies involving the rational use of the land and the conservation of natural resources depend on an adequate characterization and understanding of the land cover, including its dynamics. This paper presents an approach for monitoring vegetation dynamics using high-quality time series of MODIS surface reflectance data by generating fraction images using Linear Spectral Mixing Model (LSMM) over South America continent. The approach uses physically-based fraction images, which highlight target information and reduce data dimensionality. Further dimensionality was also reduced by using the vegetation fraction images as input to a Principal Component Analysis (PCA). The RGB composite of the first three PCA components, accounting for 92.9% of the dataset variability, showed good agreement with the main ecological regions of South America continent. The analysis of 21 temporal profiles of vegetation fraction values and precipitation data over South America showed the ability of vegetation fractions to represent phenological cycles over a variety of environments. Comparisons between vegetation fractions and precipitation data indicated the close relationship between water availability and leaf mass/chlorophyll content for several vegetation types. In addition, phenological changes and disturbance resulting from anthropogenic pressure were identified, particularly those associated with agricultural practices and forest removal. Therefore the proposed method supports the management of natural and non-natural ecosystems, and can contribute to the understanding of key conservation issues in South America, including deforestation, disturbance and fire occurrence and management.

A wireless handheld probe with spectrally constrained evolution strategies for diffuse optical imaging of tissue

NASA Astrophysics Data System (ADS)

Flexman, M. L.; Kim, H. K.; Stoll, R.; Khalil, M. A.; Fong, C. J.; Hielscher, A. H.

2012-03-01

We present a low-cost, portable, wireless diffuse optical imaging device. The handheld device is fast, portable, and can be applied to a wide range of both static and dynamic imaging applications including breast cancer, functional brain imaging, and peripheral artery disease. The continuous-wave probe has four near-infrared wavelengths and uses digital detection techniques to perform measurements at 2.3 Hz. Using a multispectral evolution algorithm for chromophore reconstruction, we can measure absolute oxygenated and deoxygenated hemoglobin concentration as well as scattering in tissue. Performance of the device is demonstrated using a series of liquid phantoms comprised of Intralipid®, ink, and dye.

Modeling Carbon Exchange

NASA Technical Reports Server (NTRS)

Sellers, Piers

2012-01-01

Model results will be reviewed to assess different methods for bounding the terrestrial role in the global carbon cycle. It is proposed that a series of climate model runs could be scoped that would tighten the limits on the "missing sink" of terrestrial carbon and could also direct future satellite image analyses to search for its geographical location and understand its seasonal dynamics.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

NASA Astrophysics Data System (ADS)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

Image registration and analysis for quantitative myocardial perfusion: application to dynamic circular cardiac CT.

PubMed

Isola, A A; Schmitt, H; van Stevendaal, U; Begemann, P G; Coulon, P; Boussel, L; Grass, M

2011-09-21

Large area detector computed tomography systems with fast rotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively, ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce x-ray dose and limit motion artefacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occur due to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image-based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in this contribution. After circular cone-beam CT reconstruction of cardiac volumes covering large areas of the myocardial tissue, the complete series is aligned with respect to a chosen reference volume. The results of the registration process and the perfusion analysis with and without registration are evaluated quantitatively in this paper. The spatial alignment leads to improved quantification of myocardial perfusion for three different pig data sets.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

USGS Publications Warehouse

Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.

2016-01-01

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

A JPEG backward-compatible HDR image compression

NASA Astrophysics Data System (ADS)

Korshunov, Pavel; Ebrahimi, Touradj

2012-10-01

High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularity and full public adoption of HDR content is however hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of Low Dynamic Range (LDR) displays that are unable to render HDR. To facilitate wide spread of HDR usage, the backward compatibility of HDR technology with commonly used legacy image storage, rendering, and compression is necessary. Although many tone-mapping algorithms were developed for generating viewable LDR images from HDR content, there is no consensus on which algorithm to use and under which conditions. This paper, via a series of subjective evaluations, demonstrates the dependency of perceived quality of the tone-mapped LDR images on environmental parameters and image content. Based on the results of subjective tests, it proposes to extend JPEG file format, as the most popular image format, in a backward compatible manner to also deal with HDR pictures. To this end, the paper provides an architecture to achieve such backward compatibility with JPEG and demonstrates efficiency of a simple implementation of this framework when compared to the state of the art HDR image compression.

CCD high-speed videography system with new concepts and techniques

NASA Astrophysics Data System (ADS)

Zheng, Zengrong; Zhao, Wenyi; Wu, Zhiqiang

1997-05-01

A novel CCD high speed videography system with brand-new concepts and techniques is developed by Zhejiang University recently. The system can send a series of short flash pulses to the moving object. All of the parameters, such as flash numbers, flash durations, flash intervals, flash intensities and flash colors, can be controlled according to needs by the computer. A series of moving object images frozen by flash pulses, carried information of moving object, are recorded by a CCD video camera, and result images are sent to a computer to be frozen, recognized and processed with special hardware and software. Obtained parameters can be displayed, output as remote controlling signals or written into CD. The highest videography frequency is 30,000 images per second. The shortest image freezing time is several microseconds. The system has been applied to wide fields of energy, chemistry, medicine, biological engineering, aero- dynamics, explosion, multi-phase flow, mechanics, vibration, athletic training, weapon development and national defense engineering. It can also be used in production streamline to carry out the online, real-time monitoring and controlling.

Towards understanding temporal and spatial dynamics of seagrass landscapes using time-series remote sensing

NASA Astrophysics Data System (ADS)

Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.

2013-03-01

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Design and implementation of the flight dynamics system for COMS satellite mission operations

NASA Astrophysics Data System (ADS)

Lee, Byoung-Sun; Hwang, Yoola; Kim, Hae-Yeon; Kim, Jaehoon

2011-04-01

The first Korean multi-mission geostationary Earth orbit satellite, Communications, Ocean, and Meteorological Satellite (COMS) was launched by an Ariane 5 launch vehicle in June 26, 2010. The COMS satellite has three payloads including Ka-band communications, Geostationary Ocean Color Imager, and Meteorological Imager. Although the COMS spacecraft bus is based on the Astrium Eurostar 3000 series, it has only one solar array to the south panel because all of the imaging sensors are located on the north panel. In order to maintain the spacecraft attitude with 5 wheels and 7 thrusters, COMS should perform twice a day wheel off-loading thruster firing operations, which affect on the satellite orbit. COMS flight dynamics system provides the general on-station functions such as orbit determination, orbit prediction, event prediction, station-keeping maneuver planning, station-relocation maneuver planning, and fuel accounting. All orbit related functions in flight dynamics system consider the orbital perturbations due to wheel off-loading operations. There are some specific flight dynamics functions to operate the spacecraft bus such as wheel off-loading management, oscillator updating management, and on-station attitude reacquisition management. In this paper, the design and implementation of the COMS flight dynamics system is presented. An object oriented analysis and design methodology is applied to the flight dynamics system design. Programming language C# within Microsoft .NET framework is used for the implementation of COMS flight dynamics system on Windows based personal computer.

Inversion of deformation fields time-series from optical images, application to the long term kinematics of slow-moving landslides

NASA Astrophysics Data System (ADS)

Bontemps, Noélie; Lacroix, Pascal; Doin, Marie-Pierre

2017-04-01

Slow-moving landslides are one of the major risks in mountainous areas. They are the cause of a lot of damages, both material and human as they can at any time exhibit sudden acceleration phases and flows that are generally difficult to predict. Landslide kinematic is driven by, inter alia, precipitation and water infiltration, river erosion, earthquakes and human activities. Complex interactions have been observed between climatic forcing and earthquakes. However, observations of these complex interactions on slow-moving landslides are very few, restricting the comprehension that we have on involved mechanisms. In this context, it is necessary to monitor slow-moving landslides over time. We propose to answer this problematic by studying slow-moving landslides over a long time period in the Colca valley, Peru, affected by both earthquakes and rainfalls. We will base our study on the 30-years long SPOT1-7/Pleiades archive, that confronts us with (1) low dynamic of images, (2) difference of pixel resolution between all acquired images and (3) long time span in between images leading to ground surface changes. To overcome these three limitations, this study proposes an adaptation to optical images of a method originally used for InSAR time-series analysis. This method uses the full redundancy of information to derive robust time-series of displacement from deformation fields. The retrieved displacement time-series obtained on the three largest landslides of the area are robust and coherent in time. The developed method allows decreasing the displacement uncertainties by approximately 25%. Eventually, we discuss the impact of the different forcing on the three main landslides of the region.

Groupwise Image Registration Guided by a Dynamic Digraph of Images.

PubMed

Tang, Zhenyu; Fan, Yong

2016-04-01

For groupwise image registration, graph theoretic methods have been adopted for discovering the manifold of images to be registered so that accurate registration of images to a group center image can be achieved by aligning similar images that are linked by the shortest graph paths. However, the image similarity measures adopted to build a graph of images in the extant methods are essentially pairwise measures, not effective for capturing the groupwise similarity among multiple images. To overcome this problem, we present a groupwise image similarity measure that is built on sparse coding for characterizing image similarity among all input images and build a directed graph (digraph) of images so that similar images are connected by the shortest paths of the digraph. Following the shortest paths determined according to the digraph, images are registered to a group center image in an iterative manner by decomposing a large anatomical deformation field required to register an image to the group center image into a series of small ones between similar images. During the iterative image registration, the digraph of images evolves dynamically at each iteration step to pursue an accurate estimation of the image manifold. Moreover, an adaptive dictionary strategy is adopted in the groupwise image similarity measure to ensure fast convergence of the iterative registration procedure. The proposed method has been validated based on both simulated and real brain images, and experiment results have demonstrated that our method was more effective for learning the manifold of input images and achieved higher registration accuracy than state-of-the-art groupwise image registration methods.

Modeling urban expansion in Yangon, Myanmar using Landsat time-series and stereo GeoEye Images

NASA Astrophysics Data System (ADS)

Sritarapipat, Tanakorn; Takeuchi, Wataru

2016-06-01

This research proposed a methodology to model the urban expansion based dynamic statistical model using Landsat and GeoEye Images. Landsat Time-Series from 1978 to 2010 have been applied to extract land covers from the past to the present. Stereo GeoEye Images have been employed to obtain the height of the building. The class translation was obtained by observing land cover from the past to the present. The height of the building can be used to detect the center of the urban area (mainly commercial area). It was assumed that the class translation and the distance of multi-centers of the urban area also the distance of the roads affect the urban growth. The urban expansion model based on the dynamic statistical model was defined to refer to three factors; (1) the class translation, (2) the distance of the multicenters of the urban areas, and (3) the distance from the roads. Estimation and prediction of urban expansion by using our model were formulated and expressed in this research. The experimental area was set up in Yangon, Myanmar. Since it is the major of country's economic with more than five million population and the urban areas have rapidly increased. The experimental results indicated that our model of urban expansion estimated urban growth in both estimation and prediction steps in efficiency.

Poisson-event-based analysis of cell proliferation.

PubMed

Summers, Huw D; Wills, John W; Brown, M Rowan; Rees, Paul

2015-05-01

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry.

Local/non-local regularized image segmentation using graph-cuts: application to dynamic and multispectral MRI.

PubMed

Hanson, Erik A; Lundervold, Arvid

2013-11-01

Multispectral, multichannel, or time series image segmentation is important for image analysis in a wide range of applications. Regularization of the segmentation is commonly performed using local image information causing the segmented image to be locally smooth or piecewise constant. A new spatial regularization method, incorporating non-local information, was developed and tested. Our spatial regularization method applies to feature space classification in multichannel images such as color images and MR image sequences. The spatial regularization involves local edge properties, region boundary minimization, as well as non-local similarities. The method is implemented in a discrete graph-cut setting allowing fast computations. The method was tested on multidimensional MRI recordings from human kidney and brain in addition to simulated MRI volumes. The proposed method successfully segment regions with both smooth and complex non-smooth shapes with a minimum of user interaction.

Using landsat time-series and lidar to inform aboveground carbon baseline estimation in Minnesota

Treesearch

Ram K. Deo; Grant M. Domke; Matthew B. Russell; Christopher W. Woodall; Michael J. Falkowski

2015-01-01

Landsat data has long been used to support forest monitoring and management decisions despite the limited success of passive optical remote sensing for accurate estimation of structural attributes such as aboveground biomass. The archive of publicly available Landsat images dating back to the 1970s can be used to predict historic forest biomass dynamics. In addition,...

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

Treesearch

Qingyuan Zhang; Xiangming Xiao; Bobby Braswell; Ernst Linder; Scott Ollinger; Marie-Louise Smith; Julian P. Jenkins; Fred Baret; Andrew D. Richardson; Berrien III Moore; Rakesh Minocha

2006-01-01

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface...

Voyager 1 Jupiter Southern Hemisphere Movie

NASA Technical Reports Server (NTRS)

2000-01-01

This movie shows a portion of Jupiter in the southern hemisphere over 17Jupiter days. Above the white belt, notice the series of atmospheric vortices headed west. Even these early approach frames show wild dynamics in the roiling environment south of the white belt. Notice the small tumbling white cloud near the center.

As Voyager 1 approached Jupiter in 1979, it took images of the planet at regular intervals. This sequence is made from 17 images taken once every Jupiter rotation period (about 10 hours). These images were acquired in the Blue filter around Feb. 1, 1979. The spacecraft was about 37 million kilometers from Jupiter at that time.

This time-lapse movie was produced at JPL by the Image Processing Laboratory in 1979.

Cardiac function and perfusion dynamics measured on a beat-by-beat basis in the live mouse using ultra-fast 4D optoacoustic imaging

NASA Astrophysics Data System (ADS)

Ford, Steven J.; Deán-Ben, Xosé L.; Razansky, Daniel

2015-03-01

The fast heart rate (~7 Hz) of the mouse makes cardiac imaging and functional analysis difficult when studying mouse models of cardiovascular disease, and cannot be done truly in real-time and 3D using established imaging modalities. Optoacoustic imaging, on the other hand, provides ultra-fast imaging at up to 50 volumetric frames per second, allowing for acquisition of several frames per mouse cardiac cycle. In this study, we combined a recently-developed 3D optoacoustic imaging array with novel analytical techniques to assess cardiac function and perfusion dynamics of the mouse heart at high, 4D spatiotemporal resolution. In brief, the heart of an anesthetized mouse was imaged over a series of multiple volumetric frames. In another experiment, an intravenous bolus of indocyanine green (ICG) was injected and its distribution was subsequently imaged in the heart. Unique temporal features of the cardiac cycle and ICG distribution profiles were used to segment the heart from background and to assess cardiac function. The 3D nature of the experimental data allowed for determination of cardiac volumes at ~7-8 frames per mouse cardiac cycle, providing important cardiac function parameters (e.g., stroke volume, ejection fraction) on a beat-by-beat basis, which has been previously unachieved by any other cardiac imaging modality. Furthermore, ICG distribution dynamics allowed for the determination of pulmonary transit time and thus additional quantitative measures of cardiovascular function. This work demonstrates the potential for optoacoustic cardiac imaging and is expected to have a major contribution toward future preclinical studies of animal models of cardiovascular health and disease.

Fast Atomic-Scale Chemical Imaging of Crystalline Materials and Dynamic Phase Transformations.

PubMed

Lu, Ping; Yuan, Ren Liang; Ihlefeld, Jon F; Spoerke, Erik David; Pan, Wei; Zuo, Jian Min

2016-04-13

Atomic-scale phenomena fundamentally influence materials form and function that makes the ability to locally probe and study these processes critical to advancing our understanding and development of materials. Atomic-scale chemical imaging by scanning transmission electron microscopy (STEM) using energy-dispersive X-ray spectroscopy (EDS) is a powerful approach to investigate solid crystal structures. Inefficient X-ray emission and collection, however, require long acquisition times (typically hundreds of seconds), making the technique incompatible with electron-beam sensitive materials and study of dynamic material phenomena. Here we describe an atomic-scale STEM-EDS chemical imaging technique that decreases the acquisition time to as little as one second, a reduction of more than 100 times. We demonstrate this new approach using LaAlO3 single crystal and study dynamic phase transformation in beam-sensitive Li[Li0.2Ni0.2Mn0.6]O2 (LNMO) lithium ion battery cathode material. By capturing a series of time-lapsed chemical maps, we show for the first time clear atomic-scale evidence of preferred Ni-mobility in LNMO transformation, revealing new kinetic mechanisms. These examples highlight the potential of this approach toward temporal, atomic-scale mapping of crystal structure and chemistry for investigating dynamic material phenomena.

Mapping the dynamics of juniper forest encroachment into grasslands during 1984-2010 based on PALSAR and Landsat images

NASA Astrophysics Data System (ADS)

Wang, J.; Xiao, X.; Qin, Y.; Dong, J.

2016-12-01

Juniper species widely encroaching into native grasslands has negatively affected the production of forage and livestock, wildlife habitats, and altered the water, carbon, nutrient and biogeochemical cycles. However, time series of juniper maps are not available across landscape, watershed and regional scales to facilitate these studies. This study examined the dynamics of juniper forest encroachment into native grasslands in Oklahoma using a pixel and phenology-based algorithm based on PALSAR mosaic data in 2010 and 10,871 Landsat 5/7 images during 1984-2010. The juniper forest maps in 2010 and five historical epochs: the late 1980s (1984-1989), early 1990s (1990-1994), late 1990s (1995-1999), early 2000s (2000-2004), and late 2000s (2005-2010) were generated. We analyzed the area dynamics at various spatial scales of state, county and geographic regions. This study found that (1) the juniper forest expanded to the northwest of Oklahoma at an annual rate of 5% during 1984-2010; (2) the geographic distribution of juniper forest has notable spatial heterogeneity, varies from one county to another; (3) the area of the juniper forest has the most significant increase in the northwestern counties, and (4) stand age analysis suggested that 65% juniper forests in Oklahoma are young with forest stand age less than 15 years. This practice at the state level demonstrated the potential to trace back the juniper encroachment into the grasslands using time series Landsat images and PALSAR data. The resultant maps can be used to support studies on the driving factors and consequences, and future estimates of the juniper forest encroachment.

Lung parenchymal analysis on dynamic MRI in thoracic insufficiency syndrome to assess changes following surgical intervention

NASA Astrophysics Data System (ADS)

Jagadale, Basavaraj N.; Udupa, Jayaram K.; Tong, Yubing; Wu, Caiyun; McDonough, Joseph; Torigian, Drew A.; Campbell, Robert M.

2018-02-01

General surgeons, orthopedists, and pulmonologists individually treat patients with thoracic insufficiency syndrome (TIS). The benefits of growth-sparing procedures such as Vertical Expandable Prosthetic Titanium Rib (VEPTR)insertionfor treating patients with TIS have been demonstrated. However, at present there is no objective assessment metricto examine different thoracic structural components individually as to their roles in the syndrome, in contributing to dynamics and function, and in influencing treatment outcome. Using thoracic dynamic MRI (dMRI), we have been developing a methodology to overcome this problem. In this paper, we extend this methodology from our previous structural analysis approaches to examining lung tissue properties. We process the T2-weighted dMRI images through a series of steps involving 4D image construction of the acquired dMRI images, intensity non-uniformity correction and standardization of the 4D image, lung segmentation, and estimation of the parameters describing lung tissue intensity distributions in the 4D image. Based on pre- and post-operative dMRI data sets from 25 TIS patients (predominantly neuromuscular and congenital conditions), we demonstrate how lung tissue can be characterized by the estimated distribution parameters. Our results show that standardized T2-weighted image intensity values decrease from the pre- to post-operative condition, likely reflecting improved lung aeration post-operatively. In both pre- and post-operative conditions, the intensity values decrease also from end-expiration to end-inspiration, supporting the basic premise of our results.

Sea ice type dynamics in the Arctic based on Sentinel-1 Data

NASA Astrophysics Data System (ADS)

Babiker, Mohamed; Korosov, Anton; Park, Jeong-Won

2017-04-01

Sea ice observation from satellites has been carried out for more than four decades and is one of the most important applications of EO data in operational monitoring as well as in climate change studies. Several sensors and retrieval methods have been developed and successfully utilized to measure sea ice area, concentration, drift, type, thickness, etc [e.g. Breivik et al., 2009]. Today operational sea ice monitoring and analysis is fully dependent on use of satellite data. However, new and improved satellite systems, such as multi-polarisation Synthetic Apperture Radar (SAR), require further studies to develop more advanced and automated sea ice monitoring methods. In addition, the unprecedented volume of data available from recently launched Sentinel missions provides both challenges and opportunities for studying sea ice dynamics. In this study we investigate sea ice type dynamics in the Fram strait based on Sentinel-1 A, B SAR data. Series of images for the winter season are classified into 4 ice types (young ice, first year ice, multiyear ice and leads) using the new algorithm developed by us for sea ice classification, which is based on segmentation, GLCM calculation, Haralick texture feature extraction, unsupervised and supervised classifications and Support Vector Machine (SVM) [Zakhvatkina et al., 2016; Korosov et al., 2016]. This algorithm is further improved by applying thermal and scalloping noise removal [Park et al. 2016]. Sea ice drift is retrieved from the same series of Sentinel-1 images using the newly developed algorithm based on combination of feature tracking and pattern matching [Mukenhuber et al., 2016]. Time series of these two products (sea ice type and sea ice drift) are combined in order to study sea ice deformation processes at small scales. Zones of sea ice convergence and divergence identified from sea ice drift are compared with ridges and leads identified from texture features. That allows more specific interpretation of SAR imagery and more accurate automatic classification. In addition, the map of four ice types calculated using the texture features from one SAR image is propagated forward using the sea ice drift vectors. The propagated ice type is compared with ice type derived from the next image. The comparison identifies changes in ice type which occurred during drift and allows to reduce uncertainties in sea ice type calculation.

Cluster analysis of dynamic contrast enhanced MRI reveals tumor subregions related to locoregional relapse for cervical cancer patients.

PubMed

Torheim, Turid; Groendahl, Aurora R; Andersen, Erlend K F; Lyng, Heidi; Malinen, Eirik; Kvaal, Knut; Futsaether, Cecilia M

2016-11-01

Solid tumors are known to be spatially heterogeneous. Detection of treatment-resistant tumor regions can improve clinical outcome, by enabling implementation of strategies targeting such regions. In this study, K-means clustering was used to group voxels in dynamic contrast enhanced magnetic resonance images (DCE-MRI) of cervical cancers. The aim was to identify clusters reflecting treatment resistance that could be used for targeted radiotherapy with a dose-painting approach. Eighty-one patients with locally advanced cervical cancer underwent DCE-MRI prior to chemoradiotherapy. The resulting image time series were fitted to two pharmacokinetic models, the Tofts model (yielding parameters K trans and ν e ) and the Brix model (A Brix , k ep and k el ). K-means clustering was used to group similar voxels based on either the pharmacokinetic parameter maps or the relative signal increase (RSI) time series. The associations between voxel clusters and treatment outcome (measured as locoregional control) were evaluated using the volume fraction or the spatial distribution of each cluster. One voxel cluster based on the RSI time series was significantly related to locoregional control (adjusted p-value 0.048). This cluster consisted of low-enhancing voxels. We found that tumors with poor prognosis had this RSI-based cluster gathered into few patches, making this cluster a potential candidate for targeted radiotherapy. None of the voxels clusters based on Tofts or Brix parameter maps were significantly related to treatment outcome. We identified one group of tumor voxels significantly associated with locoregional relapse that could potentially be used for dose painting. This tumor voxel cluster was identified using the raw MRI time series rather than the pharmacokinetic maps.

Imaging dynamic fingerprints of competing E2 and SN2 reactions.

PubMed

Carrascosa, Eduardo; Meyer, Jennifer; Zhang, Jiaxu; Stei, Martin; Michaelsen, Tim; Hase, William L; Yang, Li; Wester, Roland

2017-06-21

The competition between bimolecular nucleophilic substitution and base-induced elimination is of fundamental importance for the synthesis of pure samples in organic chemistry. Many factors that influence this competition have been identified over the years, but the underlying atomistic dynamics have remained difficult to observe. We present product velocity distributions for a series of reactive collisions of the type X -  + RY with X and Y denoting the halogen atoms fluorine, chlorine and iodine. By increasing the size of the residue R from methyl to tert-butyl in several steps, we find that the dynamics drastically change from backward to dominant forward scattering of the leaving ion relative to the reactant RY velocity. This characteristic fingerprint is also confirmed by direct dynamics simulations for ethyl as residue and attributed to the dynamics of elimination reactions. This work opens the door to a detailed atomistic understanding of transformation reactions in even larger systems.The competition between chemical reactions critically affects our natural environment and the synthesis of new materials. Here, the authors present an approach to directly image distinct fingerprints of essential organic reactions and monitor their competition as a function of steric substitution.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

NASA Astrophysics Data System (ADS)

Chiang, Y.; Chen, K.

2013-12-01

This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

Dynamic laser beam shaping for material processing using hybrid holograms

NASA Astrophysics Data System (ADS)

Liu, Dun; Wang, Yutao; Zhai, Zhongsheng; Fang, Zheng; Tao, Qing; Perrie, Walter; Edwarson, Stuart P.; Dearden, Geoff

2018-06-01

A high quality, dynamic laser beam shaping method is demonstrated by displaying a series of hybrid holograms onto a spatial light modulator (SLM), while each one of the holograms consists of a binary grating and a geometric mask. A diffraction effect around the shaped beam has been significantly reduced. Beam profiles of arbitrary shape, such as square, ring, triangle, pentagon and hexagon, can be conveniently obtained by loading the corresponding holograms on the SLM. The shaped beam can be reconstructed in the range of 0.5 mm at the image plane. Ablation on a polished stainless steel sample at the image plane are consistent with the beam shape at the diffraction near-field. The ±1st order and higher order beams can be completely removed when the grating period is smaller than 160 μm. The local energy ratio of the shaped beam observed by the CCD camera is up to 77.67%. Dynamic processing at 25 Hz using different shapes has also been achieved.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction

NASA Astrophysics Data System (ADS)

Minitti, M. P.; Budarz, J. M.; Kirrander, A.; Robinson, J. S.; Ratner, D.; Lane, T. J.; Zhu, D.; Glownia, J. M.; Kozina, M.; Lemke, H. T.; Sikorski, M.; Feng, Y.; Nelson, S.; Saita, K.; Stankus, B.; Northey, T.; Hastings, J. B.; Weber, P. M.

2015-06-01

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction.

PubMed

Minitti, M P; Budarz, J M; Kirrander, A; Robinson, J S; Ratner, D; Lane, T J; Zhu, D; Glownia, J M; Kozina, M; Lemke, H T; Sikorski, M; Feng, Y; Nelson, S; Saita, K; Stankus, B; Northey, T; Hastings, J B; Weber, P M

2015-06-26

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

Dynamic Black-Level Correction and Artifact Flagging for Kepler Pixel Time Series

NASA Technical Reports Server (NTRS)

Kolodziejczak, J. J.; Clarke, B. D.; Caldwell, D. A.

2011-01-01

Methods applied to the calibration stage of Kepler pipeline data processing [1] (CAL) do not currently use all of the information available to identify and correct several instrument-induced artifacts. These include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, and manifestations of drifting moire pattern as locally correlated nonstationary noise, and rolling bands in the images which find their way into the time series [2], [3]. As the Kepler Mission continues to improve the fidelity of its science data products, we are evaluating the benefits of adding pipeline steps to more completely model and dynamically correct the FGS crosstalk, then use the residuals from these model fits to detect and flag spatial regions and time intervals of strong time-varying black-level which may complicate later processing or lead to misinterpretation of instrument behavior as stellar activity.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

NASA Astrophysics Data System (ADS)

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-01

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology.

PubMed

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-13

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Ultrafast Bilateral DCE-MRI of the Breast with Conventional Fourier Sampling: Preliminary Evaluation of Semi-quantitative Analysis.

PubMed

Pineda, Federico D; Medved, Milica; Wang, Shiyang; Fan, Xiaobing; Schacht, David V; Sennett, Charlene; Oto, Aytekin; Newstead, Gillian M; Abe, Hiroyuki; Karczmar, Gregory S

2016-09-01

The study aimed to evaluate the feasibility and advantages of a combined high temporal and high spatial resolution protocol for dynamic contrast-enhanced magnetic resonance imaging of the breast. Twenty-three patients with enhancing lesions were imaged at 3T. The acquisition protocol consisted of a series of bilateral, fat-suppressed "ultrafast" acquisitions, with 6.9- to 9.9-second temporal resolution for the first minute following contrast injection, followed by four high spatial resolution acquisitions with 60- to 79.5-second temporal resolution. All images were acquired with standard uniform Fourier sampling. A filtering method was developed to reduce noise and detect significant enhancement in the high temporal resolution images. Time of arrival (TOA) was defined as the time at which each voxel first satisfied all the filter conditions, relative to the time of initial arterial enhancement. Ultrafast images improved visualization of the vasculature feeding and draining lesions. A small percentage of the entire field of view (<6%) enhanced significantly in the 30 seconds following contrast injection. Lesion conspicuity was highest in early ultrafast images, especially in cases with marked parenchymal enhancement. Although the sample size was relatively small, the average TOA for malignant lesions was significantly shorter than the TOA for benign lesions. Significant differences were also measured in other parameters descriptive of early contrast media uptake kinetics (P < 0.05). Ultrafast imaging in the first minute of dynamic contrast-enhanced magnetic resonance imaging of the breast has the potential to add valuable information on early contrast dynamics. Ultrafast imaging could allow radiologists to confidently identify lesions in the presence of marked background parenchymal enhancement. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

PubMed Central

Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2015-01-01

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

NASA Astrophysics Data System (ADS)

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingsong; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Román, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

2017-07-01

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

USGS Publications Warehouse

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingson; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Roman, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

2017-01-01

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Quingsong; Kim, Jihyun; Erb, Angela M.; Gao, Feng; Roman, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.;

Unsupervised and self-mapping category formation and semantic object recognition for mobile robot vision used in an actual environment

NASA Astrophysics Data System (ADS)

Madokoro, H.; Tsukada, M.; Sato, K.

2013-07-01

This paper presents an unsupervised learning-based object category formation and recognition method for mobile robot vision. Our method has the following features: detection of feature points and description of features using a scale-invariant feature transform (SIFT), selection of target feature points using one class support vector machines (OC-SVMs), generation of visual words using self-organizing maps (SOMs), formation of labels using adaptive resonance theory 2 (ART-2), and creation and classification of categories on a category map of counter propagation networks (CPNs) for visualizing spatial relations between categories. Classification results of dynamic images using time-series images obtained using two different-size robots and according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category formation of appearance changes of objects.

Transient Cognitive Dynamics, Metastability, and Decision Making

DTIC Science & Technology

2008-05-02

imaging (fMRI) and EEG have opened new possibilities for understanding and modeling cognition [11–15]. Experimental recordings have revealed detailed...between different phase-synchronized states of alpha activity in spontaneous EEG . Alpha activity has been characterized as a series of globally...novel protocols of assisted neurofeedback [59– 62], which can open a wide variety of new medical and brain- machine applications. Methods Stable

Effects of harvest, fire, and pest/pathogen disturbances on the West Cascades ecoregion carbon balance

Treesearch

David P Turner; William D Ritts; Robert E Kennedy; Andrew N Gray; Zhiqiang Yang

2015-01-01

Background: Disturbance is a key influence on forest carbon dynamics, but the complexity of spatial and temporal patterns in forest disturbance makes it difficult to quantify their impacts on carbon flux over broad spatial domains. Here we used a time series of Landsat remote sensing images and a climate-driven carbon cycle process model to evaluate carbon fluxes at...

Dynamic gadolinium-enhanced magnetic resonance imaging allows accurate assessment of the synovial inflammatory activity in rheumatoid arthritis knee joints: a comparison with synovial histology.

PubMed

Axelsen, M B; Stoltenberg, M; Poggenborg, R P; Kubassova, O; Boesen, M; Bliddal, H; Hørslev-Petersen, K; Hanson, L G; Østergaard, M

2012-03-01

To determine whether dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) evaluated using semi-automatic image processing software can accurately assess synovial inflammation in rheumatoid arthritis (RA) knee joints. In 17 RA patients undergoing knee surgery, the average grade of histological synovial inflammation was determined from four biopsies obtained during surgery. A preoperative series of T(1)-weighted dynamic fast low-angle shot (FLASH) MR images was obtained. Parameters characterizing contrast uptake dynamics, including the initial rate of enhancement (IRE), were generated by the software in three different areas: (I) the entire slice (Whole slice); (II) a manually outlined region of interest (ROI) drawn quickly around the joint, omitting large artefacts such as blood vessels (Quick ROI); and (III) a manually outlined ROI following the synovial capsule of the knee joint (Precise ROI). Intra- and inter-reader agreement was assessed using the intra-class correlation coefficient (ICC). The IRE from the Quick ROI and the Precise ROI revealed high correlations to the grade of histological inflammation (Spearman's correlation coefficient (rho) = 0.70, p = 0.001 and rho = 0.74, p = 0.001, respectively). Intra- and inter-reader ICCs were very high (0.93-1.00). No Whole slice parameters were correlated to histology. DCE-MRI provides fast and accurate assessment of synovial inflammation in RA patients. Manual outlining of the joint to omit large artefacts is necessary.

Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

NASA Astrophysics Data System (ADS)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.

Volumetric Two-photon Imaging of Neurons Using Stereoscopy (vTwINS)

PubMed Central

Song, Alexander; Charles, Adam S.; Koay, Sue Ann; Gauthier, Jeff L.; Thiberge, Stephan Y.; Pillow, Jonathan W.; Tank, David W.

2017-01-01

Two-photon laser scanning microscopy of calcium dynamics using fluorescent indicators is a widely used imaging method for large scale recording of neural activity in vivo. Here we introduce volumetric Two-photon Imaging of Neurons using Stereoscopy (vTwINS), a volumetric calcium imaging method that employs an elongated, V-shaped point spread function to image a 3D brain volume. Single neurons project to spatially displaced “image pairs” in the resulting 2D image, and the separation distance between images is proportional to depth in the volume. To demix the fluorescence time series of individual neurons, we introduce a novel orthogonal matching pursuit algorithm that also infers source locations within the 3D volume. We illustrate vTwINS by imaging neural population activity in mouse primary visual cortex and hippocampus. Our results demonstrate that vTwINS provides an effective method for volumetric two-photon calcium imaging that increases the number of neurons recorded while maintaining a high frame-rate. PMID:28319111

A Dynamic Scheduling Method of Earth-Observing Satellites by Employing Rolling Horizon Strategy

PubMed Central

Dishan, Qiu; Chuan, He; Jin, Liu; Manhao, Ma

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments. PMID:23690742

A dynamic scheduling method of Earth-observing satellites by employing rolling horizon strategy.

PubMed

Dishan, Qiu; Chuan, He; Jin, Liu; Manhao, Ma

2013-01-01

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments.

75 FR 4570 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-28

... applications. Signal-to-Noise Enhancement in Imaging Applications Using a Time-Series of Images Description of... applications that use a time-series of images. In one embodiment of the invention, a time-series of images is... Imaging Applications Using a Time-Series of Images'' (HHS Reference No. E-292- 2009/0-US-01). Related...

Cameras on the NEPTUNE Canada seafloor observatory: Towards monitoring hydrothermal vent ecosystem dynamics

NASA Astrophysics Data System (ADS)

Robert, K.; Matabos, M.; Sarrazin, J.; Sarradin, P.; Lee, R. W.; Juniper, K.

2010-12-01

Hydrothermal vent environments are among the most dynamic benthic habitats in the ocean. The relative roles of physical and biological factors in shaping vent community structure remain unclear. Undersea cabled observatories offer the power and bandwidth required for high-resolution, time-series study of the dynamics of vent communities and the physico-chemical forces that influence them. The NEPTUNE Canada cabled instrument array at the Endeavour hydrothermal vents provides a unique laboratory for researchers to conduct long-term, integrated studies of hydrothermal vent ecosystem dynamics in relation to environmental variability. Beginning in September-October 2010, NEPTUNE Canada (NC) will be deploying a multi-disciplinary suite of instruments on the Endeavour Segment of the Juan de Fuca Ridge. Two camera and sensor systems will be used to study ecosystem dynamics in relation to hydrothermal discharge. These studies will make use of new experimental protocols for time-series observations that we have been developing since 2008 at other observatory sites connected to the VENUS and NC networks. These protocols include sampling design, camera calibration (i.e. structure, position, light, settings) and image analysis methodologies (see communication by Aron et al.). The camera systems to be deployed in the Main Endeavour vent field include a Sidus high definition video camera (2010) and the TEMPO-mini system (2011), designed by IFREMER (France). Real-time data from three sensors (O2, dissolved Fe, temperature) integrated with the TEMPO-mini system will enhance interpretation of imagery. For the first year of observations, a suite of internally recording temperature probes will be strategically placed in the field of view of the Sidus camera. These installations aim at monitoring variations in vent community structure and dynamics (species composition and abundances, interactions within and among species) in response to changes in environmental conditions at different temporal scales. High-resolution time-series studies also provide a mean of studying population dynamics, biological rhythms, organism growth and faunal succession. In addition to programmed time-series monitoring, the NC infrastructure will also permit manual and automated modification of observational protocols in response to natural events. This will enhance our ability to document potentially critical but short-lived environmental forces affecting vent communities.

Cassette Series Designed for Live-Cell Imaging of Proteins and High Resolution Techniques in Yeast

PubMed Central

Young, Carissa L.; Raden, David L.; Caplan, Jeffrey; Czymmek, Kirk; Robinson, Anne S.

2012-01-01

During the past decade, it has become clear that protein function and regulation are highly dependent upon intracellular localization. Although fluorescent protein variants are ubiquitously used to monitor protein dynamics, localization, and abundance; fluorescent light microscopy techniques often lack the resolution to explore protein heterogeneity and cellular ultrastructure. Several approaches have been developed to identify, characterize, and monitor the spatial localization of proteins and complexes at the sub-organelle level; yet, many of these techniques have not been applied to yeast. Thus, we have constructed a series of cassettes containing codon-optimized epitope tags, fluorescent protein variants that cover the full spectrum of visible light, a TetCys motif used for FlAsH-based localization, and the first evaluation in yeast of a photoswitchable variant – mEos2 – to monitor discrete subpopulations of proteins via confocal microscopy. This series of modules, complete with six different selection markers, provides the optimal flexibility during live-cell imaging and multicolor labeling in vivo. Furthermore, high-resolution imaging techniques include the yeast-enhanced TetCys motif that is compatible with diaminobenzidine photooxidation used for protein localization by electron microscopy and mEos2 that is ideal for super-resolution microscopy. We have examined the utility of our cassettes by analyzing all probes fused to the C-terminus of Sec61, a polytopic membrane protein of the endoplasmic reticulum of moderate protein concentration, in order to directly compare fluorescent probes, their utility and technical applications. Our series of cassettes expand the repertoire of molecular tools available to advance targeted spatiotemporal investigations using multiple live-cell, super-resolution or electron microscopy imaging techniques. PMID:22473760

Analysis of strawberry ripening by dynamic speckle measurements

NASA Astrophysics Data System (ADS)

Mulone, C.; Budini, N.; Vincitorio, F. M.; Freyre, C.; López Díaz, A. J.; Ramil Rego, A.

2013-11-01

This work seeks to determine the age of a fruit from observation of its dynamic speckle pattern. A mobile speckle pattern originates on the fruit's surface due to the interference of the wavefronts reflected from moving scatterers. For this work we analyzed two series of photographs of a strawberry speckle pattern, at different stages of ripening, acquired with a CMOS camera. The first day, we took ten photographs at an interval of one second. The same procedure was repeated the next day. From each series of images we extracted several statistical descriptors of pixel-to-pixel gray level variation during the observation time. By comparing these values from the first to the second day we noticed a diminution of the speckle activity. This decay demonstrated that after only one day the ripening process of the strawberry can be detected by dynamic speckle pattern analysis. For this study we employed a simple new algorithm to process the data obtained from the photographs. This algorithm allows defining a global mobility index that indicates the evolution of the fruit's ripening.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

High Resolution Time Series of Plankton Communities: From Early Warning of Harmful Blooms to Sentinels of Climate Change

NASA Astrophysics Data System (ADS)

Sosik, H. M.; Campbell, L.; Olson, R. J.

2016-02-01

The combination of ocean observatory infrastructure and automated submersible flow cytometry provides an unprecedented capability for sustained high resolution time series of plankton, including taxa that are harmful or early indicators of ecosystem response to environmental change. On-going time series produced with the FlowCytobot series of instruments document important ways this challenge is already being met for phytoplankton and microzooplankton. FlowCytobot and Imaging FlowCytobot use a combination of laser-based scattering and fluorescence measurements and video imaging of individual particles to enumerate and characterize cells ranging from picocyanobacteria to large chaining-forming diatoms. Over a decade of observations at the Martha's Vineyard Coastal Observatory (MVCO), a cabled facility on the New England Shelf, have been compiled from repeated instrument deployments, typically 6 months or longer in duration. These multi-year high resolution (hourly to daily) time series are providing new insights into dynamics of community structure such as blooms, seasonality, and multi-year trends linked to regional climate-related variables. Similar observations in Texas coastal waters at the Texas Observatory for Algal Succession Time series (TOAST) have repeatedly provided early warning of harmful algal bloom events that threaten human and ecosystem health. As coastal ocean observing systems mature and expand, the continued integration of these type of detailed observations of the plankton will provide unparalleled information about variability and patterns of change at the base of the marine food webs, with direct implications for informed ecosystem-based management.

The medium and the message: a revisionist view of image quality

NASA Astrophysics Data System (ADS)

Ferwerda, James A.

2010-02-01

In his book "Understanding Media" social theorist Marshall McLuhan declared: "The medium is the message." The thesis of this paper is that with respect to image quality, imaging system developers have taken McLuhan's dictum too much to heart. Efforts focus on improving the technical specifications of the media (e.g. dynamic range, color gamut, resolution, temporal response) with little regard for the visual messages the media will be used to communicate. We present a series of psychophysical studies that investigate the visual system's ability to "see through" the limitations of imaging media to perceive the messages (object and scene properties) the images represent. The purpose of these studies is to understand the relationships between the signal characteristics of an image and the fidelity of the visual information the image conveys. The results of these studies provide a new perspective on image quality that shows that images that may be very different in "quality", can be visually equivalent as realistic representations of objects and scenes.

Image-based characterization of thrombus formation in time-lapse DIC microscopy

PubMed Central

Brieu, Nicolas; Navab, Nassir; Serbanovic-Canic, Jovana; Ouwehand, Willem H.; Stemple, Derek L.; Cvejic, Ana; Groher, Martin

2012-01-01

The characterization of thrombus formation in time-lapse DIC microscopy is of increased interest for identifying genes which account for atherothrombosis and coronary artery diseases (CADs). In particular, we are interested in large-scale studies on zebrafish, which result in large amount of data, and require automatic processing. In this work, we present an image-based solution for the automatized extraction of parameters quantifying the temporal development of thrombotic plugs. Our system is based on the joint segmentation of thrombotic and aortic regions over time. This task is made difficult by the low contrast and the high dynamic conditions observed in vivo DIC microscopic scenes. Our key idea is to perform this segmentation by distinguishing the different motion patterns in image time series rather than by solving standard image segmentation tasks in each image frame. Thus, we are able to compensate for the poor imaging conditions. We model motion patterns by energies based on the idea of dynamic textures, and regularize the model by two prior energies on the shape of the aortic region and on the topological relationship between the thrombus and the aorta. We demonstrate the performance of our segmentation algorithm by qualitative and quantitative experiments on synthetic examples as well as on real in vivo microscopic sequences. PMID:22482997

Femtosecond few- to single-electron point-projection microscopy for nanoscale dynamic imaging

PubMed Central

Bainbridge, A. R.; Barlow Myers, C. W.; Bryan, W. A.

2016-01-01

Femtosecond electron microscopy produces real-space images of matter in a series of ultrafast snapshots. Pulses of electrons self-disperse under space-charge broadening, so without compression, the ideal operation mode is a single electron per pulse. Here, we demonstrate femtosecond single-electron point projection microscopy (fs-ePPM) in a laser-pump fs-e-probe configuration. The electrons have an energy of only 150 eV and take tens of picoseconds to propagate to the object under study. Nonetheless, we achieve a temporal resolution with a standard deviation of 114 fs (equivalent to a full-width at half-maximum of 269 ± 40 fs) combined with a spatial resolution of 100 nm, applied to a localized region of charge at the apex of a nanoscale metal tip induced by 30 fs 800 nm laser pulses at 50 kHz. These observations demonstrate real-space imaging of reversible processes, such as tracking charge distributions, is feasible whilst maintaining femtosecond resolution. Our findings could find application as a characterization method, which, depending on geometry, could resolve tens of femtoseconds and tens of nanometres. Dynamically imaging electric and magnetic fields and charge distributions on sub-micron length scales opens new avenues of ultrafast dynamics. Furthermore, through the use of active compression, such pulses are an ideal seed for few-femtosecond to attosecond imaging applications which will access sub-optical cycle processes in nanoplasmonics. PMID:27158637

Generation of deformation time series from SAR data sequences in areas affected by large dynamics: insights from Sierra Negra caldera, Galápagos Islands

NASA Astrophysics Data System (ADS)

Casu, Francesco; Manconi, Andrea; Pepe, Antonio; Lanari, Riccardo

2010-05-01

Differential Synthetic Aperture Radar Interferometry (DInSAR) is a remote sensing technique that allows producing spatially dense deformation maps of the Earth surface, with centimeter accuracy. To this end, the phase difference of SAR image pairs acquired before and after a deformation episode is properly exploited. This technique, originally applied to investigate single deformation events, has been further extended to analyze the temporal evolution of the deformation field through the generation of displacement time-series. A well-established approach is represented by the Small BAseline Subset (SBAS) technique (Berardino et al., 2002), whose capability to analyze deformation events at low and full spatial resolution has largely been demonstrated. However, in areas where large and/or rapid deformation phenomena occur, the exploitation of the differential interferograms, thus also of the displacement time-series, can be strongly limited by the presence of significant misregistration errors and/or very high fringe rates, making unfeasible the phase unwrapping step. In this work, we propose advances on the generation of deformation time-series in areas affected by large deformation dynamics. We present an extension of the amplitude-based Pixel-Offset analyses by applying the SBAS strategy, in order to move from the investigation of single (large) deformation events to that of dynamic phenomena. The above-mentioned method has been tested on an ENVISAT SAR data archive (Track 61, Frames 7173-7191) related to the Galapagos Islands, focusing on Sierra Negra caldera (Galapagos Islands), an active volcanic area often characterized by large and rapid deformation events leading to severe image misregistration effects (Yun et al., 2007). Moreover, we present a cross-validation of the retrieved deformation estimates comparing our results to continuous GPS measurements and to synthetic deformation obtained by independently modeling the interferometric phase information when available. References: P. Berardino et al., (2002), A new algorithm for Surface Deformation Monitoring based on Small Baseline Differential SAR Interferograms, IEEE Transactions on Geoscience and Remote Sensing, vol. 40, 11, pp. 2375-2383. S-H. Yun et al., (2007), Interferogram formation in the presence of complex and large deformation, Geophys. Res. Lett., vol. 34, L12305.

Dominant Lyapunov exponent and approximate entropy in heart rate variability during emotional visual elicitation

PubMed Central

Valenza, Gaetano; Allegrini, Paolo; Lanatà, Antonio; Scilingo, Enzo Pasquale

2012-01-01

In this work we characterized the non-linear complexity of Heart Rate Variability (HRV) in short time series. The complexity of HRV signal was evaluated during emotional visual elicitation by using Dominant Lyapunov Exponents (DLEs) and Approximate Entropy (ApEn). We adopted a simplified model of emotion derived from the Circumplex Model of Affects (CMAs), in which emotional mechanisms are conceptualized in two dimensions by the terms of valence and arousal. Following CMA model, a set of standardized visual stimuli in terms of arousal and valence gathered from the International Affective Picture System (IAPS) was administered to a group of 35 healthy volunteers. Experimental session consisted of eight sessions alternating neutral images with high arousal content images. Several works can be found in the literature showing a chaotic dynamics of HRV during rest or relax conditions. The outcomes of this work showed a clear switching mechanism between regular and chaotic dynamics when switching from neutral to arousal elicitation. Accordingly, the mean ApEn decreased with statistical significance during arousal elicitation and the DLE became negative. Results showed a clear distinction between the neutral and the arousal elicitation and could be profitably exploited to improve the accuracy of emotion recognition systems based on HRV time series analysis. PMID:22393320

Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging

PubMed Central

Dai, Yunpeng; Chen, Xueli; Yin, Jipeng; Wang, Guodong; Wang, Bo; Zhan, Yonghua; Nie, Yongzhan; Wu, Kaichun; Liang, Jimin

2018-01-01

Dynamic optical data from a series of sampling intervals can be used for quantitative analysis to obtain meaningful kinetic parameters of probe in vivo. The sampling schemes may affect the quantification results of dynamic fluorescence imaging. Here, we investigate the influence of different sampling schemes on the quantification of binding potential (BP) with theoretically simulated and experimentally measured data. Three groups of sampling schemes are investigated including the sampling starting point, sampling sparsity, and sampling uniformity. In the investigation of the influence of the sampling starting point, we further summarize two cases by considering the missing timing sequence between the probe injection and sampling starting time. Results show that the mean value of BP exhibits an obvious growth trend with an increase in the delay of the sampling starting point, and has a strong correlation with the sampling sparsity. The growth trend is much more obvious if throwing the missing timing sequence. The standard deviation of BP is inversely related to the sampling sparsity, and independent of the sampling uniformity and the delay of sampling starting time. Moreover, the mean value of BP obtained by uniform sampling is significantly higher than that by using the non-uniform sampling. Our results collectively suggest that a suitable sampling scheme can help compartmental modeling of dynamic fluorescence imaging provide more accurate results and simpler operations. PMID:29675325

SACCON Forced Oscillation Tests at DNW-NWB and NASA Langley 14x22-Foot Tunnel

NASA Technical Reports Server (NTRS)

Vicroy Dan D.; Loeser, Thomas D.; Schuette, Andreas

2010-01-01

A series of three wind tunnel static and forced oscillation tests were conducted on a generic unmanned combat air vehicle (UCAV) geometry. These tests are part of an international research effort to assess the state-of-the-art of computational fluid dynamics (CFD) methods to predict the static and dynamic stability and control characteristics. The experimental dataset includes not only force and moment time histories but surface pressure and off body particle image velocimetry measurements as well. The extent of the data precludes a full examination within the scope of this paper. This paper provides some examples of the dynamic force and moment data available as well as some of the observed trends.

Liver enhancement in healthy dogs after gadoxetic acid administration during dynamic contrast-enhanced magnetic resonance imaging.

PubMed

Borusewicz, P; Stańczyk, E; Kubiak, K; Spużak, J; Glińska-Suchocka, K; Jankowski, M; Nicpoń, J; Podgórski, P

2018-05-01

Dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) consists of acquisition of native baseline images, followed by a series of acquisitions performed during and after administration of a contrast medium. DCE-MRI, in conjunction with hepatobiliary-specific contrast media, such as gadoxetic acid (GD-EOB-DTPA), allows for precise characterisation of the enhancement pattern of the hepatic parenchyma following administration of the contrast agent. The aim of the study was to assess the pattern of temporal resolution contrast enhancement of the hepatic parenchyma following administration of GD-EOB-DTPA and to determine the optimal time window for post-contrast assessment of the liver. The study was carried out on eight healthy beagle dogs. MRI was performed using a 1.5T scanner. The imaging protocol included T1 weighted (T1-W) gradient echo (GRE), T2 weighted (T2-W) turbo spin echo (TSE) and dynamic T1-W GRE sequences. The dynamic T1-W sequence was performed using single 10mm thick slices. Regions of interest (ROIs) were chosen and the signal intensity curves were calculated for quantitative image analysis. The mean time to peak for all dogs was 26min. The plateau phase lasted on average 21min. A gradual decrease in the signal intensity of the hepatic parenchyma was observed in all dogs. A DCE-MRI enhancement pattern of the hepatic parenchyma was evident in dogs following the administration of a GD-EOB-DTPA, establishing baseline data for an optimal time window between 26 and 41min after administration of the contrast agent. Copyright © 2018 Elsevier Ltd. All rights reserved.

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Mapping Sub-Second Structure in Mouse Behavior

PubMed Central

Wiltschko, Alexander B.; Johnson, Matthew J.; Iurilli, Giuliano; Peterson, Ralph E.; Katon, Jesse M.; Pashkovski, Stan L.; Abraira, Victoria E.; Adams, Ryan P.; Datta, Sandeep Robert

2015-01-01

Summary Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that three-dimensional (3D) mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously-hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior. PMID:26687221

Mapping Woody Plant Encroachment in Grassland Using Multiple Source Remote Sensing images: Case Study in Oklahoma

NASA Astrophysics Data System (ADS)

Wang, J.; Xiao, X.; Qin, Y.; Dong, J.; Zhang, G.; Zhang, Y.; Zou, Z.; Zhou, Y.; Wu, X.; Bajgain, R.

2015-12-01

Woody plant encroachment (mainly Juniperus virginiana, a coniferous evergreen tree) in the native grassland has been rapidly increasing in the U.S. Southern Great Plains, largely triggered by overgrazing domestic livestock, fire suppression, and changing rainfall regimes. Increasing dense woody plants have significant implications for local grassland ecosystem dynamics, such as carbon storage, soil nutrient availability, herbaceous forage production, livestock, watershed hydrology and wildlife habitats. However, very limited data are available about the spatio-temporal dynamics of woody plant encroachment to the native grassland at regional scale. Data from remotes sensing could potentially provide relevant information and improve the conversion of native grassland to woody plant encroachment. Previous studies on woody detection in grassland mainly conducted at rangeland scale using airborne or high resolution images, which is sufficient to monitor the dynamics of woody plant encroachment in local grassland. This study examined the potential of medium resolution images to detect the woody encroachment in tallgrass prairie. We selected Cleveland county, Oklahoma, US. as case study area, where eastern area has higher woody coverage than does the western area. A 25-m Phased Array Type L-band Synthetic Aperture Radar (PALSAR, N36W98) image was used to map the trees distributed in the grassland. Then, maximum enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) in the winter calculated from time-series Landsat images was used to identify the invaded woody species (Juniperus virginiana) through phenology-based algorithm. The resulting woody plant encroachment map was compared with the results extracted from the high resolution images provided by the National Agriculture Imagery Program (NAIP). Field photos were also used to validate the accuracy. These results showed that integrating PALSAR and Landsat had good performance to identify the woody encroachment in the study area. This study demonstrates the potential to monitor the dynamics of dense woody plant encroachment at the region scale using PALSAR and Landsat images and improves our understanding about the spatio-temporal dynamics of woody plant encroachment to native grasslands.

The Incidence of Adjacent Segment Degeneration after the Use of a Versatile Dynamic Hybrid Stabilization Device in Lumbar Stenosis: Results of a 5–8-Year Follow-up

PubMed Central

Dobran, Mauro; Esposito, Domenico Paolo; Gladi, Maurizio; Scerrati, Massimo; Iacoangeli, Maurizio

2018-01-01

Study Design Retrospective study with long-term follow-up. Purpose To evaluate the long-term incidence of adjacent segment degeneration (ASD) and clinical outcomes in a consecutive series of patients who underwent spinal decompression associated with dynamic or hybrid stabilization with a Flex+TM stabilization system (SpineVision, Antony, France) for lumbar spinal stenosis. Overview of Literature The incidence of ASD and clinical outcomes following dynamic or hybrid stabilization with the Flex+TM system used for lumbar spinal stenosis have not been well investigated. Methods Twenty-one patients with lumbar stenosis and probable post-decompressive spinal instability underwent decompressive laminectomy followed by spinal stabilization using the Flex+TM stabilization system. The indication for a mono-level dynamic stabilization was a preoperative magnetic resonance imaging (MRI) demonstrating evidence of severe disc disease associated with severe spinal stenosis. The hybrid stabilization (rigid-dynamic) system was used for multilevel laminectomies with associated initial degenerative scoliosis, first-grade spondylolisthesis, or rostral pathology. Results The improvement in Visual Analog Scale and Oswestry Disability Index scores at follow-up were statistically significant (p<0.0001 and p<0.0001, respectively). At the 5–8-year follow-up, clinical examination, MRI, and X-ray findings showed an ASD complication with pain and disability in one of 21 patients. The clinical outcomes were similar in patients treated with dynamic or hybrid fixation. Conclusions Patients treated with laminectomy and Flex+TM stabilization presented a satisfactory clinical outcome after 5–8 years of follow-up, and ASD incidence in our series was 4.76% (one patient out of 21). We are aware that this is a small series, but our long-term follow-up may be sufficient to contribute to the expanding body of literature on the development of symptomatic ASD associated with dynamic or hybrid fixation. PMID:29713407

OBSERVATIONS OF A SERIES OF FLARES AND ASSOCIATED JET-LIKE ERUPTIONS DRIVEN BY THE EMERGENCE OF TWISTED MAGNETIC FIELDS

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

Lim, Eun-Kyung; Yurchyshyn, Vasyl; Kim, Sujin

We studied temporal changes of morphological and magnetic properties of a succession of four confined flares followed by an eruptive flare using the high-resolution New Solar Telescope (NST) operating at the Big Bear Solar Observatory (BBSO) and Helioseismic and Magnetic Imager (HMI) magnetograms and Atmospheric Image Assembly (AIA) EUV images provided by the Solar Dynamics Observatory (SDO). From the NST/Hα and the SDO/AIA 304 Å observations we found that each flare developed a jet structure that evolved in a manner similar to evolution of the blowout jet: (1) an inverted-Y-shaped jet appeared and drifted away from its initial position; (2) jets formed amore » curtain-like structure that consisted of many fine threads accompanied by subsequent brightenings near the footpoints of the fine threads; and finally, (3) the jet showed a twisted structure visible near the flare maximum. Analysis of the HMI data showed that both the negative magnetic flux and the magnetic helicity have been gradually increasing in the positive-polarity region, indicating the continuous injection of magnetic twist before and during the series of flares. Based on these results, we suggest that the continuous emergence of twisted magnetic flux played an important role in producing successive flares and developing a series of blowout jets.« less

Why the long face? The importance of vertical image structure for biological "barcodes" underlying face recognition.

PubMed

Spence, Morgan L; Storrs, Katherine R; Arnold, Derek H

2014-07-29

Humans are experts at face recognition. The mechanisms underlying this complex capacity are not fully understood. Recently, it has been proposed that face recognition is supported by a coarse-scale analysis of visual information contained in horizontal bands of contrast distributed along the vertical image axis-a biological facial "barcode" (Dakin & Watt, 2009). A critical prediction of the facial barcode hypothesis is that the distribution of image contrast along the vertical axis will be more important for face recognition than image distributions along the horizontal axis. Using a novel paradigm involving dynamic image distortions, a series of experiments are presented examining famous face recognition impairments from selectively disrupting image distributions along the vertical or horizontal image axes. Results show that disrupting the image distribution along the vertical image axis is more disruptive for recognition than matched distortions along the horizontal axis. Consistent with the facial barcode hypothesis, these results suggest that human face recognition relies disproportionately on appropriately scaled distributions of image contrast along the vertical image axis. © 2014 ARVO.

Time-Series Analysis of Supergranule Characterstics at Solar Minimum

NASA Technical Reports Server (NTRS)

Williams, Peter E.; Pesnell, W. Dean

2013-01-01

Sixty days of Doppler images from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler Imager (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three to five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic Imager (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range time-series derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a time-series similar to the data simulations. The qualitative similarities between the simulated and the observed time-series suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

PubMed Central

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2014-01-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For OSEM, image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-fluorodeoxyglucose dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation GTM PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in CMRGlc estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters. PMID:24052021

[Vegetation spatial and temporal dynamic characteristics based on NDVI time series trajectories in grassland opencast coal mining].

PubMed

Jia, Duo; Wang, Cang Jiao; Mu, Shou Guo; Zhao, Hua

2017-06-18

The spatiotemporal dynamic patterns of vegetation in mining area are still unclear. This study utilized time series trajectory segmentation algorithm to fit Landsat NDVI time series which generated from fusion images at the most prosperous period of growth based on ESTARFM algorithm. Combining with the shape features of the fitted trajectory, this paper extracted five vegetation dynamic patterns including pre-disturbance type, continuous disturbance type, stabilization after disturbance type, stabilization between disturbance and recovery type, and recovery after disturbance type. The result indicated that recovery after disturbance type was the dominant vegetation change pattern among the five types of vegetation dynamic pattern, which accounted for 55.2% of the total number of pixels. The follows were stabilization after disturbance type and continuous disturbance type, accounting for 25.6% and 11.0%, respectively. The pre-disturbance type and stabilization between disturbance and recovery type accounted for 3.5% and 4.7%, respectively. Vegetation disturbance mainly occurred from 2004 to 2009 in Shengli mining area. The onset time of stable state was 2008 and the spatial locations mainlydistributed in open-pit stope and waste dump. The reco-very state mainly started since the year of 2008 and 2010, while the areas were small and mainly distributed at the periphery of open-pit stope and waste dump. Duration of disturbance was mainly 1 year. The duration of stable period usually sustained 7 years. The duration of recovery state of the type of stabilization between disturbances continued 2 to 5 years, while the type of recovery after disturbance often sustained 8 years.

Measurement of 3-D Vibrational Motion by Dynamic Photogrammetry Using Least-Square Image Matching for Sub-Pixel Targeting to Improve Accuracy.

PubMed

Lee, Hyoseong; Rhee, Huinam; Oh, Jae Hong; Park, Jin Ho

2016-03-11

This paper deals with an improved methodology to measure three-dimensional dynamic displacements of a structure by digital close-range photogrammetry. A series of stereo images of a vibrating structure installed with targets are taken at specified intervals by using two daily-use cameras. A new methodology is proposed to accurately trace the spatial displacement of each target in three-dimensional space. This method combines the correlation and the least-square image matching so that the sub-pixel targeting can be obtained to increase the measurement accuracy. Collinearity and space resection theory are used to determine the interior and exterior orientation parameters. To verify the proposed method, experiments have been performed to measure displacements of a cantilevered beam excited by an electrodynamic shaker, which is vibrating in a complex configuration with mixed bending and torsional motions simultaneously with multiple frequencies. The results by the present method showed good agreement with the measurement by two laser displacement sensors. The proposed methodology only requires inexpensive daily-use cameras, and can remotely detect the dynamic displacement of a structure vibrating in a complex three-dimensional defection shape up to sub-pixel accuracy. It has abundant potential applications to various fields, e.g., remote vibration monitoring of an inaccessible or dangerous facility.

Measurement of 3-D Vibrational Motion by Dynamic Photogrammetry Using Least-Square Image Matching for Sub-Pixel Targeting to Improve Accuracy

PubMed Central

Lee, Hyoseong; Rhee, Huinam; Oh, Jae Hong; Park, Jin Ho

2016-01-01

This paper deals with an improved methodology to measure three-dimensional dynamic displacements of a structure by digital close-range photogrammetry. A series of stereo images of a vibrating structure installed with targets are taken at specified intervals by using two daily-use cameras. A new methodology is proposed to accurately trace the spatial displacement of each target in three-dimensional space. This method combines the correlation and the least-square image matching so that the sub-pixel targeting can be obtained to increase the measurement accuracy. Collinearity and space resection theory are used to determine the interior and exterior orientation parameters. To verify the proposed method, experiments have been performed to measure displacements of a cantilevered beam excited by an electrodynamic shaker, which is vibrating in a complex configuration with mixed bending and torsional motions simultaneously with multiple frequencies. The results by the present method showed good agreement with the measurement by two laser displacement sensors. The proposed methodology only requires inexpensive daily-use cameras, and can remotely detect the dynamic displacement of a structure vibrating in a complex three-dimensional defection shape up to sub-pixel accuracy. It has abundant potential applications to various fields, e.g., remote vibration monitoring of an inaccessible or dangerous facility. PMID:26978366

Electricity Data Browser

EIA Publications

The Electricity Data Browser shows generation, consumption, fossil fuel receipts, stockpiles, retail sales, and electricity prices. The data appear on an interactive web page and are updated each month. The Electricity Data Browser includes all the datasets collected and published in EIA's Electric Power Monthly and allows users to perform dynamic charting of data sets as well as map the data by state. The data browser includes a series of reports that appear in the Electric Power Monthly and allows readers to drill down to plant level statistics, where available. All images and datasets are available for download. Users can also link to the data series in EIA's Application Programming Interface (API). An API makes our data machine-readable and more accessible to users.

A spatial-temporal method for assessing the energy balance dynamics of partially sealed surfaces.

NASA Astrophysics Data System (ADS)

Pipkins, Kyle; Kleinschmit, Birgit; Wessolek, Gerd

2017-04-01

The effects of different types of sealed surfaces on the surface energy balance have been well-studied in the past. However, these field studies typically aggregate these surfaces into continuous units. The proposed method seeks to disaggregate such surfaces into paving and seam areas using spatial methods, and to consider the temperature dynamics under wet and dry conditions between these two components. This experimental work is undertaken using a thermal camera to record a time series of images over two lysimeters with differing levels of surface sealing. The images are subsequently decomposed into component materials using object-based image analysis and compared on the basis of both the surface materials as well as the spatial configuration of materials. Finally, a surface energy balance method is used to estimate evaporation rates from the surfaces, both separately for the different surface components as well as using the total surface mean. Results are validated using the output of the weighing lysimeter. Our findings will determine whether the explicitly spatial method is an improvement over the mean aggregate method.

a Landsat Time-Series Stacks Model for Detection of Cropland Change

NASA Astrophysics Data System (ADS)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

Dynamics of bubble collapse under vessel confinement in 2D hydrodynamic experiments

NASA Astrophysics Data System (ADS)

Shpuntova, Galina; Austin, Joanna

2013-11-01

One trauma mechanism in biomedical treatment techniques based on the application of cumulative pressure pulses generated either externally (as in shock-wave lithotripsy) or internally (by laser-induced plasma) is the collapse of voids. However, prediction of void-collapse driven tissue damage is a challenging problem, involving complex and dynamic thermomechanical processes in a heterogeneous material. We carry out a series of model experiments to investigate the hydrodynamic processes of voids collapsing under dynamic loading in configurations designed to model cavitation with vessel confinement. The baseline case of void collapse near a single interface is also examined. Thin sheets of tissue-surrogate polymer materials with varying acoustic impedance are used to create one or two parallel material interfaces near the void. Shadowgraph photography and two-color, single-frame particle image velocimetry quantify bubble collapse dynamics including jetting, interface dynamics and penetration, and the response of the surrounding material. Research supported by NSF Award #0954769, ``CAREER: Dynamics and damage of void collapse in biological materials under stress wave loading.''

75 FR 63841 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-18

...; [email protected] . Signal-to-Noise Enhancement in Imaging Applications Using a Time-Series of Images... reduction in imaging applications that use a time-series of images. In one embodiment of the invention, a time-series of images is acquired using a same imaging protocol of the same subject area, but the...

Coupling fluid dynamics and host-rock deformation associated with magma intrusion in the crust: Insights from analogue experiments

NASA Astrophysics Data System (ADS)

Kavanagh, J. L.; Dennis, D. J.

2014-12-01

Models of magma ascent in the crust tend to either consider the dynamics of fluid flow within intrusions or the associated host-rock deformation. However, these processes are coupled in nature, and so to develop a more complete understanding of magma ascent dynamics in the crust both need to be taken into account. We present a series of gelatine analogue experiments that use both Particle Image Velocimentry (PIV) and Digital Image Correlation (DIC) techniques to characterise the dynamics of fluid flow within intrusions and to quantify the associated deformation of the intruded media. Experiments are prepared by filling a 40x40x30 cm3 clear-Perspex tank with a low-concentration gelatine mixture (2-5 wt%) scaled to be of comparable stiffness to crustal strata. Fluorescent seeding particles are added to the gelatine mixture during its preparation and to the magma analogue prior to injection. Two Dantec CCD cameras are positioned outside the tank and a vertical high-power laser sheet positioned along the centre line is triggered to illuminate the seeding particles with short intense pulses. Dyed water (the magma analogue) injected into the solid gelatine from below causes a vertically propagating penny-shaped crack (dike) to form. Incremental and cumulative displacement vectors are calculated by cross-correlation between successive images at a defined time interval. Spatial derivatives map the fluid flow within the intrusion and associated strain and stress evolution of the host, both during dike propagation and on to eruption. As the gelatine deforms elastically at the experimental conditions, strain calculations correlate with stress. Models which couple fluid dynamics and host deformation make an important step towards improving our understanding of the dynamics of magma transport through the crust and to help constrain the tendency for eruption.

Modified dixon‐based renal dynamic contrast‐enhanced MRI facilitates automated registration and perfusion analysis

PubMed Central

Leiner, Tim; Vink, Eva E.; Blankestijn, Peter J.; van den Berg, Cornelis A.T.

2017-01-01

Purpose Renal dynamic contrast‐enhanced (DCE) MRI provides information on renal perfusion and filtration. However, clinical implementation is hampered by challenges in postprocessing as a result of misalignment of the kidneys due to respiration. We propose to perform automated image registration using the fat‐only images derived from a modified Dixon reconstruction of a dual‐echo acquisition because these provide consistent contrast over the dynamic series. Methods DCE data of 10 hypertensive patients was used. Dual‐echo images were acquired at 1.5 T with temporal resolution of 3.9 s during contrast agent injection. Dixon fat, water, and in‐phase and opposed‐phase (OP) images were reconstructed. Postprocessing was automated. Registration was performed both to fat images and OP images for comparison. Perfusion and filtration values were extracted from a two‐compartment model fit. Results Automatic registration to fat images performed better than automatic registration to OP images with visible contrast enhancement. Median vertical misalignment of the kidneys was 14 mm prior to registration, compared to 3 mm and 5 mm with registration to fat images and OP images, respectively (P = 0.03). Mean perfusion values and MR‐based glomerular filtration rates (GFR) were 233 ± 64 mL/100 mL/min and 60 ± 36 mL/minute, respectively, based on fat‐registered images. MR‐based GFR correlated with creatinine‐based GFR (P = 0.04) for fat‐registered images. For unregistered and OP‐registered images, this correlation was not significant. Conclusion Absence of contrast changes on Dixon fat images improves registration in renal DCE MRI and enables automated postprocessing, resulting in a more accurate estimation of GFR. Magn Reson Med 80:66–76, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMID:29134673

High frequency mesozooplankton monitoring: Can imaging systems and automated sample analysis help us describe and interpret changes in zooplankton community composition and size structure — An example from a coastal site

NASA Astrophysics Data System (ADS)

Romagnan, Jean Baptiste; Aldamman, Lama; Gasparini, Stéphane; Nival, Paul; Aubert, Anaïs; Jamet, Jean Louis; Stemmann, Lars

2016-10-01

The present work aims to show that high throughput imaging systems can be useful to estimate mesozooplankton community size and taxonomic descriptors that can be the base for consistent large scale monitoring of plankton communities. Such monitoring is required by the European Marine Strategy Framework Directive (MSFD) in order to ensure the Good Environmental Status (GES) of European coastal and offshore marine ecosystems. Time and cost-effective, automatic, techniques are of high interest in this context. An imaging-based protocol has been applied to a high frequency time series (every second day between April 2003 to April 2004 on average) of zooplankton obtained in a coastal site of the NW Mediterranean Sea, Villefranche Bay. One hundred eighty four mesozooplankton net collected samples were analysed with a Zooscan and an associated semi-automatic classification technique. The constitution of a learning set designed to maximize copepod identification with more than 10,000 objects enabled the automatic sorting of copepods with an accuracy of 91% (true positives) and a contamination of 14% (false positives). Twenty seven samples were then chosen from the total copepod time series for detailed visual sorting of copepods after automatic identification. This method enabled the description of the dynamics of two well-known copepod species, Centropages typicus and Temora stylifera, and 7 other taxonomically broader copepod groups, in terms of size, biovolume and abundance-size distributions (size spectra). Also, total copepod size spectra underwent significant changes during the sampling period. These changes could be partially related to changes in the copepod assemblage taxonomic composition and size distributions. This study shows that the use of high throughput imaging systems is of great interest to extract relevant coarse (i.e. total abundance, size structure) and detailed (i.e. selected species dynamics) descriptors of zooplankton dynamics. Innovative zooplankton analyses are therefore proposed and open the way for further development of zooplankton community indicators of changes.

Imaging magnetisation dynamics in nano-contact spin-torque vortex oscillators exhibiting gyrotropic mode splitting

NASA Astrophysics Data System (ADS)

Keatley, Paul Steven; Redjai Sani, Sohrab; Hrkac, Gino; Majid Mohseni, Seyed; Dürrenfeld, Philipp; Åkerman, Johan; Hicken, Robert James

2017-04-01

Nano-contact spin-torque vortex oscillators (STVOs) are anticipated to find application as nanoscale sources of microwave emission in future technological applications. Presently the output power and phase stability of individual STVOs are not competitive with existing oscillator technologies. Synchronisation of multiple nano-contact STVOs via magnetisation dynamics has been proposed to enhance the microwave emission. The control of device-to-device variations, such as mode splitting of the microwave emission, is essential if multiple STVOs are to be successfully synchronised. In this work a combination of electrical measurements and time-resolved scanning Kerr microscopy (TRSKM) was used to demonstrate how mode splitting in the microwave emission of STVOs was related to the magnetisation dynamics that are generated. The free-running STVO response to a DC current only was used to identify devices and bias magnetic field configurations for which single and multiple modes of microwave emission were observed. Stroboscopic Kerr images were acquired by injecting a small amplitude RF current to phase lock the free-running STVO response. The images showed that the magnetisation dynamics of a multimode device with moderate splitting could be controlled by the injected RF current so that they exhibit similar spatial character to that of a single mode. Significant splitting was found to result from a complicated equilibrium magnetic state that was observed in Kerr images as irregular spatial characteristics of the magnetisation dynamics. Such dynamics were observed far from the nano-contact and so their presence cannot be detected in electrical measurements. This work demonstrates that TRSKM is a powerful tool for the direct observation of the magnetisation dynamics generated by STVOs that exhibit complicated microwave emission. Characterisation of such dynamics outside the nano-contact perimeter permits a deeper insight into the requirements for optimal phase-locking of multiple STVOs that share common magnetic layers. , which features invited work from the best early-career researchers working within the scope of J. Phys. D. This project is part of the Journal of Physics series' 50th anniversary celebrations in 2017. Paul Keatley was selected by the Editorial Board of J. Phys. D as an Emerging Leader.

The superiority of L3-CCDs in the high-flux and wide dynamic range regimes

NASA Astrophysics Data System (ADS)

Butler, Raymond F.; Sheehan, Brendan J.

2008-02-01

Low Light Level CCD (L3-CCD) cameras have received much attention for high cadence astronomical imaging applications. Efforts to date have concentrated on exploiting them for two scenarios: post-exposure image sharpening and ``lucky imaging'', and rapid variability in astrophysically interesting sources. We demonstrate their marked superiority in a third distinct scenario: observing in the high-flux and wide dynamic range regimes. We realized that the unique features of L3-CCDs would make them ideal for maximizing signal-to-noise in observations of bright objects (whether variable or not), and for high dynamic range scenarios such as faint targets embedded in a crowded field of bright objects. Conventional CCDs have drawbacks in such regimes, due to a poor duty cycle-the combination of short exposure times (for time-series sampling or to avoid saturation) and extended readout times (for minimizing readout noise). For different telescope sizes, we use detailed models to show that a range of conventional imaging systems are photometrically out-performed across a wide range of object brightness, once the operational parameters of the L3-CCD are carefully set. The cross-over fluxes, above which the L3-CCD is operationally superior, are surprisingly faint-even for modest telescope apertures. We also show that the use of L3-CCDs is the optimum strategy for minimizing atmospheric scintillation noise in photometric observations employing a given telescope aperture. This is particularly significant, since scintillation can be the largest source of error in timeseries photometry. These results should prompt a new direction in developing imaging instrumentation solutions for observatories.

Association between dynamic features of breast DCE-MR imaging and clinical response of neoadjuvant chemotherapy: a preliminary analysis

NASA Astrophysics Data System (ADS)

Huang, Lijuan; Fan, Ming; Li, Lihua; Zhang, Juan; Shao, Guoliang; Zheng, Bin

2016-03-01

Neoadjuvant chemotherapy (NACT) is being used increasingly in the management of patients with breast cancer for systemically reducing the size of primary tumor before surgery in order to improve survival. The clinical response of patients to NACT is correlated with reduced or abolished of their primary tumor, which is important for treatment in the next stage. Recently, the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used for evaluation of the response of patients to NACT. To measure this correlation, we extracted the dynamic features from the DCE- MRI and performed association analysis between these features and the clinical response to NACT. In this study, 59 patients are screened before NATC, of which 47 are complete or partial response, and 12 are no response. We segmented the breast areas depicted on each MR image by a computer-aided diagnosis (CAD) scheme, registered images acquired from the sequential MR image scan series, and calculated eighteen features extracted from DCE-MRI. We performed SVM with the 18 features for classification between patients of response and no response. Furthermore, 6 of the 18 features are selected to refine the classification by using Genetic Algorithm. The accuracy, sensitivity and specificity are 87%, 95.74% and 50%, respectively. The calculated area under a receiver operating characteristic (ROC) curve is 0.79+/-0.04. This study indicates that the features of DCE-MRI of breast cancer are associated with the response of NACT. Therefore, our method could be helpful for evaluation of NACT in treatment of breast cancer.

The Pearson-Readhead Survey of Compact Extragalactic Radio Sources from Space. I. The Images

NASA Astrophysics Data System (ADS)

Lister, M. L.; Tingay, S. J.; Murphy, D. W.; Piner, B. G.; Jones, D. L.; Preston, R. A.

2001-06-01

We present images from a space-VLBI survey using the facilities of the VLBI Space Observatory Programme (VSOP), drawing our sample from the well-studied Pearson-Readhead survey of extragalactic radio sources. Our survey has taken advantage of long space-VLBI baselines and large arrays of ground antennas, such as the Very Long Baseline Array and European VLBI Network, to obtain high-resolution images of 27 active galactic nuclei and to measure the core brightness temperatures of these sources more accurately than is possible from the ground. A detailed analysis of the source properties is given in accompanying papers. We have also performed an extensive series of simulations to investigate the errors in VSOP images caused by the relatively large holes in the (u,v)-plane when sources are observed near the orbit normal direction. We find that while the nominal dynamic range (defined as the ratio of map peak to off-source error) often exceeds 1000:1, the true dynamic range (map peak to on-source error) is only about 30:1 for relatively complex core-jet sources. For sources dominated by a strong point source, this value rises to approximately 100:1. We find the true dynamic range to be a relatively weak function of the difference in position angle (P.A.) between the jet P.A. and u-v coverage major axis P.A. For regions with low signal-to-noise ratios, typically located down the jet away from the core, large errors can occur, causing spurious features in VSOP images that should be interpreted with caution.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Dynamic laser speckle applied to the analysis of maturation process of irradiated fresh fruits

NASA Astrophysics Data System (ADS)

Vincitorio, F. M.; Budini, N.; Freyre, C.; Mulone, C.; Fiorucci, M. P.; López, A. J.; Ramil, A.

2012-10-01

The treatment of fresh fruits with different doses of ionizing radiation has been found effective for delaying ripening and, in this way, to extend shelf life. This preservation method is likely to produce some functional or constitutive changes in the cellular structure of the fruit. In this work, a test of the effectiveness of fruit irradiation with relatively low doses was performed by using dynamic speckle imaging. Bananas from a same lot were chosen, being a first series of them irradiated with different doses of 0.2, 0.4 and 0.6 kGy (Gy = J/kg) and a second series with doses of 0.2, 0.4, 0.6 and 1 kGy. Non irradiated bananas (0 kGy) were considered as the lot reference for contrast. Irradiation was carried out at the Semi-Industrial Cobalt 60 facility of the Ezeiza Atomic Center, with an activity of 6 × 105 Curie and a dose rate of 28.5 Gy/min. The objective of this work is to analyze differences in the maturation process between irradiated and nonirradiated fruits by means of dynamic speckle pattern evaluation.

Diagnostic Accuracy of Dynamic Contrast Enhanced Magnetic Resonance Imaging in Characterizing Lung Masses

PubMed Central

Inan, Nagihan; Arslan, Arzu; Donmez, Muhammed; Sarisoy, Hasan Tahsin

2016-01-01

Background Imaging plays a critical role not only in the detection, but also in the characterization of lung masses as benign or malignant. Objectives To determine the diagnostic accuracy of dynamic magnetic resonance imaging (MRI) in the differential diagnosis of benign and malignant lung masses. Patients and Methods Ninety-four masses were included in this prospective study. Five dynamic series of T1-weighted spoiled gradient echo (FFE) images were obtained, followed by a T1-weighted FFE sequence in the late phase (5th minutes). Contrast enhancement patterns in the early (25th second) and late (5th minute) phase images were evaluated. For the quantitative evaluation, signal intensity (SI)-time curves were obtained and the maximum relative enhancement, wash-in rate, and time-to-peak enhancement of masses in both groups were calculated. Results The early phase contrast enhancement patterns were homogeneous in 78.2% of the benign masses, while heterogeneous in 74.4% of the malignant tumors. On the late phase images, 70.8% of the benign masses showed homogeneous enhancement, while most of the malignant masses showed heterogeneous enhancement (82.4%). During the first pass, the maximum relative enhancement and wash-in rate values of malignant masses were significantly higher than those of the benign masses (P = 0.03 and 0.04, respectively). The cutoff value at 15% yielded a sensitivity of 85.4%, specificity of 61.2%, and positive predictive value of 68.7% for the maximum relative enhancement. Conclusion Contrast enhancement patterns and SI-time curve analysis of MRI are helpful in the differential diagnosis of benign and malignant lung masses. PMID:27703654

Reproducibility of image quality for moving objects using respiratory-gated computed tomography: a study using a phantom model

PubMed Central

Fukumitsu, Nobuyoshi; Ishida, Masaya; Terunuma, Toshiyuki; Mizumoto, Masashi; Hashimoto, Takayuki; Moritake, Takashi; Okumura, Toshiyuki; Sakae, Takeji; Tsuboi, Koji; Sakurai, Hideyuki

2012-01-01

To investigate the reproducibility of computed tomography (CT) imaging quality in respiratory-gated radiation treatment planning is essential in radiotherapy of movable tumors. Seven series of regular and six series of irregular respiratory motions were performed using a thorax dynamic phantom. For the regular respiratory motions, the respiratory cycle was changed from 2.5 to 4 s and the amplitude was changed from 4 to 10 mm. For the irregular respiratory motions, a cycle of 2.5 to 4 or an amplitude of 4 to 10 mm was added to the base data (i.e. 3.5-s cycle, 6-mm amplitude) every three cycles. Images of the object were acquired six times using respiratory-gated data acquisition. The volume of the object was calculated and the reproducibility of the volume was decided based on the variety. The registered image of the object was added and the reproducibility of the shape was decided based on the degree of overlap of objects. The variety in the volumes and shapes differed significantly as the respiratory cycle changed according to regular respiratory motions. In irregular respiratory motion, shape reproducibility was further inferior, and the percentage of overlap among the six images was 35.26% in the 2.5- and 3.5-s cycle mixed group. Amplitude changes did not produce significant differences in the variety of the volumes and shapes. Respiratory cycle changes reduced the reproducibility of the image quality in respiratory-gated CT. PMID:22966173

Prospective MR image alignment between breath-holds: Application to renal BOLD MRI.

PubMed

Kalis, Inge M; Pilutti, David; Krafft, Axel J; Hennig, Jürgen; Bock, Michael

2017-04-01

To present an image registration method for renal blood oxygen level-dependent (BOLD) measurements that enables semiautomatic assessment of parenchymal and medullary R2* changes under a functional challenge. In a series of breath-hold acquisitions, three-dimensional data were acquired initially for prospective image registration of subsequent BOLD measurements. An algorithm for kidney alignment for BOLD renal imaging (KALIBRI) was implemented to detect the positions of the left and right kidney so that the kidneys were acquired in the subsequent BOLD measurement at consistent anatomical locations. Residual in-plane distortions were corrected retrospectively so that semiautomatic dynamic R2* measurements of the renal cortex and medulla become feasible. KALIBRI was tested in six healthy volunteers during a series of BOLD experiments, which included a 600- to 1000-mL water challenge. Prospective image registration and BOLD imaging of each kidney was achieved within a total measurement time of about 17 s, enabling its execution within a single breath-hold. KALIBRI improved the registration by up to 35% as found with mutual information measures. In four volunteers, a medullary R2* decrease of up to 40% was observed after water ingestion. KALIBRI improves the quality of two-dimensional time-resolved renal BOLD MRI by aligning local renal anatomy, which allows for consistent R2* measurements over many breath-holds. Magn Reson Med 77:1573-1582, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

The relationship between the change of magnetic energy and eruption behavior in NOAA AR 11429

NASA Astrophysics Data System (ADS)

Wang, R.; Liu, Y. D.

2013-12-01

We study the evolution of magnetic energy in an active region (AR) NOAA 11429, which produced a series of X/M class flares and fast coronal mass ejections (CMEs) in March 2012. In particular, this AR spawned double X-class flares (X5.4/X1.3) within a time internal of only 1 hr on March 7, which are associated with wide and fast CMEs with speeds of ~2000 km/s. A nonlinear force-free field extrapolation method is adopted to reconstruct the coronal magnetic field. We apply this method to a time series of 176 high-cadence vector magnetograms of the AR acquired by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory (HMI/SDO), which span a time interval of 1.5 days. We investigate the budgets of the free magnetic energy and relative magnetic helicity. We find that there exist some relations between the changes of magnetic energy and flare magnitudes. Compared with previous studies, our results indicate that the magnetic energy decrease occurs before the flare and CME launch time. We will also combine images from the Atmospheric Imaging Assembly (AIA) to further explore the detailed process of the eruptions.

All-optical framing photography based on hyperspectral imaging method

NASA Astrophysics Data System (ADS)

Liu, Shouxian; Li, Yu; Li, Zeren; Chen, Guanghua; Peng, Qixian; Lei, Jiangbo; Liu, Jun; Yuan, Shuyun

2017-02-01

We propose and experimentally demonstrate a new all optical-framing photography that uses hyperspectral imaging methods to record a chirped pulse's temporal-spatial information. This proposed method consists of three parts: (1) a chirped laser pulse encodes temporal phenomena onto wavelengths; (2) a lenslet array generates a series of integral pupil images;(3) a dispersive device disperses the integral images at void space of image sensor. Compared with Ultrafast All-Optical Framing Technology(Daniel Frayer,2013,2014) and Sequentially Time All-Optical Mapping Photography( Nakagawa 2014, 2015), our method is convenient to adjust the temporal resolution and to flexibly increase the numbers of frames. Theoretically, the temporal resolution of our scheme is limited by the amount of dispersion that is added to a Fourier transform limited femtosecond laser pulse. Correspondingly, the optimal number of frames is decided by the ratio of the observational time window to the temporal resolution, and the effective pixels of each frame are mostly limited by the dimensions M×N of the lenslet array. For example, if a 40fs Fourier transform limited femtosecond pulse is stretched to 10ps, a CCD camera with 2048×3072 pixels can record 15 framing images with temporal resolution of 650fs and image size of 100×100 pixels. As spectrometer structure, our recording part has another advantage that not only amplitude images but also frequency domain interferograms can be imaged. Therefore, it is comparatively easy to capture fast dynamics in the refractive index change of materials. A further dynamic experiment is being conducted.

Dynamic Black-Level Correction and Artifact Flagging in the Kepler Data Pipeline

NASA Technical Reports Server (NTRS)

Clarke, B. D.; Kolodziejczak, J. J.; Caldwell, D. A.

2013-01-01

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images which find their way into the calibrated pixel time series and ultimately into the calibrated target flux time series. Using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data the Keplerpipeline models and removes the FGS crosstalk artifacts by dynamically adjusting the black level correction. By examining the residuals to the model fits, the pipeline detects and flags spatial regions and time intervals of strong time-varying blacklevel (rolling bands ) on a per row per cadence basis. These flags are made available to downstream users of the data since the uncorrected rolling band artifacts could complicate processing or lead to misinterpretation of instrument behavior as stellar. This model fitting and artifact flagging is performed within the new stand-alone pipeline model called Dynablack. We discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performances as a result of including FGS corrections in the calibration. We also discuss the effectiveness of the rolling band flagging for downstream users and illustrate with some affected light curves.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

OSM-Classic : An optical imaging technique for accurately determining strain

NASA Astrophysics Data System (ADS)

Aldrich, Daniel R.; Ayranci, Cagri; Nobes, David S.

OSM-Classic is a program designed in MATLAB® to provide a method of accurately determining strain in a test sample using an optical imaging technique. Measuring strain for the mechanical characterization of materials is most commonly performed with extensometers, LVDT (linear variable differential transistors), and strain gauges; however, these strain measurement methods suffer from their fragile nature and it is not particularly easy to attach these devices to the material for testing. To alleviate these potential problems, an optical approach that does not require contact with the specimen can be implemented to measure the strain. OSM-Classic is a software that interrogates a series of images to determine elongation in a test sample and hence, strain of the specimen. It was designed to provide a graphical user interface that includes image processing with a dynamic region of interest. Additionally, the stain is calculated directly while providing active feedback during the processing.

Wavelet Imaging on Multiple Scales (WIMS) reveals focal adhesion distributions, dynamics and coupling between actomyosin bundle stability

PubMed Central

Toplak, Tim; Palmieri, Benoit; Juanes-García, Alba; Vicente-Manzanares, Miguel; Grant, Martin; Wiseman, Paul W.

2017-01-01

We introduce and use Wavelet Imaging on Multiple Scales (WIMS) as an improvement to fluorescence correlation spectroscopy to measure physical processes and features that occur across multiple length scales. In this study, wavelet transforms of cell images are used to characterize molecular dynamics at the cellular and subcellular levels (i.e. focal adhesions). We show the usefulness of the technique by applying WIMS to an image time series of a migrating osteosarcoma cell expressing fluorescently labelled adhesion proteins, which allows us to characterize different components of the cell ranging from optical resolution scale through to focal adhesion and whole cell size scales. Using WIMS we measured focal adhesion numbers, orientation and cell boundary velocities for retraction and protrusion. We also determine the internal dynamics of individual focal adhesions undergoing assembly, disassembly or elongation. Thus confirming as previously shown, WIMS reveals that the number of adhesions and the area of the protruding region of the cell are strongly correlated, establishing a correlation between protrusion size and adhesion dynamics. We also apply this technique to characterize the behavior of adhesions, actin and myosin in Chinese hamster ovary cells expressing a mutant form of myosin IIB (1935D) that displays decreased filament stability and impairs front-back cell polarity. We find separate populations of actin and myosin at each adhesion pole for both the mutant and wild type form. However, we find these populations move rapidly inwards toward one another in the mutant case in contrast to the cells that express wild type myosin IIB where those populations remain stationary. Results obtained with these two systems demonstrate how WIMS has the potential to reveal novel correlations between chosen parameters that belong to different scales. PMID:29049414

Measurement of wave-front aberration in a small telescope remote imaging system using scene-based wave-front sensing

DOEpatents

Poyneer, Lisa A; Bauman, Brian J

2015-03-31

Reference-free compensated imaging makes an estimation of the Fourier phase of a series of images of a target. The Fourier magnitude of the series of images is obtained by dividing the power spectral density of the series of images by an estimate of the power spectral density of atmospheric turbulence from a series of scene based wave front sensor (SBWFS) measurements of the target. A high-resolution image of the target is recovered from the Fourier phase and the Fourier magnitude.

Ocean Processes Revealing by Seasonal Dynamics of Surface Chlorophyll Concentration (by Satellite Data)

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Vysotskaya, Galina

Continuous monitoring of phytopigment concentrations in the ocean by space-borne methods makes possible to estimate ecological condition of biocenoses in critical areas. Unlike land vege-tation, hydrological processes largely determine phytoplankton dynamics, which may be either recurrent or random. The types of chlorophyll concentration dynamics can manifest as zones quasistationary by seasonal chlorophyll dynamics, perennial variations of phytopigment con-centrations, anomalous variations, etc., that makes possible revealing of hydrological structure of the ocean. While large-scale and frequently occurring phenomena have been much studied, the seldom-occurring changes of small size may be of interest for analysis of long-term processes and rare natural variations. Along with this, the ability to reflect consequences of anthropoge-nous impact or natural ecological disasters on the ocean biota makes the anomalous variations ecologically essential. Civilization aspiring for steady development and preservation of the bio-sphere, must have the knowledge of spatial distribution, seasonal dynamics and anomalies of the primary production process on the planet. In the papers of the authors (Shevyrnogov A.P., Vysotskaya G.S., Gitelzon J.I. Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data. Adv. Space Res. Vol. 18, No. 7, pp. 129-132, 1996) existence of zones, which are quasi-stationary with similar seasonal dynamics of chlorophyll concentration at surface layer of ocean, was shown. Results were obtained on the base of pro-cessing of time series of satellite images SeaWiFS. It was shown that fronts and frontal zones coincide with dividing lines between quasi-stationary areas, especially in areas of large oceanic streams. Biota of surface oceanic layer is more stable in comparison with quickly changing sur-face temperature. It gives a possibility to circumvent influence of high-frequency component (for example, a diurnal cycle) in investigation of dynamics of spatial distribution of surface streams. In addition, an analyses of nonstable ocean productivity phenomena, stood out time series of satellite images, showed existence of areas with different types of instability in the all Global ocean. They are observed as adjacent nonstationary zones of different size, which are associated by different ways with known oceanic phenomena. It is evident that dynamics of a spatial distribution of biological productivity can give an additional knowledge of complicated picture of surface oceanic layer hydrology.

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

PubMed

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

2013-03-01

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

Dynamic Textures Modeling via Joint Video Dictionary Learning.

PubMed

Wei, Xian; Li, Yuanxiang; Shen, Hao; Chen, Fang; Kleinsteuber, Martin; Wang, Zhongfeng

2017-04-06

Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series. Hence, a dynamic scene sequence is represented by an appropriate transition matrix associated with a dictionary. In order to ensure the stability of JVDL, we impose several constraints on such transition matrix and dictionary. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. Moreover, such learned JVDL parameters can be used for various DT applications, such as DT synthesis and recognition. Experimental results demonstrate the strong competitiveness of the proposed JVDL approach in comparison with state-of-the-art video representation methods. Especially, it performs significantly better in dealing with DT synthesis and recognition on heavily corrupted data.

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PubMed

Velikina, Julia V; Samsonov, Alexey A

2015-11-01

To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. © 2014 Wiley Periodicals, Inc.

RECONSTRUCTION OF DYNAMIC IMAGE SERIES FROM UNDERSAMPLED MRI DATA USING DATA-DRIVEN MODEL CONSISTENCY CONDITION (MOCCO)

PubMed Central

Velikina, Julia V.; Samsonov, Alexey A.

2014-01-01

Purpose To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models pre-estimated from training data. Theory We introduce the MOdel Consistency COndition (MOCCO) technique that utilizes temporal models to regularize the reconstruction without constraining the solution to be low-rank as performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Methods Our method was compared to standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE MRA) and cardiac CINE imaging. We studied sensitivity of all methods to rank-reduction and temporal subspace modeling errors. Results MOCCO demonstrated reduced sensitivity to modeling errors compared to the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. Conclusions MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. PMID:25399724

Virtual non-contrast dual-energy CT compared to single-energy CT of the urinary tract: a prospective study.

PubMed

Lundin, Margareta; Lidén, Mats; Magnuson, Anders; Mohammed, Ahmed Abdulilah; Geijer, Håkan; Andersson, Torbjörn; Persson, Anders

2012-07-01

Dual-energy computed tomography (DECT) has been shown to be useful for subtracting bone or calcium in CT angiography and gives an opportunity to produce a virtual non-contrast-enhanced (VNC) image from a series where contrast agents have been given intravenously. High noise levels and low resolution have previously limited the diagnostic value of the VNC images created with the first generation of DECT. With the recent introduction of a second generation of DECT, there is a possibility of obtaining VNC images with better image quality at hopefully lower radiation dose compared to the previous generation. To compare the image quality of the single-energy series to a VNC series obtained with a two generations of DECT scanners. CT of the urinary tract was used as a model. Thirty patients referred for evaluation of hematuria were examined with an older system (Somatom Definition) and another 30 patients with a new generation (Somatom Definition Flash). One single-energy series was obtained before and one dual-energy series after administration of intravenous contrast media. We created a VNC series from the contrast-enhanced images. Images were assessed concerning image quality with a visual grading scale evaluation of the VNC series with the single-energy series as gold standard. The image quality of the VNC images was rated inferior to the single-energy variant for both scanners, OR 11.5-67.3 for the Definition and OR 2.1-2.8 for the Definition Flash. Visual noise and overall quality were regarded as better with Flash than Definition. Image quality of VNC images obtained with the new generation of DECT is still slightly inferior compared to native images. However, the difference is smaller with the new compared to the older system.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

NASA Astrophysics Data System (ADS)

Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2014-05-01

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

Revealing real-time emotional responses: a personalized assessment based on heartbeat dynamics.

PubMed

Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

2014-05-21

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

Monitoring the dynamics of glacial lakes in the High Mountain Asia region through time series Landsat images

NASA Astrophysics Data System (ADS)

Zhang, M.; Chen, F.

2017-12-01

Glacial lakes have been developing dramatically in the High Mountain Asia (HMA) region associated with human activities and persistent climatic warming. This leads to increased probability of glacial lake outburst floods (GLOF), pose potential threats to the downstream lives and properties of people. However, comprehensive information is lacking about the annual distribution, evolution and the driving mechanism of glacial lakes in the entire HMA due to the low accessibility and harsh natural conditions, with most studies focused either on certain portion of this region or at most several time intervals effort at monitoring glacial lakes at coarse resolution remote sensing. In this research, we produce yearly map of glacial lake extents in HMA from 2008 to 2016 using Landsat series satellites images, and further study the formation, distribution and dynamics of glacial lakes. In total 6197 and 8256 glacial lakes were detected in 2008 and 2016, respectively, mainly located at altitudes between 4400 m and 5600 m. The annual expansion rate is approximately 4.68 % from 2008 to 2016. To explore the cause of rapid expansion for some typical glacial lakes, we investigated their changing patterns through long-term expansion rates measured from change in shoreline positions. The results show that glacial lake expansion rates at some points change substantially (> 30 m/yr) and the formation of proglacial lakes may be dominated by different orientation-driving forces from parent glacier. The accelerating rate of ice and snow melting from glacier caused by global warming are primary contributor to glacial lake growth. The results may provide information for understanding the mechanism of lake dynamics, which also facilitate the scientific recognition of the potential glacial lakes hazards in this region.

Higher-Order Hurst Signatures: Dynamical Information in Time Series

NASA Astrophysics Data System (ADS)

Ferenbaugh, Willis

2005-10-01

Understanding and comparing time series from different systems requires characteristic measures of the dynamics embedded in the series. The Hurst exponent is a second-order dynamical measure of a time series which grew up within the blossoming fractal world of Mandelbrot. This characteristic measure is directly related to the behavior of the autocorrelation, the power-spectrum, and other second-order things. And as with these other measures, the Hurst exponent captures and quantifies some but not all of the intrinsic nature of a series. The more elusive characteristics live in the phase spectrum and the higher-order spectra. This research is a continuing quest to (more) fully characterize the dynamical information in time series produced by plasma experiments or models. The goal is to supplement the series information which can be represented by a Hurst exponent, and we would like to develop supplemental techniques in analogy with Hurst's original R/S analysis. These techniques should be another way to plumb the higher-order dynamics.

Monitoring of reforestation on burnt areas in Western Russia using Landsat time series

NASA Astrophysics Data System (ADS)

Vorobev, Oleg; Kurbanov, Eldar

2017-04-01

Forest fires are main disturbance factor for the natural ecosystems, especially in boreal forests. Monitoring for the dynamic of forest cover regeneration in the post-fire period of ecosystem recovery is crucial to both estimation of forest stands and forest management. In this study, on the example of burnt areas of 2010 wildfires in Republic Mari El of Russian Federation we estimated post-fire dynamic of different classes of vegetation cover between 2011-2016 years with the use of time series Landsat satellite images. To validate the newly obtained thematic maps we used 80 test sites with independent field data, as well Canopus-B images of high spatial resolution. For the analysis of the satellite images we referred to Normalized Differenced Vegetation Index (NDVI) and Tasseled Cap transformation. The research revealed that at the post-fire period the area of thematic classes "Reforestation of the middle and low density" has maximum cover (44%) on the investigated burnt area. On the burnt areas of 2010 there is ongoing active process of grass overgrowing (up to 20%), also there are thematic classes of deadwood (15%) and open spaces (10%). The results indicate that there is mostly natural regeneration of tree species pattern corresponding to the pre-fire condition. Forest plantations cover only 2% of the overall burnt area. By the 2016 year the NDVI parameters of young vegetation cover were recovered to the pre-fire level as well. The overall unsupervised classification accuracy of more than 70% shows high degree of agreement between the thematic map and the ground truth data. The research results can be applied for the long term succession monitoring and management plan development for the reforestation activities on the lands disturbed by fire.

Versatile utilization of real-time intraoperative contrast-enhanced ultrasound in cranial neurosurgery: technical note and retrospective case series.

PubMed

Lekht, Ilya; Brauner, Noah; Bakhsheshian, Joshua; Chang, Ki-Eun; Gulati, Mittul; Shiroishi, Mark S; Grant, Edward G; Christian, Eisha; Zada, Gabriel

2016-03-01

Intraoperative contrast-enhanced ultrasound (iCEUS) offers dynamic imaging and provides functional data in real time. However, no standardized protocols or validated quantitative data exist to guide its routine use in neurosurgery. The authors aimed to provide further clinical data on the versatile application of iCEUS through a technical note and illustrative case series. Five patients undergoing craniotomies for suspected tumors were included. iCEUS was performed using a contrast agent composed of lipid shell microspheres enclosing perflutren (octafluoropropane) gas. Perfusion data were acquired through a time-intensity curve analysis protocol obtained using iCEUS prior to biopsy and/or resection of all lesions. Three primary tumors (gemistocytic astrocytoma, glioblastoma multiforme, and meningioma), 1 metastatic lesion (melanoma), and 1 tumefactive demyelinating lesion (multiple sclerosis) were assessed using real-time iCEUS. No intraoperative complications occurred following multiple administrations of contrast agent in all cases. In all neoplastic cases, iCEUS replicated enhancement patterns observed on preoperative Gd-enhanced MRI, facilitated safe tumor debulking by differentiating neoplastic tissue from normal brain parenchyma, and helped identify arterial feeders and draining veins in and around the surgical cavity. Intraoperative CEUS was also useful in guiding a successful intraoperative needle biopsy of a cerebellar tumefactive demyelinating lesion obtained during real-time perfusion analysis. Intraoperative CEUS has potential for safe, real-time, dynamic contrast-based imaging for routine use in neurooncological surgery and image-guided biopsy. Intraoperative CEUS eliminates the effect of anatomical distortions associated with standard neuronavigation and provides quantitative perfusion data in real time, which may hold major implications for intraoperative diagnosis, tissue differentiation, and quantification of extent of resection. Further prospective studies will help standardize the role of iCEUS in neurosurgery.

Monitoring Endeavour vent field deep-sea ecosystem dynamics through NEPTUNE Canada seafloor observatory

NASA Astrophysics Data System (ADS)

Matabos, M.; NC Endeavour Science Team

2010-12-01

Mid-ocean ridges are dynamic systems where the complex linkages between geological, biological, chemical, and physical processes are not yet well understood. Indeed, the poor accessibility to the marine environment has greatly limited our understanding of deep-sea ecosystems. Undersea cabled observatories offer the power and bandwidth required to conduct long-term and high-resolution time-series observations of the seafloor. Investigations of mid-ocean ridge hydrothermal ecosystem require interdisciplinary studies to better understand the dynamics of vent communities and the physico-chemical forces that influence them. NEPTUNE Canada (NC) regional observatory is located in the Northeast Pacific, off Vancouver Island (BC, Canada), and spans ecological environments from the beach to the abyss. In September-October 2010, NC will be instrumenting its 5th node, including deployment of a multi-disciplinary suite of instruments in two vent fields on the Endeavour Segment of the Juan de Fuca Ridge. These include a digital camera, an imaging sonar for vent plumes and flow characteristics (i.e. COVIS), temperature resistivity probes, a water sampler and seismometers. In 2011, the TEMPO-mini, a new custom-designed camera and sensor package created by IFREMER for real-time monitoring of hydrothermal faunal assemblages and their ecosystems (Sarrazin et al. 2007), and a microbial incubator, will added to the network in the Main Endeavour and Mothra vent fields. This multidisciplinary approach will involve a scientific community from different institutions and countries. Significant experience aids in this installation. For example, video systems connected to VENUS and NC have led to the development of new experimental protocols for time-series observations using seafloor cameras, including sampling design, camera calibration and image analysis methodologies (see communication by Aron et al. and Robert et al.). Similarly, autonomous deployment of many of the planned instruments has informed their adoption to the cabled instrument array at the Endeavour hydrothermal vents. This provides a unique laboratory for researchers to conduct long-term, integrated studies of hydrothermal vent ecosystem dynamics in relation to environmental variability at different temporal scales. In addition to programmed time-series monitoring, the NC infrastructure will also permit manual and automated modification of observational protocols in response to natural events. This will enhance our ability to document how the entire ecosystem reacts to potentially critical but short-lived environmental forces (e.g. seismic events). Sarrazin et al 2007. TEMPO: a new ecological module for studying deep-sea community dynamics at hydrothermal vents. OCEANS’07 IEEE Aberdeen Conference Proceedings

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

NASA Astrophysics Data System (ADS)

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2013-10-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose (18F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Influence of the partial volume correction method on (18)F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM.

PubMed

Bowen, Spencer L; Byars, Larry G; Michel, Christian J; Chonde, Daniel B; Catana, Ciprian

2013-10-21

Kinetic parameters estimated from dynamic (18)F-fluorodeoxyglucose ((18)F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting (18)F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment.

PubMed

Fuangrod, Todsaporn; Woodruff, Henry C; van Uytven, Eric; McCurdy, Boyd M C; Kuncic, Zdenka; O'Connor, Daryl J; Greer, Peter B

2013-09-01

To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient. The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance. The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s). A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.

Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging.

PubMed

Yarach, Uten; Tung, Yi-Hang; Setsompop, Kawin; In, Myung-Ho; Chatnuntawech, Itthi; Yakupov, Renat; Godenschweger, Frank; Speck, Oliver

2018-02-09

To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3R y 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm 3 . The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map. © 2018 International Society for Magnetic Resonance in Medicine.

Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; McCabe, Matthew F.; Angel, Yoseline; Middleton, Elizabeth M.

2016-01-01

Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI.

PubMed

Solo, Victor

2016-05-01

The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability.

State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI

PubMed Central

Solo, Victor

2017-01-01

The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability. PMID:26942749

Objective criteria for acceptability and constancy tests of digital subtraction angiography.

PubMed

de las Heras, Hugo; Torres, Ricardo; Fernández-Soto, José Miguel; Vañó, Eliseo

2016-01-01

Demonstrate an objective procedure to quantify image quality in digital subtraction angiography (DSA) and suggest thresholds for acceptability and constancy tests. Series of images were obtained in a DSA system simulating a small (paediatric) and a large patient using the dynamic phantom described in the IEC and DIN standards for acceptance tests of DSA equipment. Image quality was quantified using measurements of contrast-to-noise ratio (CNR). Overall scores combining the CNR of 10-100 mg/ml Iodine at a vascular diameter of 1-4 mm in a homogeneous background were defined. Phantom entrance surface air kerma (Ka,e) was measured with an ionisation chamber. The visibility of a low-contrast vessel in DSA images has been identified with a CNR value of 0.50 ± 0.03. Despite using 14 times more Ka,e (8.85 vs 0.63 mGy/image), the protocol for large patients showed a decrease in the overall score CNRsum of 67% (4.21 ± 0.06 vs 2.10 ± 0.05). The uncertainty in the results of the objective method was below 5%. Objective evaluation of DSA images using CNR is feasible with dedicated phantom measurements. An objective methodology has been suggested for acceptance tests compliant with the IEC/DIN standards. The defined overall scores can serve to fix a reproducible baseline for constancy tests, as well as to study the device stability within one acquisition series and compare different imaging protocols. This work provides aspects that have not been included in the recent European guidelines on Criteria for Acceptability of Medical Radiological Equipment. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Automatic Temporal Tracking of Supra-Glacial Lakes

NASA Astrophysics Data System (ADS)

Liang, Y.; Lv, Q.; Gallaher, D. W.; Fanning, D.

2010-12-01

During the recent years, supra-glacial lakes in Greenland have attracted extensive global attention as they potentially play an important role in glacier movement, sea level rise, and climate change. Previous works focused on classification methods and individual cloud-free satellite images, which have limited capabilities in terms of tracking changes of lakes over time. The challenges of tracking supra-glacial lakes automatically include (1) massive amount of satellite images with diverse qualities and frequent cloud coverage, and (2) diversity and dynamics of large number of supra-glacial lakes on the Greenland ice sheet. In this study, we develop an innovative method to automatically track supra-glacial lakes temporally using the Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data. The method works for both cloudy and cloud-free data and is unsupervised, i.e., no manual identification is required. After selecting the highest-quality image within each time interval, our method automatically detects supra-glacial lakes in individual images, using adaptive thresholding to handle diverse image qualities. We then track lakes across time series of images as lakes appear, change in size, and disappear. Using multi-year MODIS data during melting season, we demonstrate that this new method can detect and track supra-glacial lakes in both space and time with 95% accuracy. Attached figure shows an example of the current result. Detailed analysis of the temporal variation of detected lakes will be presented. (a) One of our experimental data. The Investigated region is centered at Jakobshavn Isbrae glacier in west Greenland. (b) Enlarged view of part of ice sheet. It is partially cloudy and with supra-glacial lakes on it. Lakes are shown as dark spots. (c) Current result. Red spots are detected lakes.

Identification of "ever-cropped" land (1984-2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study.

PubMed

Maxwell, Susan K; Sylvester, Kenneth M

2012-06-01

A time series of 230 intra- and inter-annual Landsat Thematic Mapper images was used to identify land that was ever cropped during the years 1984 through 2010 for a five county region in southwestern Kansas. Annual maximum Normalized Difference Vegetation Index (NDVI) image composites (NDVI(ann-max)) were used to evaluate the inter-annual dynamics of cropped and non-cropped land. Three feature images were derived from the 27-year NDVI(ann-max) image time series and used in the classification: 1) maximum NDVI value that occurred over the entire 27 year time span (NDVI(max)), 2) standard deviation of the annual maximum NDVI values for all years (NDVI(sd)), and 3) standard deviation of the annual maximum NDVI values for years 1984-1986 (NDVI(sd84-86)) to improve Conservation Reserve Program land discrimination.Results of the classification were compared to three reference data sets: County-level USDA Census records (1982-2007) and two digital land cover maps (Kansas 2005 and USGS Trends Program maps (1986-2000)). Area of ever-cropped land for the five counties was on average 11.8 % higher than the area estimated from Census records. Overall agreement between the ever-cropped land map and the 2005 Kansas map was 91.9% and 97.2% for the Trends maps. Converting the intra-annual Landsat data set to a single annual maximum NDVI image composite considerably reduced the data set size, eliminated clouds and cloud-shadow affects, yet maintained information important for discriminating cropped land. Our results suggest that Landsat annual maximum NDVI image composites will be useful for characterizing land use and land cover change for many applications.

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

NASA Astrophysics Data System (ADS)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

Pulsation Detection from Noisy Ultrasound-Echo Moving Images of Newborn Baby Head Using Fourier Transform

NASA Astrophysics Data System (ADS)

Yamada, Masayoshi; Fukuzawa, Masayuki; Kitsunezuka, Yoshiki; Kishida, Jun; Nakamori, Nobuyuki; Kanamori, Hitoshi; Sakurai, Takashi; Kodama, Souichi

1995-05-01

In order to detect pulsation from a series of noisy ultrasound-echo moving images of a newborn baby's head for pediatric diagnosis, a digital image processing system capable of recording at the video rate and processing the recorded series of images was constructed. The time-sequence variations of each pixel value in a series of moving images were analyzed and then an algorithm based on Fourier transform was developed for the pulsation detection, noting that the pulsation associated with blood flow was periodically changed by heartbeat. Pulsation detection for pediatric diagnosis was successfully made from a series of noisy ultrasound-echo moving images of newborn baby's head by using the image processing system and the pulsation detection algorithm developed here.

MHz-Rate NO PLIF Imaging in a Mach 10 Hypersonic Wind Tunnel

NASA Technical Reports Server (NTRS)

Jiang, N.; Webster, M.; Lempert, Walter R.; Miller, J. D.; Meyer, T. R.; Danehy, Paul M.

2010-01-01

NO PLIF imaging at repetition rates as high as 1 MHz is demonstrated in the NASA Langley 31 inch Mach 10 hypersonic wind tunnel. Approximately two hundred time correlated image sequences, of between ten and twenty individual frames, were obtained over eight days of wind tunnel testing spanning two entries in March and September of 2009. The majority of the image sequences were obtained from the boundary layer of a 20 flat plate model, in which transition was induced using a variety of cylindrical and triangular shaped protuberances. The high speed image sequences captured a variety of laminar and transitional flow phenomena, ranging from mostly laminar flow, typically at lower Reynolds number and/or in the near wall region of the model, to highly transitional flow in which the temporal evolution and progression of characteristic streak instabilities and/or corkscrew-shaped vortices could be clearly identified. A series of image sequences were also obtained from a 20 compression ramp at a 10 angle of attack in which the temporal dynamics of the characteristic separated flow was captured in a time correlated manner.

Quantifying forest LAI succession in sub-tropical forests using time-series of Landsat data, 1987 -2015

NASA Astrophysics Data System (ADS)

Wu, Q.; Song, J.; Wang, J.; Chen, S.; Yu, B.; Liao, L.

2016-12-01

Monitoring the dynamics of leaf area index (LAI) throughout the life-cycle of forests (from seeding to maturity) is vital for simulating forest growth and quantifying carbon sequestration. However, all current global LAI produts show extremely low accuracy in forests and the coarse spatial resolution(nearly 1-km) mismatch with the spatial scale of forest inventory plots (nearly 26m*26m). To date, several studies have explored the possibility of satellite data to classify forest succession or predict stand age. And a few studies have explored the potential of using long term Landsat data to monitor the growing trend of forests, but no studies have quantified the inter-annual and intra-annual LAI dynamics along with forest succession. Vegetation indexes are not perfect variables in quantifying forest foliage dynamics. Hallet (1995) suggested remote sensing of biophysical characteristics should shift away from direct inference from vegetation indices toward more physically based algorithms. This work intends to be a pioneer example for improving the accuracy of forests LAI and providing temporal-spatial matching LAI datasets for monitoring forest processes. We integrates the Geometric-Optical and Radiative Transfer (GORT) model with the Physiological Principles Predicting Growth (3-PG) model to improve the estimation of the forest canopy LAI dynamics. Reflectance time-series data from 1987 to 2015 were collected and preprocessed for forests in southern China, using all available Landsat data (with <80% cloud). Effective LAI and true LAI were field measured to validate our results using various instruments, including digital hemispheric photographs (DHP), LAI-2000 Plant Canopy Analyzer (LI-COR), and Tracing radiation and Architecture of Canopies (TRAC). Results show that the relationship between spectral metrics of satellite images and forest LAI is clear in early stages before maturity. 3-PG provide accurate inter-annual trend of forest LAI, while satellite images provide clear intra-annual LAI dynamics. We concluded that the GORT-3PG model improved the LAI estimation significantly of forest stands. Improving forest LAI estimates will help inform forest management policy and such methods may be applied in other similar forests.

Metabolic Imaging in Multiple Time Scales

PubMed Central

Ramanujan, V Krishnan

2013-01-01

We report here a novel combination of time-resolved imaging methods for probing mitochondrial metabolism multiple time scales at the level of single cells. By exploiting a mitochondrial membrane potential reporter fluorescence we demonstrate the single cell metabolic dynamics in time scales ranging from milliseconds to seconds to minutes in response to glucose metabolism and mitochondrial perturbations in real time. Our results show that in comparison with normal human mammary epithelial cells, the breast cancer cells display significant alterations in metabolic responses at all measured time scales by single cell kinetics, fluorescence recovery after photobleaching and by scaling analysis of time-series data obtained from mitochondrial fluorescence fluctuations. Furthermore scaling analysis of time-series data in living cells with distinct mitochondrial dysfunction also revealed significant metabolic differences thereby suggesting the broader applicability (e.g. in mitochondrial myopathies and other metabolic disorders) of the proposed strategies beyond the scope of cancer metabolism. We discuss the scope of these findings in the context of developing portable, real-time metabolic measurement systems that can find applications in preclinical and clinical diagnostics. PMID:24013043

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

PubMed

Yang, Y; Van Reeth, E; Poh, C L; Tan, C H; Tham, I W K

2014-05-01

Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

On pictures and stuff: image quality and material appearance

NASA Astrophysics Data System (ADS)

Ferwerda, James A.

2014-02-01

Realistic images are a puzzle because they serve as visual representations of objects while also being objects themselves. When we look at an image we are able to perceive both the properties of the image and the properties of the objects represented by the image. Research on image quality has typically focused improving image properties (resolution, dynamic range, frame rate, etc.) while ignoring the issue of whether images are serving their role as visual representations. In this paper we describe a series of experiments that investigate how well images of different quality convey information about the properties of the objects they represent. In the experiments we focus on the effects that two image properties (contrast and sharpness) have on the ability of images to represent the gloss of depicted objects. We found that different experimental methods produced differing results. Specifically, when the stimulus images were presented using simultaneous pair comparison, observers were influenced by the surface properties of the images and conflated changes in image contrast and sharpness with changes in object gloss. On the other hand, when the stimulus images were presented sequentially, observers were able to disregard the image plane properties and more accurately match the gloss of the objects represented by the different quality images. These findings suggest that in understanding image quality it is useful to distinguish between quality of the imaging medium and the quality of the visual information represented by that medium.

Effectively Communicating Information about Dynamically Changing Arctic Sea Ice to the Public through the Global Fiducials Program

NASA Astrophysics Data System (ADS)

Molnia, B. F.; Friesen, B.; Wilson, E.; Noble, S.

2015-12-01

On July 15, 2009, the National Academy of Sciences (NAS) released a report, Scientific Value of Arctic Sea Ice Imagery Derived Products, advocating public release of Arctic images derived from classified data. In the NAS press release that announced the release, report lead Stephanie Pfirman states "To prepare for a possibly ice-free Arctic and its subsequent effects on the environment, economy, and national security, it is critical to have accurate projections of changes over the next several decades." In the same release NAS President Ralph Cicerone states "We hope that these images are the first of many that could help scientists learn how the changing climate could impact the environment and our society." The same day, Secretary of the Interior Ken Salazar announced that the requested images had been released and were available to the public on a US Geological Survey Global Fiducials Program (GFP) Library website (http://gfl.usgs.gov). The website was developed by the USGS to provide public access to the images and to support environmental analysis of global climate-related science. In the statement describing the release titled, Information Derived from Classified Materials Will Aid Understanding of Changing Climate, Secretary Salazar states "We need the best data from all places if we are to meet the challenges that rising carbon emissions are creating. This information will be invaluable to scientists, researchers, and the public as we tackle climate change." Initially about 700 Arctic sea ice images were released. Six years later, the number exceeds 1,500. The GFP continues to facilitate the acquisition of new Arctic sea ice imagery from US National Imagery Systems. This example demonstrates how information about dynamically changing Arctic sea ice continues to be effectively communicated to the public by the GFP. In addition to Arctic sea ice imagery, the GFP has publicly released imagery time series of more than 125 other environmentally important geographic locations. Recently, the GFP has developed a second website (http://gfp.usgs.gov) to provide more in-depth scientific descriptions of the time series to the public.

a Method of Time-Series Change Detection Using Full Polsar Images from Different Sensors

NASA Astrophysics Data System (ADS)

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

2018-04-01

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by Rj statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can detect the time-series change from different sensors.

Live-Cell Imaging of F-Actin Dynamics During Fertilization in Arabidopsis thaliana.

PubMed

Susaki, Daichi; Maruyama, Daisuke; Yelagandula, Ramesh; Berger, Frederic; Kawashima, Tomokazu

2017-01-01

Fertilization comprises a complex series of cellular processes leading to the fusion of a male and female gamete. Many studies have been carried out to investigate each step of fertilization in plants; however, our comprehensive understanding of all the sequential events during fertilization is still limited. This is largely due to difficulty in investigating events in the female gametophyte, which is deeply embedded in the maternal tissue. Recent advances in confocal microcopy assisted by fluorescent marker lines have contributed to visualizing subcellular dynamics in real time during fertilization in vivo. In this chapter, we describe a method focusing on the investigation of F-actin dynamics in the central cell during male gamete nuclear migration. This method also allows the study of a wide range of early sexual reproduction events, from pollen tube guidance to the early stage of seed development.

Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies.

PubMed

Strauss, Ludwig G; Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2011-03-01

(18)F-FDG kinetics are quantified by a 2-tissue-compartment model. The routine use of dynamic PET is limited because of this modality's 1-h acquisition time. We evaluated shortened acquisition protocols up to 0-30 min regarding the accuracy for data analysis with the 2-tissue-compartment model. Full dynamic series for 0-60 min were analyzed using a 2-tissue-compartment model. The time-activity curves and the resulting parameters for the model were stored in a database. Shortened acquisition data were generated from the database using the following time intervals: 0-10, 0-16, 0-20, 0-25, and 0-30 min. Furthermore, the impact of adding a 60-min uptake value to the dynamic series was evaluated. The datasets were analyzed using dedicated software to predict the results of the full dynamic series. The software is based on a modified support vector machines (SVM) algorithm and predicts the compartment parameters of the full dynamic series. The SVM-based software provides user-independent results and was accurate at predicting the compartment parameters of the full dynamic series. If a squared correlation coefficient of 0.8 (corresponding to 80% explained variance of the data) was used as a limit, a shortened acquisition of 0-16 min was accurate at predicting the 60-min 2-tissue-compartment parameters. If a limit of 0.9 (90% explained variance) was used, a dynamic series of at least 0-20 min together with the 60-min uptake values is required. Shortened acquisition protocols can be used to predict the parameters of the 2-tissue-compartment model. Either a dynamic PET series of 0-16 min or a combination of a dynamic PET/CT series of 0-20 min and a 60-min uptake value is accurate for analysis with a 2-tissue-compartment model.

A large-signal dynamic simulation for the series resonant converter

NASA Technical Reports Server (NTRS)

King, R. J.; Stuart, T. A.

1983-01-01

A simple nonlinear discrete-time dynamic model for the series resonant dc-dc converter is derived using approximations appropriate to most power converters. This model is useful for the dynamic simulation of a series resonant converter using only a desktop calculator. The model is compared with a laboratory converter for a large transient event.

Robotics and dynamic image analysis for studies of gene expression in plant tissues.

PubMed

Hernandez-Garcia, Carlos M; Chiera, Joseph M; Finer, John J

2010-05-05

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections.

Optical Modeling Activities for the James Webb Space Telescope (JWST) Project. II; Determining Image Motion and Wavefront Error Over an Extended Field of View with a Segmented Optical System

NASA Technical Reports Server (NTRS)

Howard, Joseph M.; Ha, Kong Q.

2004-01-01

This is part two of a series on the optical modeling activities for JWST. Starting with the linear optical model discussed in part one, we develop centroid and wavefront error sensitivities for the special case of a segmented optical system such as JWST, where the primary mirror consists of 18 individual segments. Our approach extends standard sensitivity matrix methods used for systems consisting of monolithic optics, where the image motion is approximated by averaging ray coordinates at the image and residual wavefront error is determined with global tip/tilt removed. We develop an exact formulation using the linear optical model, and extend it to cover multiple field points for performance prediction at each instrument aboard JWST. This optical model is then driven by thermal and dynamic structural perturbations in an integrated modeling environment. Results are presented.

Evaluating methods for controlling depth perception in stereoscopic cinematography

NASA Astrophysics Data System (ADS)

Sun, Geng; Holliman, Nick

2009-02-01

Existing stereoscopic imaging algorithms can create static stereoscopic images with perceived depth control function to ensure a compelling 3D viewing experience without visual discomfort. However, current algorithms do not normally support standard Cinematic Storytelling techniques. These techniques, such as object movement, camera motion, and zooming, can result in dynamic scene depth change within and between a series of frames (shots) in stereoscopic cinematography. In this study, we empirically evaluate the following three types of stereoscopic imaging approaches that aim to address this problem. (1) Real-Eye Configuration: set camera separation equal to the nominal human eye interpupillary distance. The perceived depth on the display is identical to the scene depth without any distortion. (2) Mapping Algorithm: map the scene depth to a predefined range on the display to avoid excessive perceived depth. A new method that dynamically adjusts the depth mapping from scene space to display space is presented in addition to an existing fixed depth mapping method. (3) Depth of Field Simulation: apply Depth of Field (DOF) blur effect to stereoscopic images. Only objects that are inside the DOF are viewed in full sharpness. Objects that are far away from the focus plane are blurred. We performed a human-based trial using the ITU-R BT.500-11 Recommendation to compare the depth quality of stereoscopic video sequences generated by the above-mentioned imaging methods. Our results indicate that viewers' practical 3D viewing volumes are different for individual stereoscopic displays and viewers can cope with much larger perceived depth range in viewing stereoscopic cinematography in comparison to static stereoscopic images. Our new dynamic depth mapping method does have an advantage over the fixed depth mapping method in controlling stereo depth perception. The DOF blur effect does not provide the expected improvement for perceived depth quality control in 3D cinematography. We anticipate the results will be of particular interest to 3D filmmaking and real time computer games.

Identification of Dust Source Regions at High-Resolution and Dynamics of Dust Source Mask over Southwest United States Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Sprigg, W. A.; Sahoo, S.; Prasad, A. K.; Venkatesh, A. S.; Vukovic, A.; Nickovic, S.

2015-12-01

Identification and evaluation of sources of aeolian mineral dust is a critical task in the simulation of dust. Recently, time series of space based multi-sensor satellite images have been used to identify and monitor changes in the land surface characteristics. Modeling of windblown dust requires precise delineation of mineral dust source and its strength that varies over a region as well as seasonal and inter-annual variability due to changes in land use and land cover. Southwest USA is one of the major dust emission prone zone in North American continent where dust is generated from low lying dried-up areas with bare ground surface and they may be scattered or appear as point sources on high resolution satellite images. In the current research, various satellite derived variables have been integrated to produce a high-resolution dust source mask, at grid size of 250 m, using data such as digital elevation model, surface reflectance, vegetation cover, land cover class, and surface wetness. Previous dust source models have been adopted to produce a multi-parameter dust source mask using data from satellites such as Terra (Moderate Resolution Imaging Spectroradiometer - MODIS), and Landsat. The dust source mask model captures the topographically low regions with bare soil surface, dried-up river plains, and lakes which form important source of dust in southwest USA. The study region is also one of the hottest regions of USA where surface dryness, land use (agricultural use), and vegetation cover changes significantly leading to major changes in the areal coverage of potential dust source regions. A dynamic high resolution dust source mask have been produced to address intra-annual change in the aerial extent of bare dry surfaces. Time series of satellite derived data have been used to create dynamic dust source masks. A new dust source mask at 16 day interval allows enhanced detection of potential dust source regions that can be employed in the dust emission and transport pathways models for better estimation of emission of dust during dust storms, particulate air pollution, public health risk assessment tools and decision support systems.

[MRI methods for pulmonary ventilation and perfusion imaging].

PubMed

Sommer, G; Bauman, G

2016-02-01

Separate assessment of respiratory mechanics, gas exchange and pulmonary circulation is essential for the diagnosis and therapy of pulmonary diseases. Due to the global character of the information obtained clinical lung function tests are often not sufficiently specific in the differential diagnosis or have a limited sensitivity in the detection of early pathological changes. The standard procedures of pulmonary imaging are computed tomography (CT) for depiction of the morphology as well as perfusion/ventilation scintigraphy and single photon emission computed tomography (SPECT) for functional assessment. Magnetic resonance imaging (MRI) with hyperpolarized gases, O2-enhanced MRI, MRI with fluorinated gases and Fourier decomposition MRI (FD-MRI) are available for assessment of pulmonary ventilation. For assessment of pulmonary perfusion dynamic contrast-enhanced MRI (DCE-MRI), arterial spin labeling (ASL) and FD-MRI can be used. Imaging provides a more precise insight into the pathophysiology of pulmonary function on a regional level. The advantages of MRI are a lack of ionizing radiation, which allows a protective acquisition of dynamic data as well as the high number of available contrasts and therefore accessible lung function parameters. Sufficient clinical data exist only for certain applications of DCE-MRI. For the other techniques, only feasibility studies and case series of different sizes are available. The clinical applicability of hyperpolarized gases is limited for technical reasons. The clinical application of the techniques described, except for DCE-MRI, should be restricted to scientific studies.

Photon statistics and speckle visibility spectroscopy with partially coherent X-rays.

PubMed

Li, Luxi; Kwaśniewski, Paweł; Orsi, Davide; Wiegart, Lutz; Cristofolini, Luigi; Caronna, Chiara; Fluerasu, Andrei

2014-11-01

A new approach is proposed for measuring structural dynamics in materials from multi-speckle scattering patterns obtained with partially coherent X-rays. Coherent X-ray scattering is already widely used at high-brightness synchrotron lightsources to measure dynamics using X-ray photon correlation spectroscopy, but in many situations this experimental approach based on recording long series of images (i.e. movies) is either not adequate or not practical. Following the development of visible-light speckle visibility spectroscopy, the dynamic information is obtained instead by analyzing the photon statistics and calculating the speckle contrast in single scattering patterns. This quantity, also referred to as the speckle visibility, is determined by the properties of the partially coherent beam and other experimental parameters, as well as the internal motions in the sample (dynamics). As a case study, Brownian dynamics in a low-density colloidal suspension is measured and an excellent agreement is found between correlation functions measured by X-ray photon correlation spectroscopy and the decay in speckle visibility with integration time obtained from the analysis presented here.

Intravascular lymphoma: magnetic resonance imaging correlates of disease dynamics within the central nervous system

PubMed Central

Baehring, J; Henchcliffe, C; Ledezma, C; Fulbright, R; Hochberg, F

2005-01-01

Background: Intravascular lymphoma (IVL) is a rare non-Hodgkin's lymphoma with relative predilection for the central nervous system. In the absence of extraneural manifestations, the disease is not recognised until autopsy in the majority of cases underlining the need for new clinical markers. Methods: This is a retrospective series of five patients with IVL seen at a single institution over three years. An advanced magnetic resonance imaging (MRI) protocol was performed at various time points prior to diagnosis and during treatment. Results: MRI revealed multiple lesions scattered throughout the cerebral hemispheres; the brainstem, cerebellum, and spinal cord were less frequently involved. On initial presentation, hyperintense lesions were seen on diffusion weighted images suggestive of ischaemia in three of four patients in whom the images were obtained at that time point. In four patients lesions were also identifiable as hyperintense areas on fluid attenuated inversion recovery (FLAIR) sequences. Initial contrast enhancement was encountered in three cases. Diffusion weighted imaging lesions either vanished or followed the typical pattern of an ischaemic small vessel stroke with evolution of abnormal FLAIR signal followed by enhancement with gadolinium in the subacute stage and tissue loss in the chronic stage. Diffusion weighted imaging and FLAIR abnormalities proved to be partially reversible, correlating with the response to chemotherapy. Conclusion: We provide the first detailed description of the dynamic pattern of diffusion weighted MRI in IVL. These patterns in combination with systemic findings may facilitate early diagnosis and serve as a new tool to monitor treatment response. PMID:15774442

Fast Atomic-Scale Chemical Imaging of Crystalline Materials and Dynamic Phase Transformations

DOE PAGES

Lu, Ping; Yuan, Ren Liang; Ihlefeld, Jon F.; ...

2016-03-04

Chemical imaging at the atomic-scale provides a useful real-space approach to chemically investigate solid crystal structures, and has been recently demonstrated in aberration corrected scanning transmission electron microscopy (STEM). Atomic-scale chemical imaging by STEM using energy-dispersive X-ray spectroscopy (EDS) offers easy data interpretation with a one-to-one correspondence between image and structure but has a severe shortcoming due to the poor efficiency of X-ray generation and collection. As a result, it requires a long acquisition time of typical > few 100 seconds, limiting its potential applications. Here we describe the development of an atomic-scale STEM EDS chemical imaging technique that cutsmore » the acquisition time to one or a few seconds, efficiently reducing the acquisition time by more than 100 times. This method was demonstrated using LaAlO 3 (LAO) as a model crystal. Applying this method to the study of phase transformation induced by electron-beam radiation in a layered lithium transition-metal (TM) oxide, i.e., Li[Li 0.2Ni 0.2Mn 0.6]O 2 (LNMO), a cathode materials for lithium-ion batteries, we obtained a time-series of the atomic-scale chemical imaging, showing the transformation progressing by preferably jumping of Ni atoms from the TM layers into the Li-layers. The new capability offers an opportunity for temporal, atomic-scale chemical mapping of crystal structures for the investigation of materials susceptible to electron irradiation as well as phase transformation and dynamics at the atomic-scale.« less

Characterizing system dynamics with a weighted and directed network constructed from time series data

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

Sun, Xiaoran, E-mail: sxr0806@gmail.com; School of Mathematics and Statistics, The University of Western Australia, Crawley WA 6009; Small, Michael, E-mail: michael.small@uwa.edu.au

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the timemore » series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics.« less

High dynamic range image acquisition based on multiplex cameras

NASA Astrophysics Data System (ADS)

Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

2018-03-01

High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

Thermal imaging for cold air flow visualisation and analysis

NASA Astrophysics Data System (ADS)

Grudzielanek, M.; Pflitsch, A.; Cermak, J.

2012-04-01

In this work we present first applications of a thermal imaging system for animated visualization and analysis of cold air flow in field studies. The development of mobile thermal imaging systems advanced very fast in the last decades. The surface temperature of objects, which is detected with long-wave infrared radiation, affords conclusions in different problems of research. Modern thermal imaging systems allow infrared picture-sequences and a following data analysis; the systems are not exclusive imaging methods like in the past. Thus, the monitoring and analysing of dynamic processes became possible. We measured the cold air flow on a sloping grassland area with standard methods (sonic anemometers and temperature loggers) plus a thermal imaging system measuring in the range from 7.5 to 14µm. To analyse the cold air with the thermal measurements, we collected the surface infrared temperatures at a projection screen, which was located in cold air flow direction, opposite the infrared (IR) camera. The intention of using a thermal imaging system for our work was: 1. to get a general idea of practicability in our problem, 2. to assess the value of the extensive and more detailed data sets and 3. to optimise visualisation. The results were very promising. Through the possibility of generating time-lapse movies of the image sequences in time scaling, processes of cold air flow, like flow waves, turbulence and general flow speed, can be directly identified. Vertical temperature gradients and near-ground inversions can be visualised very well. Time-lapse movies will be presented. The extensive data collection permits a higher spatial resolution of the data than standard methods, so that cold air flow attributes can be explored in much more detail. Time series are extracted from the IR data series, analysed statistically, and compared to data obtained using traditional systems. Finally, we assess the usefulness of the additional measurement of cold air flow with thermal imaging systems.

Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

NASA Astrophysics Data System (ADS)

Li, Jing; Fan, Ming; Zhang, Juan; Li, Lihua

2017-03-01

Convolutional neural networks (CNNs) are the state-of-the-art deep learning network architectures that can be used in a range of applications, including computer vision and medical image analysis. It exhibits a powerful representation learning mechanism with an automated design to learn features directly from the data. However, the common 2D CNNs only use the two dimension spatial information without evaluating the correlation between the adjoin slices. In this study, we established a method of 3D CNNs to discriminate between malignant and benign breast tumors. To this end, 143 patients were enrolled which include 66 benign and 77 malignant instances. The MRI images were pre-processed for noise reduction and breast tumor region segmentation. Data augmentation by spatial translating, rotating and vertical and horizontal flipping is applied to the cases to reduce possible over-fitting. A region-of-interest (ROI) and a volume-of-interest (VOI) were segmented in 2D and 3D DCE-MRI, respectively. The enhancement ratio for each MR series was calculated for the 2D and 3D images. The results for the enhancement ratio images in the two series are integrated for classification. The results of the area under the ROC curve(AUC) values are 0.739 and 0.801 for 2D and 3D methods, respectively. The results for 3D CNN which combined 5 slices for each enhancement ratio images achieved a high accuracy(Acc), sensitivity(Sens) and specificity(Spec) of 0.781, 0.744 and 0.823, respectively. This study indicates that 3D CNN deep learning methods can be a promising technology for breast tumor classification without manual feature extraction.

SUVI Thematic Maps: A new tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Hughes, J. M.; Seaton, D. B.; Darnel, J.

2017-12-01

The new Solar Ultraviolet Imager (SUVI) instruments aboard NOAA's GOES-R series satellites collect continuous, high-quality imagery of the Sun in six wavelengths. SUVI imagers produce at least one image every 10 seconds, or 8,640 images per day, considerably more data than observers can digest in real time. Over the projected 20-year lifetime of the four GOES-R series spacecraft, SUVI will provide critical imagery for space weather forecasters and produce an extensive but unwieldy archive. In order to condense the database into a dynamic and searchable form we have developed solar thematic maps, maps of the Sun with key features, such as coronal holes, flares, bright regions, quiet corona, and filaments, identified. Thematic maps will be used in NOAA's Space Weather Prediction Center to improve forecaster response time to solar events and generate several derivative products. Likewise, scientists use thematic maps to find observations of interest more easily. Using an expert-trained, naive Bayesian classifier to label each pixel, we create thematic maps in real-time. We created software to collect expert classifications of solar features based on SUVI images. Using this software, we compiled a database of expert classifications, from which we could characterize the distribution of pixels associated with each theme. Given new images, the classifier assigns each pixel the most appropriate label according to the trained distribution. Here we describe the software to collect expert training and the successes and limitations of the classifier. The algorithm excellently identifies coronal holes but fails to consistently detect filaments and prominences. We compare the Bayesian classifier to an artificial neural network, one of our attempts to overcome the aforementioned limitations. These results are very promising and encourage future research into an ensemble classification approach.

Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2001-01-01

Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

Charge transfer excitons and image potential states on organic semiconductor surfaces

NASA Astrophysics Data System (ADS)

Yang, Qingxin; Muntwiler, Matthias; Zhu, X.-Y.

2009-09-01

We report two types of excited electronic states on organic semiconductor surfaces: image potential states (IPS) and charge transfer excitons (CTE). In the former, an excited electron is localized in the surface-normal direction by the image potential and delocalized in the surface plane. In the latter, the electron is localized in all directions by both the image potential and the Coulomb potential from a photogenerated hole on an organic molecule. We use crystalline pentacene and tetracene surfaces as model systems, and time- and angle-resolved two-photon photoemission spectroscopy to probe the energetics and dynamics of both the IPS and the CTE states. On either pentacene or tetracene surfaces, we observe delocalized image bands and a series of CT excitons with binding energies <0.5eV below the image-band minimum. The binding energies of these CT excitons agree well with solutions to the atomic-H-like Schrödinger equation based on the image potential and the electron-hole Coulomb potential. We hypothesize that the formation of CT excitons should be general to the surfaces of organic semiconductors where the relatively narrow valance-band width facilitates the localization of the hole and the low dielectric constant ensures strong electron-hole attraction.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Monitoring landslide dynamics using timeseries of UAV imagery

NASA Astrophysics Data System (ADS)

de Jong, S. M.; Van Beek, L. P.

2017-12-01

Landslides are worldwide occurring processes that can have large economic impact and sometimes result in fatalities. Multiple factors are important in landslide processes and can make an area prone to landslide activity. Human factors like drainage and removal of vegetation or land clearing are examples of factors that may cause a landslide. Other environmental factors such as topography and the shear strength of the slope material are more difficult to control. Triggering factors for landslides are typically heavy rainfall events or sometimes by earthquakes or under cutting processes by a river. The collection of data about existing landslides in a given area is important for predicting future landslides in that region. We have setup a monitoring program for landslide using cameras aboard Unmanned Airborne Vehicles. UAV with cameras are able to collect ultra-high resolution images and UAVs can be operated in a very flexible way, they just fit in the back of a car. Here, in this study we used Unmanned Aerial Vehicles to collect a time series of high-resolution images over landslides in France and Australia. The algorithm used to process the UAV images into OrthoMosaics and OrthoDEMs is Structure from Motion (SfM). The process generally results in centimeter precision in the horizontal and vertical direction. Such multi-temporal datasets enable the detection of landslide area, the leading edge slope, temporal patterns and volumetric changes of particular areas of the landslide. We measured and computed surface movement of the landslide using the COSI-Corr image correlation algorithm with ground validation. Our study shows the possibilities of generating accurate Digital Surface Models (DSMs) of landslides using images collected with an Unmanned Aerial Vehicle (UAV). The technique is robust and repeatable such that a substantial time series of datasets can be routinely collected. It is shown that a time-series of UAV images can be used to map landslide movements with centimeter accuracy. It also found that there can be a cyclical nature to the slope of the leading edge of the landslide, suggesting that the steepness of the slope can be used to predict the next forward surge of the leading edge.

Structural Response Prediction: Full-field, Dynamic Pressure and Displacement Measurements of a Panel Excited by Shock Boundary-layer Interaction

DTIC Science & Technology

2015-02-01

research cell14. The RC-19 facility is a continuous flow wind tunnel designed to study the mechanisms that govern the mixing and combustion process... angle of 39° from the tunnel bottom wall. The shock generator can translate 170 mm in the flow direction to allow for the shock wave to impinge from...approximate absolute pressure of 20.5 kPa. A series of “ wind -off” images for PSP were collected at that time. The tunnel was then started by setting the

Satellite Monitoring of the Northern Territories Disturbed by Oil Production

NASA Astrophysics Data System (ADS)

Bondur, V. G.; Vorobyev, V. E.; Lukin, A. A.

2017-12-01

The results of satellite monitoring of the state of northern territories disturbed by oil production are presented by the example of the Usinsk oil field in the Komi Republic. The sets of vegetation indices formed by the results of processing long-term series of multispectral satellite images for the period from 1988 to 2014 are analyzed. They are used to assess long-term environmental changes, to reveal the most disturbed zones, and to estimate the dynamics of changes in the vegetation cover area caused by the extraction and transportation of hydrocarbons.

Comparative Analysis of Volcanic Inflation—Deflation Cycles

NASA Astrophysics Data System (ADS)

Walwer, D.; Ghil, M.; Calais, E.

2016-12-01

GPS geodetic data together with INSAR images are often used to formulate kinematic models of the sources of volcanic deformations. The increasing amount of data now available allows one to produce time series that are several years long and thus capture continuously the history of volcanic deformations, in particular their nonlinear behavior. This information is highly valuable in helping understand the dynamics of volcanic systems.Nonlinear deformation signals are, however, difficult to extract from the background noise inherent in the GPS time series. It is also arduous to unravel the signal of interest from other nonlinear signals, such as the seasonal oscillations associated with mass variations in the atmosphere, the ocean, and the hydrological reservoirs. Here we use Multichannel Singular Spectrum Analysis (M-SSA) — an advanced, data-adaptive method for time series analysis that exploits simultaneously the temporal and spatial correlations of geophysical fields — to extract such deformation signals.We apply M-SSA to GPS data sets from four volcanoes: Akutan, Alaska; Okmok, Alaska; Westdahl, Alaska; and Piton de la Fournaise, La Reunion. Our analyses show that all four volcanoes share similar features in their deformation history, suggesting similarities in the dynamics that generate the inflation-deflation cycles. In particular, all four volcanic systems exhibit sawtooth-shaped oscillations with slow inflations followed by slower deflations, with time scales that vary from 6 months to 4 years. This relation of dynamical similarity is further highlighted by the phase portrait reconstruction of the four systems in the plane of deformation vs. rate-of-deformation, as obtained from the deformation signals extracted from the GPS time series using M-SSA.The inflating phase of these oscillations is followed by eruptions at Okmok volcano and at Piton de la Fournaise. These analysis results suggest that these volcanic inflation—deflation cycles are associated with the destabilization of a volcanic system and may lead to the identification of premonitory signals for an eruptive regime.

Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings.

PubMed

Liu, Yang; Ning, Yong; Li, Sheng; Zhou, Ping; Rymer, William Z; Zhang, Yingchun

2015-09-01

There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3D IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their MU action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings.

Solar thematic maps for space weather operations

USGS Publications Warehouse

Rigler, E. Joshua; Hill, Steven M.; Reinard, Alysha A.; Steenburgh, Robert A.

2012-01-01

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

THREE-DIMENSIONAL INNERVATION ZONE IMAGING FROM MULTI-CHANNEL SURFACE EMG RECORDINGS

PubMed Central

LIU, YANG; NING, YONG; LI, SHENG; ZHOU, PING; RYMER, WILLIAM Z.; ZHANG, YINGCHUN

2017-01-01

There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3-dimensional IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their motor unit action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings. PMID:26160432

CSF Venous Fistulas in Spontaneous Intracranial Hypotension: Imaging Characteristics on Dynamic and CT Myelography.

PubMed

Kranz, Peter G; Amrhein, Timothy J; Gray, Linda

2017-12-01

The objective of this study is to describe the anatomic and imaging features of CSF venous fistulas, which are a recently reported cause of spontaneous intracranial hypotension (SIH). We retrospectively reviewed the records of patients with SIH caused by CSF venous fistulas who received treatment at our institution. The anatomic details of each fistula were recorded. Attenuation of the veins involved by the fistula was compared with that of adjacent control veins on CT myelography (CTM). Visibility of the CSF venous fistula on CTM and a modified conventional myelography technique we refer to as dynamic myelography was also compared. Twenty-two cases of CSF venous fistula were identified. The fistulas were located between T4 and L1. Ninety percent occurred without a concurrent epidural CSF leak. In most cases (82%), the CSF venous fistula originated from a nerve root sleeve diverticulum. On CTM, the abnormal veins associated with the CSF venous fistula were seen in a paravertebral location in 45% of cases, centrally within the epidural venous plexus in 32%, and lateral to the spine in 23%. Differences in attenuation between the fistula veins and the control veins was highly statistically significant (p < 0.0001), with a threshold of 70 HU perfectly discriminating fistulas from normal veins in our series. When both CTM and dynamic myelography were performed, the fistula was identified on both modalities in 88% of cases. CSF venous fistulas are an important cause of SIH that can be detected on both CTM and dynamic myelograph y and may occur without an epidural CSF leak. Familiarity with the imaging characteristics of these lesions is critical to providing appropriate treatment to patients with SIH.

From fast fluorescence imaging to molecular diffusion law on live cell membranes in a commercial microscope.

PubMed

Di Rienzo, Carmine; Gratton, Enrico; Beltram, Fabio; Cardarelli, Francesco

2014-10-09

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn't need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.

Long-term 4D Geoelectrical Imaging of Moisture Dynamics in an Active Landslide

NASA Astrophysics Data System (ADS)

Uhlemann, S.; Chambers, J. E.; Wilkinson, P. B.; Maurer, H.; Meldrum, P.; Gunn, D.; Smith, A.; Dijkstra, T.

2016-12-01

Landslides are a major natural hazard, endangering communities and infrastructure worldwide. Mitigating landslide risk relies on understanding causes and triggering processes, which are often linked to moisture dynamics in slopes causing material softening and elevated pore water pressures. Geoelectrical monitoring is frequently applied to study landslide hydrology. However, its sensitivity to sensor movements has been a challenge for long-term studies on actively failing slopes. Although 2D data acquisition has previously been favoured, it provides limited resolution and relatively poor representation of important 3D landslide structures. We present a novel methodology to incorporate electrode movements into a time-lapse 3D inversion workflow, resulting in a virtually artefact-free time-series of resistivity models. Using temperature correction and laboratory hydro-geophysical relationships, resistivity models are translated into models of moisture content. The data span more than three years, enabling imaging of processes pre- and post landslide reactivation. In the two years before reactivation, the models showed surficial wetting and drying, drainage pathways, and deeper groundwater dynamics. During reactivation, exceptionally high moisture contents were imaged throughout the slope, which was confirmed by independent measurements. Preferential flow was imaged that stabilized parts of the landslide by diverting moisture, and thus dissipating pore pressures, from the slip surface. The results highlight that moisture levels obtained from resistivity monitoring may provide a better activity threshold than rainfall intensity. Based on this work, pro-active remediation measures could be designed and effective early-warning systems implemented. Eventually, resistivity monitoring that can account for moving electrodes may provide a new means for pro-active mitigation of landslide risk, especially for communities and critical infrastructure.

Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

NASA Astrophysics Data System (ADS)

Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

2018-03-01

In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

Dynamics of a fringe mangrove forest detected by Landsat images in the Mekong delta, Vietnam

NASA Astrophysics Data System (ADS)

Fagherazzi, S.; Nardin, W.; Woodcock, C. E.; Locatelli, S.; Rulli, M. C.; Pasquarella, V. J.

2016-02-01

Mangrove forests dominate many tropical coastlines and are one of the most bio-diverse and productive environments on Earth. However, little is known of the large scale dynamics of mangrove canopies and how they colonize intertidal areas. Here we focus on a fringe mangrove forest located in the Mekong delta, Vietnam, a fast prograding shoreline where mangroves are encroaching tidal flats. The spatial and temporal evolution of the mangrove canopy is studied using a time series of Landsat images spanning two decades as well as Shuttle Radar Topography Mission (SRTM) elevation data. Our results show that fast mangrove expansion is followed by an increase in Normalized Difference Vegetation Index (NDVI) in the newly established canopy. We observe two different dynamics of the mangrove fringe: near the mouth of the rivers where the fringe boundary is linear the canopy expands uniformly on the tidal flats with a high colonization rate and high NDVI values. Far from the river mouths the fringe boundary is highly irregular and mangroves expansion in characterized by sparse vegetated patches displaying low NDVI values. We conclude that high NDVI values and a regular vegetation-water interface are indicative of stable mangrove canopies undergoing expansion, and therefore of resilient coastlines. In the Mekong delta these area are more likely located near a river mouth.

Automatic assessment of dynamic contrast-enhanced MRI in an ischemic rat hindlimb model: an exploratory study of transplanted multipotent progenitor cells.

PubMed

Hsu, Li-Yueh; Wragg, Andrew; Anderson, Stasia A; Balaban, Robert S; Boehm, Manfred; Arai, Andrew E

2008-02-01

This study presents computerized automatic image analysis for quantitatively evaluating dynamic contrast-enhanced MRI in an ischemic rat hindlimb model. MRI at 7 T was performed on animals in a blinded placebo-controlled experiment comparing multipotent adult progenitor cell-derived progenitor cell (MDPC)-treated, phosphate buffered saline (PBS)-injected, and sham-operated rats. Ischemic and non-ischemic limb regions of interest were automatically segmented from time-series images for detecting changes in perfusion and late enhancement. In correlation analysis of the time-signal intensity histograms, the MDPC-treated limbs correlated well with their corresponding non-ischemic limbs. However, the correlation coefficient of the PBS control group was significantly lower than that of the MDPC-treated and sham-operated groups. In semi-quantitative parametric maps of contrast enhancement, there was no significant difference in hypo-enhanced area between the MDPC and PBS groups at early perfusion-dependent time frames. However, the late-enhancement area was significantly larger in the PBS than the MDPC group. The results of this exploratory study show that MDPC-treated rats could be objectively distinguished from PBS controls. The differences were primarily determined by late contrast enhancement of PBS-treated limbs. These computerized methods appear promising for assessing perfusion and late enhancement in dynamic contrast-enhanced MRI.

Slower Rate of Binocular Rivalry in Autism

PubMed Central

Kravitz, Dwight J.; Freyberg, Jan; Baron-Cohen, Simon; Baker, Chris I.

2013-01-01

An imbalance between cortical excitation and inhibition is a central component of many models of autistic neurobiology. We tested a potential behavioral footprint of this proposed imbalance using binocular rivalry, a visual phenomenon in which perceptual experience is thought to mirror the push and pull of excitatory and inhibitory cortical dynamics. In binocular rivalry, two monocularly presented images compete, leading to a percept that alternates between them. In a series of trials, we presented separate images of objects (e.g., a baseball and a broccoli) to each eye using a mirror stereoscope and asked human participants with autism and matched control subjects to continuously report which object they perceived, or whether they perceived a mixed percept. Individuals with autism demonstrated a slower rate of binocular rivalry alternations than matched control subjects, with longer durations of mixed percepts and an increased likelihood to revert to the previously perceived object when exiting a mixed percept. Critically, each of these findings was highly predictive of clinical measures of autistic symptomatology. Control “playback” experiments demonstrated that differences in neither response latencies nor response criteria could account for the atypical dynamics of binocular rivalry we observed in autistic spectrum conditions. Overall, these results may provide an index of atypical cortical dynamics that may underlie both the social and nonsocial symptoms of autism. PMID:24155303

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

NASA Astrophysics Data System (ADS)

Lu, Yong; Zhang, Mingliang; Gao, Dong

2014-02-01

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improved image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

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

Lu, Yong; Zhang, Mingliang, E-mail: niudun12@126.com; Gao, Dong

2014-02-14

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improvedmore » image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.« less

High-frequency ultrasound annular array imaging. Part II: digital beamformer design and imaging.

PubMed

Hu, Chang-Hong; Snook, Kevin A; Cao, Pei-Jie; Shung, K Kirk

2006-02-01

This is the second part of a two-paper series reporting a recent effort in the development of a high-frequency annular array ultrasound imaging system. In this paper an imaging system composed of a six-element, 43 MHz annular array transducer, a six-channel analog front-end, a field programmable gate array (FPGA)-based beamformer, and a digital signal processor (DSP) microprocessor-based scan converter will be described. A computer is used as the interface for image display. The beamformer that applies delays to the echoes for each channel is implemented with the strategy of combining the coarse and fine delays. The coarse delays that are integer multiples of the clock periods are achieved by using a first-in-first-out (FIFO) structure, and the fine delays are obtained with a fractional delay (FD) filter. Using this principle, dynamic receiving focusing is achieved. The image from a wire phantom obtained with the imaging system was compared to that from a prototype ultrasonic backscatter microscope with a 45 MHz single-element transducer. The improved lateral resolution and depth of field from the wire phantom image were observed. Images from an excised rabbit eye sample also were obtained, and fine anatomical structures were discerned.

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

PubMed

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration. Convergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images. Direct reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET. © 2017 American Association of Physicists in Medicine.

The iMars WebGIS - Spatio-Temporal Data Queries and Single Image Map Web Services

NASA Astrophysics Data System (ADS)

Walter, Sebastian; Steikert, Ralf; Schreiner, Bjoern; Muller, Jan-Peter; van Gasselt, Stephan; Sidiropoulos, Panagiotis; Lanz-Kroechert, Julia

2017-04-01

Introduction: Web-based planetary image dissemination platforms usually show outline coverages of the data and offer querying for metadata as well as preview and download, e.g. the HRSC Mapserver (Walter & van Gasselt, 2014). Here we introduce a new approach for a system dedicated to change detection by simultanous visualisation of single-image time series in a multi-temporal context. While the usual form of presenting multi-orbit datasets is the merge of the data into a larger mosaic, we want to stay with the single image as an important snapshot of the planetary surface at a specific time. In the context of the EU FP-7 iMars project we process and ingest vast amounts of automatically co-registered (ACRO) images. The base of the co-registration are the high precision HRSC multi-orbit quadrangle image mosaics, which are based on bundle-block-adjusted multi-orbit HRSC DTMs. Additionally we make use of the existing bundle-adjusted HRSC single images available at the PDS archives. A prototype demonstrating the presented features is available at http://imars.planet.fu-berlin.de. Multi-temporal database: In order to locate multiple coverage of images and select images based on spatio-temporal queries, we converge available coverage catalogs for various NASA imaging missions into a relational database management system with geometry support. We harvest available metadata entries during our processing pipeline using the Integrated Software for Imagers and Spectrometers (ISIS) software. Currently, this database contains image outlines from the MGS/MOC, MRO/CTX and the MO/THEMIS instruments with imaging dates ranging from 1996 to the present. For the MEx/HRSC data, we already maintain a database which we automatically update with custom software based on the VICAR environment. Web Map Service with time support: The MapServer software is connected to the database and provides Web Map Services (WMS) with time support based on the START_TIME image attribute. It allows temporal WMS GetMap requests by setting additional TIME parameter values in the request. The values for the parameter represent an interval defined by its lower and upper bounds. As the WMS time standard only supports one time variable, only the start times of the images are considered. If no time values are submitted with the request, the full time range of all images is assumed as the default. Dynamic single image WMS: To compare images from different acquisition times at sites of multiple coverage, we have to load every image as a single WMS layer. Due to the vast amount of single images we need a way to set up the layers in a dynamic way - the map server does not know the images to be served beforehand. We use the MapScript interface to dynamically access MapServer's objects and configure the file name and path of the requested image in the map configuration. The layers are created on-the-fly each representing only one single image. On the frontend side, the vendor-specific WMS request parameter (PRODUCTID) has to be appended to the regular set of WMS parameters. The request is then passed on to the MapScript instance. Web Map Tile Cache: In order to speed up access of the WMS requests, a MapCache instance has been integrated in the pipeline. As it is not aware of the available PDS product IDs which will be queried, the PRODUCTID parameter is configured as an additional dimension of the cache. The WMS request is received by the Apache webserver configured with the MapCache module. If the tile is available in the tile cache, it is immediately commited to the client. If not available, the tile request is forwarded to Apache and the MapScript module. The Python script intercepts the WMS request and extracts the product ID from the parameter chain. It loads the layer object from the map file and appends the file name and path of the inquired image. After some possible further image processing inside the script (stretching, color matching), the request is submitted to the MapServer backend which in turn delivers the response back to the MapCache instance. Web frontend: We have implemented a web-GIS frontend based on various OpenLayers components. The basemap is a global color-hillshaded HRSC bundle-adjusted DTM mosaic with a resolution of 50 m per pixel. The new bundle-block-adjusted qudrangle mosaics of the MC-11 quadrangle, both image and DTM, are included with opacity slider options. The layer user interface has been adapted on the base of the ol3-layerswitcher and extended by foldable and switchable groups, layer sorting (by resolution, by time and alphabeticallly) and reordering (drag-and-drop). A collapsible time panel accomodates a time slider interface where the user can filter the visible data by a range of Mars or Earth dates and/or by solar longitudes. The visualisation of time-series of single images is controlled by a specific toolbar enabling the workflow of image selection (by point or bounding box), dynamic image loading and playback of single images in a video player-like environment. During a stress-test campaign we could demonstrate that the system is capable of serving up to 10 simultaneous users on its current lightweight development hardware. It is planned to relocate the software to more powerful hardware by the time of this conference. Conclusions/Outlook: The iMars webGIS is an expert tool for the detection and visualization of surface changes. We demonstrate a technique to dynamically retrieve and display single images based on the time-series structure of the data. Together with the multi-temporal database and its MapServer/MapCache backend it provides a stable and high performance environment for the dissemination of the various iMars products. Acknowledgements: This research has received funding from the EU's FP7 Programme under iMars 607379 and by the German Space Agency (DLR Bonn), grant 50 QM 1301 (HRSC on Mars Express).

Sliding window prior data assisted compressed sensing for MRI tracking of lung tumors.

PubMed

Yip, Eugene; Yun, Jihyun; Wachowicz, Keith; Gabos, Zsolt; Rathee, Satyapal; Fallone, B G

2017-01-01

Hybrid magnetic resonance imaging and radiation therapy devices are capable of imaging in real-time to track intrafractional lung tumor motion during radiotherapy. Highly accelerated magnetic resonance (MR) imaging methods can potentially reduce system delay time and/or improves imaging spatial resolution, and provide flexibility in imaging parameters. Prior Data Assisted Compressed Sensing (PDACS) has previously been proposed as an acceleration method that combines the advantages of 2D compressed sensing and the KEYHOLE view-sharing technique. However, as PDACS relies on prior data acquired at the beginning of a dynamic imaging sequence, decline in image quality occurs for longer duration scans due to drifts in MR signal. Novel sliding window-based techniques for refreshing prior data are proposed as a solution to this problem. MR acceleration is performed by retrospective removal of data from the fully sampled sets. Six patients with lung tumors are scanned with a clinical 3 T MRI using a balanced steady-state free precession (bSSFP) sequence for 3 min at approximately 4 frames per second, for a total of 650 dynamics. A series of distinct pseudo-random patterns of partial k-space acquisition is generated such that, when combined with other dynamics within a sliding window of 100 dynamics, covers the entire k-space. The prior data in the sliding window are continuously refreshed to reduce the impact of MR signal drifts. We intended to demonstrate two different ways to utilize the sliding window data: a simple averaging method and a navigator-based method. These two sliding window methods are quantitatively compared against the original PDACS method using three metrics: artifact power, centroid displacement error, and Dice's coefficient. The study is repeated with pseudo 0.5 T images by adding complex, normally distributed noise with a standard deviation that reduces image SNR, relative to original 3 T images, by a factor of 6. Without sliding window implemented, PDACS-reconstructed dynamic datasets showed progressive increases in image artifact power as the 3 min scan progresses. With sliding windows implemented, this increase in artifact power is eliminated. Near the end of a 3 min scan at 3 T SNR and 5× acceleration, implementation of an averaging (navigator) sliding window method improves our metrics by the following ways: artifact power decreases from 0.065 without sliding window to 0.030 (0.031), centroid error decreases from 2.64 to 1.41 mm (1.28 mm), and Dice coefficient agreement increases from 0.860 to 0.912 (0.915). At pseudo 0.5 T SNR, the improvements in metrics are as follows: artifact power decreases from 0.110 without sliding window to 0.0897 (0.0985), centroid error decreases from 2.92 mm to 1.36 mm (1.32 mm), and Dice coefficient agreements increases from 0.851 to 0.894 (0.896). In this work we demonstrated the negative impact of slow changes in MR signal for longer duration PDACS dynamic scans, namely increases in image artifact power and reductions of tumor tracking accuracy. We have also demonstrated sliding window implementations (i.e., refreshing of prior data) of PDACS are effective solutions to this problem at both 3 T and simulated 0.5 T bSSFP images. © 2016 American Association of Physicists in Medicine.

Application of State-Space Smoothing to fMRI Data for Calculation of Lagged Transinformation between Human Brain Activations

NASA Astrophysics Data System (ADS)

Watanabe, Jobu

2009-09-01

Mutual information can be given a directional sense by introducing a time lag in one of the variables. In an author's previous study, to investigate the network dynamics of human brain regions, lagged transinformation (LTI) was introduced using time delayed mutual information. The LTI makes it possible to quantify the time course of dynamic information transfer between regions in the temporal domain. The LTI was applied to functional magnetic resonance imaging (fMRI) data involved in neural processing of the transformation and comparison from three-dimensional (3D) visual information to a two-dimensional (2D) location to calculate directed information flows between the activated brain regions. In the present study, for more precise estimation of LTI, Kalman filter smoothing was applied to the same fMRI data. Because the smoothing method exploits the full length of the time series data for the estimation, its application increases the precision. Large information flows were found from the bilateral prefrontal cortices to the parietal cortices. The results suggest that information of the 3D images stored as working memory was retrieved and transferred from the prefrontal cortices to the parietal cortices for comparison with information of the 2D images.

Photocapacitive image converter

NASA Technical Reports Server (NTRS)

Miller, W. E.; Sher, A.; Tsuo, Y. H. (Inventor)

1982-01-01

An apparatus for converting a radiant energy image into corresponding electrical signals including an image converter is described. The image converter includes a substrate of semiconductor material, an insulating layer on the front surface of the substrate, and an electrical contact on the back surface of the substrate. A first series of parallel transparent conductive stripes is on the insulating layer with a processing circuit connected to each of the conductive stripes for detecting the modulated voltages generated thereon. In a first embodiment of the invention, a modulated light stripe perpendicular to the conductive stripes scans the image converter. In a second embodiment a second insulating layer is deposited over the conductive stripes and a second series of parallel transparent conductive stripes perpendicular to the first series is on the second insulating layer. A different frequency current signal is applied to each of the second series of conductive stripes and a modulated image is applied to the image converter.

Dynamics modeling for sugar cane sucrose estimation using time series satellite imagery

NASA Astrophysics Data System (ADS)

Zhao, Yu; Justina, Diego Della; Kazama, Yoriko; Rocha, Jansle Vieira; Graziano, Paulo Sergio; Lamparelli, Rubens Augusto Camargo

2016-10-01

Sugarcane, as one of the most mainstay crop in Brazil, plays an essential role in ethanol production. To monitor sugarcane crop growth and predict sugarcane sucrose content, remote sensing technology plays an essential role while accurate and timely crop growth information is significant, in particularly for large scale farming. We focused on the issues of sugarcane sucrose content estimation using time-series satellite image. Firstly, we calculated the spectral features and vegetation indices to make them be correspondence to the sucrose accumulation biological mechanism. Secondly, we improved the statistical regression model considering more other factors. The evaluation was performed and we got precision of 90% which is about 20% higher than the conventional method. The validation results showed that prediction accuracy using our sugarcane growth modeling and improved mix model is satisfied.

A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction

PubMed Central

Lehman, Li-Wei H.; Adams, Ryan P.; Mayaud, Louis; Moody, George B.; Malhotra, Atul; Mark, Roger G.; Nemati, Shamim

2015-01-01

Cardiovascular variables such as heart rate (HR) and blood pressure (BP) are regulated by an underlying control system, and therefore, the time series of these vital signs exhibit rich dynamical patterns of interaction in response to external perturbations (e.g., drug administration), as well as pathological states (e.g., onset of sepsis and hypotension). A question of interest is whether “similar” dynamical patterns can be identified across a heterogeneous patient cohort, and be used for prognosis of patients’ health and progress. In this paper, we used a switching vector autoregressive framework to systematically learn and identify a collection of vital sign time series dynamics, which are possibly recurrent within the same patient and may be shared across the entire cohort. We show that these dynamical behaviors can be used to characterize the physiological “state” of a patient. We validate our technique using simulated time series of the cardiovascular system, and human recordings of HR and BP time series from an orthostatic stress study with known postural states. Using the HR and BP dynamics of an intensive care unit (ICU) cohort of over 450 patients from the MIMIC II database, we demonstrate that the discovered cardiovascular dynamics are significantly associated with hospital mortality (dynamic modes 3 and 9, p = 0.001, p = 0.006 from logistic regression after adjusting for the APACHE scores). Combining the dynamics of BP time series and SAPS-I or APACHE-III provided a more accurate assessment of patient survival/mortality in the hospital than using SAPS-I and APACHE-III alone (p = 0.005 and p = 0.045). Our results suggest that the discovered dynamics of vital sign time series may contain additional prognostic value beyond that of the baseline acuity measures, and can potentially be used as an independent predictor of outcomes in the ICU. PMID:25014976

Nonequilibrium dynamic phases in driven vortex lattices with periodic pinning

NASA Astrophysics Data System (ADS)

Reichhardt, Charles Michael

1998-12-01

We present the results of an extensive series of simulations of flux-gradient and current driven vortices interacting with either random or periodically arranged pinning sites. First, we consider flux-gradient-driven simulations of superconducting vortices interacting with strong randomly-distributed columnar pinning defects, as an external field H(t) is quasi-statically swept from zero through a matching field Bsb{phi}. Here, we find significant changes in the behavior of the local flux density B(x, y, H(t)), magnetization M(H(t)), critical current Jsb{c}(B(t)), and the individual vortex flow paths, as the local flux density crosses Bsb{phi}. Further, we find that for a given pin density, Jsb{c}(B) can be enhanced by maximizing the distance between the pins for B < Bsb{phi}. For the case of periodic pinning sites as a function of applied field, we find a rich variety of ordered and partially-ordered vortex lattice configurations. We present formulas that predict the matching fields at which commensurate vortex configurations occur and the vortex lattice orientation with respect to the pinning lattice. Our results are in excellent agreement with recent imaging experiments on square pinning arrays (K. Harada et al., Science 274, 1167 (1996)). For current driven simulations with periodic pinning we find a remarkable number of dynamical plastic flow phases. Signatures of the transitions between these different dynamical phases include sudden jumps in the current-voltage curves, hysteresis, as well as marked changes in the vortex trajectories and vortex lattice order. These phases are outlined in a series of dynamic phase diagrams. We show that several of these phases and their phase-boundaries can be understood in terms of analytical arguments. Finally, when the vortex lattice is driven at varying angles with respect to the underlying periodic pinning array, the transverse voltage-current V(I) curves show a series of mode-locked plateaus with the overall V(I) forming a devil's staircase structure.

The dynamics of magma ascent in the crust: Characterising fluid flow and host-rock deformation using scaled analogue experiments

NASA Astrophysics Data System (ADS)

Kavanagh, Janine; Dennis, David

2015-04-01

We present the results from a series of analogue experiments that use gelatine injected by water to study magma ascent dynamics in the crust. Gelatine is a viscoelastic material that displays predominantly elastic deformation when used at low temperatures (5-10 °C) and mid-to-low concentrations (2-5 wt%). To study dyke propagation we have used a combination of Particle Image Velocimentry (PIV) and Digital Image Correlation (DIC) to characterise the dynamics of fluid flow within the intrusion and contemporaneous deformation of the host gelatine. Experiments are prepared by filling a 40 cm x 40 cm x 30 cm clear-Perspex tank with a gelatine mixture that has been seeded with neutrally buoyant fluorescent particles. Water, also seeded with tracer particles, is then injected into the solid gelatine from below under a constant flux or constant head pressure. This causes a vertical penny-shaped crack (dyke) to propagate through the gelatine and erupt at the surface. During the experiment, a vertical high-power laser sheet positioned along the centre of the tank is triggered to illuminate the seeding particles with short intense pulses, and two Dantec CCD cameras record successive images. Using PIV and DIC, vector fields of fluid flow within the intrusion and strain within the gelatine host is calculated by cross-correlation between successive images at a defined time interval. The experiments indicate that, prior to eruption, dyke propagation is characterised by rapid centralised and upwards fluid flow with accompanying downwards motion at the intrusion margin. Deformation of the gelatine solid is focused at a small head region, with the tail remaining relatively static as the dyke grows. Upon eruption, rapid centralised fluid evacuation occurs with contemporaneous contraction of the dyke and relaxation of the host gelatine. Models that can couple fluid dynamics and host deformation during magma ascent and eruption will make an important step towards improving our understanding of the dynamics of magma transport through the crust, and may help to constrain the tendency for eruption.

Modeling apple surface temperature dynamics based on weather data.

PubMed

Li, Lei; Peters, Troy; Zhang, Qin; Zhang, Jingjin; Huang, Danfeng

2014-10-27

The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST) dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed) was recorded for seven hours between 11:00-18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of "Fuji" apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

Modeling Apple Surface Temperature Dynamics Based on Weather Data

PubMed Central

Li, Lei; Peters, Troy; Zhang, Qin; Zhang, Jingjin; Huang, Danfeng

2014-01-01

The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST) dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed) was recorded for seven hours between 11:00–18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of “Fuji” apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management. PMID:25350507

Effects of Telecoupling on Global Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Viña, A.; Liu, J.

2016-12-01

With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

Regenerating time series from ordinal networks.

PubMed

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Regenerating time series from ordinal networks

NASA Astrophysics Data System (ADS)

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Comet ISON Seen Coming and Going

NASA Image and Video Library

2013-11-30

"Timelapse" series of images of comet ISON as viewed by ESA/NASA's Solar and Heliospheric Observatory, or SOHO. This image is a composite, with the sun imaged by NASA's Solar Dynamics Observatory in the center, and SOHO's two coronagraphs showing the solar atmosphere, the corona. The most recent image in this is from 5:30 p.m. EST on Nov. 29, 2013. Continuing a history of surprising behavior, material from Comet ISON appeared on the other side of the sun on the evening on Nov. 28, 2013, despite not having been seen in observations during its closest approach to the sun. The question remains whether it is merely debris from the comet, or if some portion of the comet's nucleus survived, but late-night analysis from scientists with NASA's Comet ISON Observing Campaign suggest that there is at least a small nucleus intact. Image Credit:ESA&NASA/SOHO/SDO NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

The infinitesimal operator for the semigroup of the Frobenius-Perron operator from image sequence data: vector fields and transport barriers from movies.

PubMed

Santitissadeekorn, N; Bollt, E M

2007-06-01

In this paper, we present an approach to approximate the Frobenius-Perron transfer operator from a sequence of time-ordered images, that is, a movie dataset. Unlike time-series data, successive images do not provide a direct access to a trajectory of a point in a phase space; more precisely, a pixel in an image plane. Therefore, we reconstruct the velocity field from image sequences based on the infinitesimal generator of the Frobenius-Perron operator. Moreover, we relate this problem to the well-known optical flow problem from the computer vision community and we validate the continuity equation derived from the infinitesimal operator as a constraint equation for the optical flow problem. Once the vector field and then a discrete transfer operator are found, then, in addition, we present a graph modularity method as a tool to discover basin structure in the phase space. Together with a tool to reconstruct a velocity field, this graph-based partition method provides us with a way to study transport behavior and other ergodic properties of measurable dynamical systems captured only through image sequences.

Quantitative assessment of dynamic PET imaging data in cancer imaging.

PubMed

Muzi, Mark; O'Sullivan, Finbarr; Mankoff, David A; Doot, Robert K; Pierce, Larry A; Kurland, Brenda F; Linden, Hannah M; Kinahan, Paul E

2012-11-01

Clinical imaging in positron emission tomography (PET) is often performed using single-time-point estimates of tracer uptake or static imaging that provides a spatial map of regional tracer concentration. However, dynamic tracer imaging can provide considerably more information about in vivo biology by delineating both the temporal and spatial pattern of tracer uptake. In addition, several potential sources of error that occur in static imaging can be mitigated. This review focuses on the application of dynamic PET imaging to measuring regional cancer biologic features and especially in using dynamic PET imaging for quantitative therapeutic response monitoring for cancer clinical trials. Dynamic PET imaging output parameters, particularly transport (flow) and overall metabolic rate, have provided imaging end points for clinical trials at single-center institutions for years. However, dynamic imaging poses many challenges for multicenter clinical trial implementations from cross-center calibration to the inadequacy of a common informatics infrastructure. Underlying principles and methodology of PET dynamic imaging are first reviewed, followed by an examination of current approaches to dynamic PET image analysis with a specific case example of dynamic fluorothymidine imaging to illustrate the approach. Copyright © 2012 Elsevier Inc. All rights reserved.

Long-term monitoring of glacier dynamics of Fleming Glacier after the disintegration of Wordie Ice Shelf, Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Friedl, Peter; Seehaus, Thorsten; Wendt, Anja; Braun, Matthias

2017-04-01

The Antarctic Peninsula is one of the world`s most affected regions by Climate Change. Dense and long time series of remote sensing data enable detailed studies of the rapid glaciological changes in this area. We present results of a study on Fleming Glacier, which was the major tributary glacier of former Wordie Ice Shelf, located at the south-western side of the Antarctic Peninsula. Since the ice shelf disintegrated in a series of events starting in the 1970s, only disconnected tidewater glaciers have remained today. As a reaction to the loss of the buttressing force of the ice shelf, Fleming Glacier accelerated and dynamically thinned. However, all previous studies conducted at Wordie Bay covered only relatively short investigation periods and ended in 2008 the latest. Hence it was not well known how long the process of adaption to the changing boundary conditions exactly lasts and how it is characterized in detail. We provide long time series (1994 - 2016) of glaciological parameters (i.e. ice extent, velocity, grounding line position, ice elevation) for Fleming Glacier obtained from multi-mission remote sensing data. For this purpose large datasets of previously active (e.g. ERS, Envisat, ALOS PALSAR, Radarsat-1) as well as currently recording SAR sensors (e.g. Sentinel-1, TerraSAR-X, TanDEM-X) were processed and combined with data from other sources (e.g. optical images, laser altimeter and ice thickness data). The high temporal resolution of our dataset enables us to present a detailed history of 22 years of glacial dynamics at Fleming Glacier after the disintegration of Wordie Ice Shelf. We found strong evidence for a rapid grounding line retreat of up to 13 km between 2008 and 2011, which led to a further amplification of dynamic ice thinning. Today Fleming Glacier seems to be far away from approaching a new equilibrium. Our data show that the current glacier dynamics of Fleming Glacier are not primarily controlled by the loss of the ice shelf anymore, but by other sources of external forcing, such as oceanic warming.

The Compressive Behavior of Isocyanate-crosslinked Silica Aerogel at High Strain Rates

NASA Technical Reports Server (NTRS)

Luo, H.; Lu, H.; Leventis, N.

2006-01-01

Aerogels are low-density, highly nano-porous materials. Their engineering applications are limited due to their brittleness and hydrophilicity. Recently, a strong lightweight crosslinked silica aerogel has been developed by encapsulating the skeletal framework of amine-modified silica aerogels with polyureas derived by isocyanate. The mesoporous structure of the underlying silica framework is preserved through conformal polymer coating, and the thermal conductivity remains low. Characterization has been conducted on the thermal, physical properties and the mechanical properties under quasi-static loading conditions. In this paper, we present results on the dynamic compressive behavior of the crosslinked silica aerogel (CSA) using a split Hopkinson pressure bar (SHPB). A new tubing pulse shaper was employed to help reach the dynamic stress equilibrium and constant strain rate. The stress-strain relationship was determined at high strain rates within 114-4386/s. The effects of strain rate, density, specimen thickness and water absorption on the dynamic behavior of the CSA were investigated through a series of dynamic experiments. The Young's moduli (or 0.2% offset compressive yield strengths) at a strain rate approx.350/s were determined as 10.96/2.08, 159.5/6.75, 192.2/7.68, 304.6/11.46, 407.0/20.91 and 640.5/30.47 MPa for CSA with densities 0.205, 0.454, 0.492, 0.551,0.628 and 0.731 g/cu cm, respectively. The deformation and failure behaviors of a native silica aerogel with density (0.472 g/cu cm ), approximately the same as a typical CSA sample were observed with a high speed digital camera. Digital image correlation technique was used to determine the surface strains through a series of images acquired using high speed photography. The relative uniform axial deformation indicated that localized compaction did not occur at a compressive strain level of approx.17%, suggesting most likely failure mechanism at high strain rate to be different from that under quasi-static loading condition. The Poisson s ratio was determined to be 0.162 in nonlinear regime under high strain rates. CSA samples failed generally by splitting, but were much more ductile than native silica aerogels.

Flare Prediction Using Photospheric and Coronal Image Data

NASA Astrophysics Data System (ADS)

Jonas, E.; Shankar, V.; Bobra, M.; Recht, B.

2016-12-01

We attempt to forecast M-and X-class solar flares using a machine-learning algorithm and five years of image data from both the Helioseismic and Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) instruments aboard the Solar Dynamics Observatory. HMI is the first instrument to continuously map the full-disk photospheric vector magnetic field from space (Schou et al., 2012). The AIA instrument maps the transition region and corona using various ultraviolet wavelengths (Lemen et al., 2012). HMI and AIA data are taken nearly simultaneously, providing an opportunity to study the entire solar atmosphere at a rapid cadence. Most flare forecasting efforts described in the literature use some parameterization of solar data - typically of the photospheric magnetic field within active regions. These numbers are considered to capture the information in any given image relevant to predicting solar flares. In our approach, we use HMI and AIA images of solar active regions and a deep convolutional kernel network to predict solar flares. This is effectively a series of shallow-but-wide random convolutional neural networks stacked and then trained with a large-scale block-weighted least squares solver. This algorithm automatically determines which patterns in the image data are most correlated with flaring activity and then uses these patterns to predict solar flares. Using the recently-developed KeystoneML machine learning framework, we construct a pipeline to process millions of images in a few hours on commodity cloud computing infrastructure. This is the first time vector magnetic field images have been combined with coronal imagery to forecast solar flares. This is also the first time such a large dataset of solar images, some 8.5 terabytes of images that together capture over 3000 active regions, has been used to forecast solar flares. We evaluate our method using various flare prediction windows defined in the literature (e.g. Ahmed et al., 2013) and a novel per-hour time series we've constructed which more closely mimics the demands of an operational solar flare prediction system. We estimate the performance of our algorithm using the True Skill Statistic (TSS; Bloomfield et al., 2012). We find that our algorithm gives a high TSS score and predictive abilities.

Nonlinear dynamic analysis of D α signals for type I edge localized modes characterization on JET with a carbon wall

NASA Astrophysics Data System (ADS)

Cannas, Barbara; Fanni, Alessandra; Murari, Andrea; Pisano, Fabio; Contributors, JET

2018-02-01

In this paper, the dynamic characteristics of type-I ELM time-series from the JET tokamak, the world’s largest magnetic confinement plasma physics experiment, have been investigated. The dynamic analysis has been focused on the detection of nonlinear structure in D α radiation time series. Firstly, the method of surrogate data has been applied to evaluate the statistical significance of the null hypothesis of static nonlinear distortion of an underlying Gaussian linear process. Several nonlinear statistics have been evaluated, such us the time delayed mutual information, the correlation dimension and the maximal Lyapunov exponent. The obtained results allow us to reject the null hypothesis, giving evidence of underlying nonlinear dynamics. Moreover, no evidence of low-dimensional chaos has been found; indeed, the analysed time series are better characterized by the power law sensitivity to initial conditions which can suggest a motion at the ‘edge of chaos’, at the border between chaotic and regular non-chaotic dynamics. This uncertainty makes it necessary to further investigate about the nature of the nonlinear dynamics. For this purpose, a second surrogate test to distinguish chaotic orbits from pseudo-periodic orbits has been applied. In this case, we cannot reject the null hypothesis which means that the ELM time series is possibly pseudo-periodic. In order to reproduce pseudo-periodic dynamical properties, a periodic state-of-the-art model, proposed to reproduce the ELM cycle, has been corrupted by a dynamical noise, obtaining time series qualitatively in agreement with experimental time series.

Fluctuation of similarity (FLUS) to detect transitions between distinct dynamical regimes in short time series

PubMed Central

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2016-01-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [1], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In the present work, we describe the details of the analytical relationships between this newly introduced measure and the well known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method’s robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the U.S. crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980’s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980’s and early 1990’s, leading to increase in the dynamical complexity of these rates. PMID:25019852

BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems.

PubMed

Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M

2017-11-25

Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays.

A Nonlinear Dynamical Systems based Model for Stochastic Simulation of Streamflow

NASA Astrophysics Data System (ADS)

Erkyihun, S. T.; Rajagopalan, B.; Zagona, E. A.

2014-12-01

Traditional time series methods model the evolution of the underlying process as a linear or nonlinear function of the autocorrelation. These methods capture the distributional statistics but are incapable of providing insights into the dynamics of the process, the potential regimes, and predictability. This work develops a nonlinear dynamical model for stochastic simulation of streamflows. In this, first a wavelet spectral analysis is employed on the flow series to isolate dominant orthogonal quasi periodic timeseries components. The periodic bands are added denoting the 'signal' component of the time series and the residual being the 'noise' component. Next, the underlying nonlinear dynamics of this combined band time series is recovered. For this the univariate time series is embedded in a d-dimensional space with an appropriate lag T to recover the state space in which the dynamics unfolds. Predictability is assessed by quantifying the divergence of trajectories in the state space with time, as Lyapunov exponents. The nonlinear dynamics in conjunction with a K-nearest neighbor time resampling is used to simulate the combined band, to which the noise component is added to simulate the timeseries. We demonstrate this method by applying it to the data at Lees Ferry that comprises of both the paleo reconstructed and naturalized historic annual flow spanning 1490-2010. We identify interesting dynamics of the signal in the flow series and epochal behavior of predictability. These will be of immense use for water resources planning and management.

Variations in annual water-energy balance and their correlations with vegetation and soil moisture dynamics: A case study in the Wei River Basin, China

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

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong

It is of importance to investigate watershed water-energy balance variations and to explore their correlations with vegetation and soil moisture dynamics, which helps better understand the interplays between underlying surface dynamics and the terrestrial water cycle. The heuristic segmentation method was adopted to identify change points in the parameter to series in Fu's equation belonging to the Budyko framework in the Wei River Basin (WRB) and its sub-basins aiming to examine the validity of stationary assumptions. Additionally, the cross wavelet analysis was applied to explore the correlations between vegetation and soil moisture dynamics and to variations. Results indicated that (1)more » the omega variations in the WRB are significant, with some change points identified except for the sub-basin above Zhangjiashan, implying that the stationarity of omega series in the WRB is invalid except for the sub-basin above Zhangjiashan; (2) the correlations between soil moisture series and to series are weaker than those between Normalized Difference Vegetation Index (NDVI) series and omega series; (3) vegetation dynamics show significantly negative correlations with omega variations in 1983-2003 with a 4-8 year signal in the whole WRB, and both vegetation and soil moisture dynamics exert strong impacts on the parameter omega changes. This study helps understanding the interactions between underlying land surface dynamics and watershed water-energy balance. (C) 2017 Elsevier B.V. All rights reserved.« less

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. PMID:25534671

Feasibility of quantitative regional ventilation and perfusion mapping with phase-resolved functional lung (PREFUL) MRI in healthy volunteers and COPD, CTEPH, and CF patients.

PubMed

Voskrebenzev, Andreas; Gutberlet, Marcel; Klimeš, Filip; Kaireit, Till F; Schönfeld, Christian; Rotärmel, Alexander; Wacker, Frank; Vogel-Claussen, Jens

2018-04-01

In this feasibility study, a phase-resolved functional lung imaging postprocessing method for extraction of dynamic perfusion (Q) and ventilation (V) parameters using a conventional 1H lung MRI Fourier decomposition acquisition is introduced. Time series of coronal gradient-echo MR images with a temporal resolution of 288 to 324 ms of two healthy volunteers, one patient with chronic thromboembolic hypertension, one patient with cystic fibrosis, and one patient with chronic obstructive pulmonary disease were acquired at 1.5 T. Using a sine model to estimate cardiac and respiratory phases of each image, all images were sorted to reconstruct full cardiac and respiratory cycles. Time to peak (TTP), V/Q maps, and fractional ventilation flow-volume loops were calculated. For the volunteers, homogenous ventilation and perfusion TTP maps (V-TTP, Q-TTP) were obtained. The chronic thromboembolic hypertension patient showed increased perfusion TTP in hypoperfused regions in visual agreement with dynamic contrast-enhanced MRI, which improved postpulmonary endaterectomy surgery. Cystic fibrosis and chronic obstructive pulmonary disease patients showed a pattern of increased V-TTP and Q-TTP in regions of hypoventilation and decreased perfusion. Fractional ventilation flow-volume loops of the chronic obstructive pulmonary disease patient were smaller in comparison with the healthy volunteer, and showed regional differences in visual agreement with functional small airways disease and emphysema on CT. This study shows the feasibility of phase-resolved functional lung imaging to gain quantitative information regarding regional lung perfusion and ventilation without the need for ultrafast imaging, which will be advantageous for future clinical translation. Magn Reson Med 79:2306-2314, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Optimization of Rb-82 PET acquisition and reconstruction protocols for myocardial perfusion defect detection

NASA Astrophysics Data System (ADS)

Tang, Jing; Rahmim, Arman; Lautamäki, Riikka; Lodge, Martin A.; Bengel, Frank M.; Tsui, Benjamin M. W.

2009-05-01

The purpose of this study is to optimize the dynamic Rb-82 cardiac PET acquisition and reconstruction protocols for maximum myocardial perfusion defect detection using realistic simulation data and task-based evaluation. Time activity curves (TACs) of different organs under both rest and stress conditions were extracted from dynamic Rb-82 PET images of five normal patients. Combined SimSET-GATE Monte Carlo simulation was used to generate nearly noise-free cardiac PET data from a time series of 3D NCAT phantoms with organ activities modeling different pre-scan delay times (PDTs) and total acquisition times (TATs). Poisson noise was added to the nearly noise-free projections and the OS-EM algorithm was applied to generate noisy reconstructed images. The channelized Hotelling observer (CHO) with 32× 32 spatial templates corresponding to four octave-wide frequency channels was used to evaluate the images. The area under the ROC curve (AUC) was calculated from the CHO rating data as an index for image quality in terms of myocardial perfusion defect detection. The 0.5 cycle cm-1 Butterworth post-filtering on OS-EM (with 21 subsets) reconstructed images generates the highest AUC values while those from iteration numbers 1 to 4 do not show different AUC values. The optimized PDTs for both rest and stress conditions are found to be close to the cross points of the left ventricular chamber and myocardium TACs, which may promote an individualized PDT for patient data processing and image reconstruction. Shortening the TATs for <~3 min from the clinically employed acquisition time does not affect the myocardial perfusion defect detection significantly for both rest and stress studies.

CHANGES IN THE CRAB PULSAR

NASA Technical Reports Server (NTRS)

2002-01-01

Scientists are learning more about how pulsars work by studying a series of Hubble Space Telescope images of the heart of the Crab Nebula. The images, taken over a period of several months, show that the Crab is a far more dynamic object than previously understood. At the center of the nebula lies the Crab Pulsar. The pulsar is a tiny object by astronomical standards -- only about six miles across -- but has a mass greater than that of the Sun and rotates at a rate of 30 times a second. As the pulsar spins its intense magnetic field whips around, acting like a sling shot, accelerating subatomic particles and sending them hurtling them into space at close to the speed of light. The tiny pulsar and its wind are the powerhouse for the entire Crab Nebula, which is 10 light-years across -- a feat comparable to an object the size of a hydrogen atom illuminating a volume of space a kilometer across. The three pictures shown here, taken from the series of Hubble images, show dramatic changes in the appearance of the central regions of the nebula. These include wisp-like structures that move outward away from the pulsar at half the speed of light, as well as a mysterious 'halo' which remains stationary, but grows brighter then fainter over time. Also seen are the effects of two polar jets that move out along the rotation axis of the pulsar. The most dynamic feature seen -- a small knot that 'dances around' so much that astronomers have been calling it a 'sprite' -- is actually a shock front (where fast-moving material runs into slower-moving material)in one of these polar jets. The telescope captured the images with the Wide Field and Planetary Camera 2 using a filter that passes light of wavelength around 550 nanometers, near the middle of the visible part of the spectrum. The Crab Nebula is located 7,000 light-years away in the constellation Taurus. Credit: Jeff Hester and Paul Scowen (Arizona State University), and NASA

Solar Scientist Confirm Existence of Flux Ropes on the Sun

NASA Image and Video Library

2013-02-14

Caption: This is an image of magnetic loops on the sun, captured by NASA's Solar Dynamics Observatory (SDO). It has been processed to highlight the edges of each loop to make the structure more clear. A series of loops such as this is known as a flux rope, and these lie at the heart of eruptions on the sun known as coronal mass ejections (CMEs.) This is the first time scientists were able to discern the timing of a flux rope's formation. (SDO AIA 131 and 171 difference blended image of flux ropes during CME.) Credit: NASA/Goddard Space Flight Center/SDO ---- On July 18, 2012, a fairly small explosion of light burst off the lower right limb of the sun. Such flares often come with an associated eruption of solar material, known as a coronal mass ejection or CME – but this one did not. Something interesting did happen, however. Magnetic field lines in this area of the sun's atmosphere, the corona, began to twist and kink, generating the hottest solar material – a charged gas called plasma – to trace out the newly-formed slinky shape. The plasma glowed brightly in extreme ultraviolet images from the Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory (SDO) and scientists were able to watch for the first time the very formation of something they had long theorized was at the heart of many eruptive events on the sun: a flux rope. Eight hours later, on July 19, the same region flared again. This time the flux rope's connection to the sun was severed, and the magnetic fields escaped into space, dragging billions of tons of solar material along for the ride -- a classic CME. "Seeing this structure was amazing," says Angelos Vourlidas, a solar scientist at the Naval Research Laboratory in Washington, D.C. "It looks exactly like the cartoon sketches theorists have been drawing of flux ropes since the 1970s. It was a series of figure eights lined up to look like a giant slinky on the sun." To read more about this new discovery go to: 1.usa.gov/14UHsTt

Solar Scientist Confirm Existence of Flux Ropes on the Sun

NASA Image and Video Library

2017-12-08

Caption: This is an image of magnetic loops on the sun, captured by NASA's Solar Dynamics Observatory (SDO). It has been processed to highlight the edges of each loop to make the structure more clear. A series of loops such as this is known as a flux rope, and these lie at the heart of eruptions on the sun known as coronal mass ejections (CMEs.) This is the first time scientists were able to discern the timing of a flux rope's formation. (SDO AIA 131 and 171 difference blended image of flux ropes during CME.) Credit: NASA/Goddard Space Flight Center/SDO ---- On July 18, 2012, a fairly small explosion of light burst off the lower right limb of the sun. Such flares often come with an associated eruption of solar material, known as a coronal mass ejection or CME – but this one did not. Something interesting did happen, however. Magnetic field lines in this area of the sun's atmosphere, the corona, began to twist and kink, generating the hottest solar material – a charged gas called plasma – to trace out the newly-formed slinky shape. The plasma glowed brightly in extreme ultraviolet images from the Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory (SDO) and scientists were able to watch for the first time the very formation of something they had long theorized was at the heart of many eruptive events on the sun: a flux rope. Eight hours later, on July 19, the same region flared again. This time the flux rope's connection to the sun was severed, and the magnetic fields escaped into space, dragging billions of tons of solar material along for the ride -- a classic CME. "Seeing this structure was amazing," says Angelos Vourlidas, a solar scientist at the Naval Research Laboratory in Washington, D.C. "It looks exactly like the cartoon sketches theorists have been drawing of flux ropes since the 1970s. It was a series of figure eights lined up to look like a giant slinky on the sun." To read more about this new discovery go to: 1.usa.gov/14UHsTt

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery

NASA Astrophysics Data System (ADS)

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms (R2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms ( R 2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Dynamic contrast-enhanced breast MR imaging in men: preliminary results.

PubMed

Morakkabati-Spitz, Nuschin; Schild, Hans H; Leutner, Claudia C; von Falkenhausen, Marcus; Lutterbey, Götz; Kuhl, Christiane K

2006-02-01

To prospectively evaluate whether the descriptors of lesion features and the diagnostic criteria that have been established for breast magnetic resonance (MR) imaging in female patients may be used for differential diagnosis with breast MR imaging in male patients as well. The study design was approved by the institutional review board; all patients gave informed consent. The Institutional Review Board and informed consent information applied to the prospective and any retrospective component of the study. Seventeen consecutive male patients (mean age, 53 years +/- 14) were referred for imaging of a palpable breast mass. In addition to mammography and high-frequency breast ultrasonography, patients underwent dynamic breast MR imaging in a prone position with a dedicated double-breast surface coil. The standardized protocol consisted of a T2-weighted turbo spin-echo sequence followed by a dynamic series. Findings were recorded by using the terminology and descriptors and by evaluating the diagnostic criteria (related to morphology and enhancement kinetics) that have been developed for breast MR imaging in female patients. Validation was achieved at biopsy (nine patients) or follow-up with clinical examination and conventional imaging (eight patients). Because of the small size of the patient cohort, statistical significance was not tested. A total of 24 breast abnormalities were diagnosed. Three patients had invasive breast cancer (five tumors), 11 had gynecomastia (six unilateral, five bilateral), two had pseudogynecomastia, and one had a benign solid tumor (angiolipoma). All malignant tumors appeared as irregular masses with heterogeneous internal architecture or rim enhancement and showed rapid initial enhancement (mean value, 137% +/- 23) followed by a washout time course (Breast Imaging Reporting and Data System [BI-RADS] category 5). Diffuse and nodular gynecomastia showed slow initial and persistent enhancement with normal-appearing parenchymal architecture (BI-RADS category 2; 15 of 16 breasts in 10 of 11 patients). In one patient with biopsy-proved bilateral gynecomastia, an area with segmental enhancement was classified as suspicious for ductal carcinoma in situ. Pseudogynecomastia did not enhance at all. The angiolipoma showed benign morphologic features and slow initial and persistent enhancement (BI-RADS category 2). In the small study cohort, the MR imaging features of benign breast diseases and breast cancers in male patients seemed to be comparable to those seen in female patients. (c) RSNA, 2005

The number comb for a soil physical properties dynamic measurement

NASA Astrophysics Data System (ADS)

Olechko, K.; Patiño, P.; Tarquis, A. M.

2012-04-01

We propose the prime numbers distribution extracted from the soil digital multiscale images and some physical properties time series as the precise indicator of the spatial and temporal dynamics under soil management changes. With this new indicator the soil dynamics can be studied as a critical phenomenon where each phase transition is estimated and modeled by the graph partitioning induced phase transition. The critical point of prime numbers distribution was correlated with the beginning of Andosols, Vertisols and saline soils physical degradation under the unsustainable soil management in Michoacan, Guanajuato and Veracruz States of Mexico. The data banks corresponding to the long time periods (between 10 and 28 years) were statistically compared by RISK 5.0 software and our own algorithms. Our approach makes us able to distill free-form natural laws of soils physical properties dynamics directly from the experimental data. The Richter (1987) and Schmidt and Lipson (2009) original approaches were very useful to design the algorithms to identify Hamiltonians, Lagrangians and other laws of geometric and momentum conservation especially for erosion case.

Life-histories from Landsat: Algorithmic approaches to distilling Earth's recent ecological dynamics

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Yang, Z.; Braaten, J.; Cohen, W. B.; Ohmann, J.; Gregory, M.; Roberts, H.; Meigs, G. W.; Nelson, P.; Pfaff, E.

2012-12-01

As the longest running continuous satellite Earth-observation record, data from the Landsat family of sensors have the potential to uniquely reveal temporal dynamics critical to many terrestrial disciplines. The convergence of a free-data access policy in the late 2000s with a rapid rise in computing and storage capacity has highlighted an increasinagly common challenge: effective distillation of information from large digital datasets. Here, we describe how an algorithmic workflow informed by basic understanding of ecological processes is being used to convert multi-terabyte image time-series datasets into concise renditions of landscape dynamics. Using examples from our own work, we show how these are in turn applied to monitor vegetative disturbance and growth dynamics in national parks, to evaluate effectiveness of natural resource policy in national forests, to constrain and inform biogeochemical models, to measure carbon impacts of natural and anthropogenic stressors, to assess impacts of land use change on threatened species, to educate and inform students, and to better characterize complex links between changing climate, insect pathogens, and wildfire in forests.

Spherical Harmonic Inductive Detection Coils and their use In Dynamic Pre-emphasis for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Edler, Karl T.

The issue of eddy currents induced by the rapid switching of magnetic field gradients is a long-standing problem in magnetic resonance imaging. A new method for dealing with this problem is presented whereby spatial harmonic components of the magnetic field are continuously sensed, through their temporal rates of change, and corrected. In this way, the effects of the eddy currents on multiple spatial harmonic components of the magnetic field can be detected and corrections applied during the rise time of the gradients. Sensing the temporal changes in each spatial harmonic is made possible with specially designed detection coils. However to make the design of these coils possible, general relationships between the spatial harmonics of the field, scalar potential, and vector potential are found within the quasi-static approximation. These relationships allow the vector potential to be found from the field -- an inverse curl operation -- and may be of use beyond the specific problem of detection coil design. Using the detection coils as sensors, methods are developed for designing a negative feedback system to control the eddy current effects and optimizing that system with respect to image noise and distortion. The design methods are successfully tested in a series of proof-of-principle experiments which lead to a discussion of how to incorporate similar designs into an operational MRI. Keywords: magnetic resonance imaging, eddy currents, dynamic shimming, negative feedback, quasi-static fields, vector potential, inverse curl

Quantitative fluorescence microscopy and image deconvolution.

PubMed

Swedlow, Jason R

2013-01-01

Quantitative imaging and image deconvolution have become standard techniques for the modern cell biologist because they can form the basis of an increasing number of assays for molecular function in a cellular context. There are two major types of deconvolution approaches--deblurring and restoration algorithms. Deblurring algorithms remove blur but treat a series of optical sections as individual two-dimensional entities and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed in this chapter. Image deconvolution in fluorescence microscopy has usually been applied to high-resolution imaging to improve contrast and thus detect small, dim objects that might otherwise be obscured. Their proper use demands some consideration of the imaging hardware, the acquisition process, fundamental aspects of photon detection, and image processing. This can prove daunting for some cell biologists, but the power of these techniques has been proven many times in the works cited in the chapter and elsewhere. Their usage is now well defined, so they can be incorporated into the capabilities of most laboratories. A major application of fluorescence microscopy is the quantitative measurement of the localization, dynamics, and interactions of cellular factors. The introduction of green fluorescent protein and its spectral variants has led to a significant increase in the use of fluorescence microscopy as a quantitative assay system. For quantitative imaging assays, it is critical to consider the nature of the image-acquisition system and to validate its response to known standards. Any image-processing algorithms used before quantitative analysis should preserve the relative signal levels in different parts of the image. A very common image-processing algorithm, image deconvolution, is used to remove blurred signal from an image. There are two major types of deconvolution approaches, deblurring and restoration algorithms. Deblurring algorithms remove blur, but treat a series of optical sections as individual two-dimensional entities, and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed. Copyright © 1998 Elsevier Inc. All rights reserved.

Classification of time-series images using deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Hatami, Nima; Gavet, Yann; Debayle, Johan

2018-04-01

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.

Advancing Access to New Technology for Sustained High Resolution Observations of Plankton: From Bloom Dynamics to Climate Change

NASA Astrophysics Data System (ADS)

Sosik, H. M.; Olson, R. J.

2012-12-01

The combination of ocean observatory infrastructure and automated submersible flow cytometry can provide unprecedented capability for sustained high resolution time series of plankton, including taxa that are harmful or early indicators of ecosystem response to environmental change. Over the past decade, we have developed the FlowCytobot series of instruments that exemplify this capability. FlowCytobot and Imaging FlowCytobot use a combination of laser-based scattering and fluorescence measurements and video imaging of individual particles to enumerate and characterize cells ranging from picocyanobacteria to large chaining-forming diatoms. The process of developing these complex instruments was streamlined by access to the Martha's Vineyard Coastal Observatory (MVCO), a cabled facility on the New England Shelf, where real time two-way communications and access to shore power expedited cycles of instrument evaluation and design refinement. Repeated deployments at MVCO, typically 6 months in duration, have produced multi-year high resolution (hourly to daily) time series that are providing new insights into dynamics of community structure such as blooms, seasonality, and possibly even trends linked to regional climate change. The high temporal resolution observations of single cell properties make it possible not only to characterize taxonomic composition and size structure, but also to quantify taxon-specific growth rates. To meet the challenge of broadening access to this enabling technology, we have taken a two-step approach. First, we are partnering with a few scientific collaborators interested in using the instruments in different environments and to address different applications, notably the detection and characterization of harmful algal bloom events. Collaboration at this stage ensured that these first users outside the developers' lab had access to technical know-how required for successful outcomes; it also provided additional feedback that could be incorporated into more robust and user-friendly design. In the second and most recent stage, we have partnered with McLane Research Laboratories, Inc., a commercial vendor licensed to produce and market Imaging FlowCytobot. This stage of the development process has involved interactions between the scientific developers and company engineers, emphasizing joint construction of a pre-commercial prototype. A first run of commercially available units is anticipated to begin in the coming months paving the way for an expanding set of sustained high resolution plankton observations in conjunction with existing and emerging ocean observing systems.

8. SECOND IMAGE OF THE PANORAMIC SERIES LOOKING WEST FROM ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. SECOND IMAGE OF THE PANORAMIC SERIES LOOKING WEST FROM THE UPHILL SIDE OF THE MILL. THE ORE RECEIVING HOUSE AND THE ORE DELIVERY TRESTLE IS IMAGE RIGHT, THE MILL BUILDING AND ANCILLARY STRUCTURE ARE IMAGE CENTER AND THE TOWN OF BODIE IS IMAGE BACKGROUND RIGHT. - Standard Gold Mill, East of Bodie Creek, Northeast of Bodie, Bodie, Mono County, CA

Complex dynamic in ecological time series

Treesearch

Peter Turchin; Andrew D. Taylor

1992-01-01

Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...

Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; And Others

1992-01-01

The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

PubMed

Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

2018-02-12

The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

Filamentation and light bullet formation dynamics in solid-state dielectric media with weak, moderate and strong anomalous group velocity dispersion

NASA Astrophysics Data System (ADS)

Gražulevičiūtė, I.; Garejev, N.; Majus, D.; Jukna, V.; Tamošauskas, G.; Dubietis, A.

2016-02-01

We present a series of measurements, which characterize filamentation dynamics of intense ultrashort laser pulses in the space-time domain, as captured by means of three-dimensional imaging technique in sapphire and fused silica, in the wavelength range of 1.45-2.25 μm, accessing the regimes of weak, moderate and strong anomalous group velocity dispersion (GVD). In the regime of weak anomalous GVD (at 1.45 μm), pulse splitting into two sub-pulses producing a pair of light bullets with spectrally shifted carrier frequencies in both nonlinear media is observed. In contrast, in the regimes of moderate (at 1.8 μm) and strong (at 2.25 μm) anomalous GVD we observe notably different transient dynamics, which however lead to the formation of a single self-compressed quasistationary light bullet with an universal spatiotemporal shape comprised of an extended ring-shaped periphery and a localized intense core that carries the self-compressed pulse.

Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

NASA Astrophysics Data System (ADS)

Zhang, Xiaoping; Pan, Delu; Chen, Jianyu; Zhan, Yuanzeng; Mao, Zhihua

2013-01-01

Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on time-series classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution satellite images were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are <15 %. The results reveal that the ISA in the Zhoushan Islands increased from 19.2 km2 in 1986 to 86.5 km2 in 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59 km2 per year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. Time-series maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

In-vivo Fourier domain optical coherence tomography as a new tool for investigation of vasodynamics in the mouse model.

PubMed

Meissner, Sven; Müller, Gregor; Walther, Julia; Morawietz, Henning; Koch, Edmund

2009-01-01

In-vivo imaging of the vascular system can provide novel insight into the dynamics of vasoconstriction and vasodilation. Fourier domain optical coherence tomography (FD-OCT) is an optical, noncontact imaging technique based on interferometry of short-coherent near-infrared light with axial resolution of less than 10 microm. In this study, we apply FD-OCT as an in-vivo imaging technique to investigate blood vessels in their anatomical context using temporally resolved image stacks. Our chosen model system is the murine saphenous artery and vein, due to their small inner vessel diameters, sensitive response to vasoactive stimuli, and advantageous anatomical position. The vascular function of male wild-type mice (C57BL/6) is determined at the ages of 6 and 20 weeks. Vasoconstriction is analyzed in response to dermal application of potassium (K(+)), and vasodilation in response to sodium nitroprusside (SNP). Vasodynamics are quantified from time series (75 sec, 4 frames per sec, 330 x 512 pixels per frame) of cross sectional images that are analyzed by semiautomated image processing software. The morphology of the saphenous artery and vein is determined by 3-D image stacks of 512 x 512 x 512 pixels. Using the FD-OCT technique, we are able to demonstrate age-dependent differences in vascular function and vasodynamics.

Phytoplankton pigment patterns and wind forcing off central California

NASA Technical Reports Server (NTRS)

Abbott, Mark R.; Barksdale, Brett

1991-01-01

Mesoscale variability in phytoplankton pigment distributions of central California during the spring-summer upwelling season are studied via a 4-yr time series of high-resolution coastal zone color scanner imagery. Empirical orthogonal functions are used to decompose the time series of spatial images into its dominant modes of variability. The coupling between wind forcing of the upper ocean and phytoplankton distribution on mesoscales is investigated. Wind forcing, in particular the curl of the wind stress, was found to play an important role in the distribution of phytoplankton pigment in the California Current. The spring transition varies in timing and intensity from year to year but appears to be a recurrent feature associated with the rapid onset of the upwelling-favorable winds. Although the underlying dynamics may be dominated by processes other than forcing by wind stress curl, it appears that curl may force the variability of the filaments and hence the pigment patterns.

A Microplate Reader-Based System for Visualizing Transcriptional Activity During in vivo Microbial Interactions in Space and Time.

PubMed

Hennessy, Rosanna C; Stougaard, Peter; Olsson, Stefan

2017-03-21

Here, we report the development of a microplate reader-based system for visualizing gene expression dynamics in living bacterial cells in response to a fungus in space and real-time. A bacterium expressing the red fluorescent protein mCherry fused to the promoter region of a regulator gene nunF indicating activation of an antifungal secondary metabolite gene cluster was used as a reporter system. Time-lapse image recordings of the reporter red signal and a green signal from fluorescent metabolites combined with microbial growth measurements showed that nunF-regulated gene transcription is switched on when the bacterium enters the deceleration growth phase and upon physical encounter with fungal hyphae. This novel technique enables real-time live imaging of samples by time-series multi-channel automatic recordings using a microplate reader as both an incubator and image recorder of general use to researchers. The technique can aid in deciding when to destructively sample for other methods e.g. transcriptomics and mass spectrometry imaging to study gene expression and metabolites exchanged during the interaction.

STEM Tomography Imaging of Hypertrophied Golgi Stacks in Mucilage-Secreting Cells.

PubMed

Kang, Byung-Ho

2016-01-01

Because of the weak penetrating power of electrons, the signal-to-noise ratio of a transmission electron micrograph (TEM) worsens as section thickness increases. This problem is alleviated by the use of the scanning transmission electron microscopy (STEM). Tomography analyses using STEM of thick sections from yeast and mammalian cells are of higher quality than are bright-field (BF) images. In this study, we compared regular BF tomograms and STEM tomograms from 500-nm thick sections from hypertrophied Golgi stacks of alfalfa root cap cells. Due to their thickness and intense heavy metal staining, BF tomograms of the thick sections suffer from poor contrast and high noise levels. We were able to mitigate these drawbacks by using STEM tomography. When we performed STEM tomography of densely stained chloroplasts of Arabidopsis cotyledon, we observed similar improvements relative to BF tomograms. A longer time is required to collect a STEM tilt series than similar BF TEM images, and dynamic autofocusing required for STEM imaging often fails at high tilt angles. Despite these limitations, STEM tomography is a powerful method for analyzing structures of large or dense organelles of plant cells.

Preliminary Study on Earthquake Surface Rupture Extraction from Uav Images

NASA Astrophysics Data System (ADS)

Yuan, X.; Wang, X.; Ding, X.; Wu, X.; Dou, A.; Wang, S.

2018-04-01

Because of the advantages of low-cost, lightweight and photography under the cloud, UAVs have been widely used in the field of seismic geomorphology research in recent years. Earthquake surface rupture is a typical seismic tectonic geomorphology that reflects the dynamic and kinematic characteristics of crustal movement. The quick identification of earthquake surface rupture is of great significance for understanding the mechanism of earthquake occurrence, disasters distribution and scale. Using integrated differential UAV platform, series images were acquired with accuracy POS around the former urban area (Qushan town) of Beichuan County as the area stricken seriously by the 2008 Wenchuan Ms8.0 earthquake. Based on the multi-view 3D reconstruction technique, the high resolution DSM and DOM are obtained from differential UAV images. Through the shade-relief map and aspect map derived from DSM, the earthquake surface rupture is extracted and analyzed. The results show that the surface rupture can still be identified by using the UAV images although the time of earthquake elapse is longer, whose middle segment is characterized by vertical movement caused by compression deformation from fault planes.

Assessing blood vessel perfusion and vital signs through retinal imaging photoplethysmography.

PubMed

Hassan, Harnani; Jaidka, Sheila; Dwyer, Vincent M; Hu, Sijung

2018-05-01

One solution to the global challenge of increasing ocular disease is a cost-effective technique for rapid screening and assessment. Current ophthalmic imaging techniques, e.g. scanning and ocular blood flow systems, are expensive, complex to operate and utilize invasive contrast agents during assessment. The work presented here demonstrates a simple retinal imaging photoplethysmography (iPPG) system with the potential to provide screening, diagnosis, monitoring and assessment that is non-invasive, painless and radiationless. Time series of individual retinal blood vessel images, captured with an eye fundus camera, are processed using standard filtering, amplitude demodulation and principle component analysis (PCA) methods to determine the values of the heart rate (HR) and respiration rate (RR), which are in compliance with simultaneously obtained measurements using commercial pulse oximetry. It also seems possible that some information on the dynamic changes in oxygen saturation levels ( SpO 2 ) in a retinal blood vessel may also be obtained. As a consequence, the retinal iPPG modality system demonstrates a potential avenue for rapid ophthalmic screening, and even early diagnosis, against ocular disease without the need for fluorescent or contrast agents.

Statistical modelling of subdiffusive dynamics in the cytoplasm of living cells: A FARIMA approach

NASA Astrophysics Data System (ADS)

Burnecki, K.; Muszkieta, M.; Sikora, G.; Weron, A.

2012-04-01

Golding and Cox (Phys. Rev. Lett., 96 (2006) 098102) tracked the motion of individual fluorescently labelled mRNA molecules inside live E. coli cells. They found that in the set of 23 trajectories from 3 different experiments, the automatically recognized motion is subdiffusive and published an intriguing microscopy video. Here, we extract the corresponding time series from this video by image segmentation method and present its detailed statistical analysis. We find that this trajectory was not included in the data set already studied and has different statistical properties. It is best fitted by a fractional autoregressive integrated moving average (FARIMA) process with the normal-inverse Gaussian (NIG) noise and the negative memory. In contrast to earlier studies, this shows that the fractional Brownian motion is not the best model for the dynamics documented in this video.

SHARPs - A Near-Real-Time Space Weather Data Product from HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Turmon, M.; Baldner, C.; Sun, X.; Hoeksema, J. T.

2012-12-01

A data product from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO), called Space-weather HMI Active Region Patches (SHARPs), is now available through the SDO Joint Science Operations Center (JSOC) and the Virtual Solar Observatory. SHARPs are magnetically active regions identified on the solar disk and tracked automatically in time. SHARP data are processed within a few hours of the observation time. The SHARP data series contains active region-sized disambiguated vector magnetic field data in both Lambert Cylindrical Equal-Area and CCD coordinates on a 12 minute cadence. The series also provides simultaneous HMI maps of the line-of-sight magnetic field, continuum intensity, and velocity on the same ~0.5 arc-second pixel grid. In addition, the SHARP data series provides space weather quantities computed on the inverted, disambiguated, and remapped data. The values for each tracked region are computed and updated in near real time. We present space weather results for several X-class flares; furthermore, we compare said space weather quantities with helioseismic quantities calculated using ring-diagram analysis.

Annual land cover change mapping using MODIS time series to improve emissions inventories.

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Quaife, T. L.; Clifford, D.

2014-12-01

Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A prototype land cover product was created for 2006 to 2008. Several machine learning classifiers were tested as well as different sets of input features going from the BRDF parameters to spectral Albedo. We will present the results of the time series development and the first exercises when creating the prototype land cover product.

Cycles, scaling and crossover phenomenon in length of the day (LOD) time series

NASA Astrophysics Data System (ADS)

Telesca, Luciano

2007-06-01

The dynamics of the temporal fluctuations of the length of the day (LOD) time series from January 1, 1962 to November 2, 2006 were investigated. The power spectrum of the whole time series has revealed annual, semi-annual, decadal and daily oscillatory behaviors, correlated with oceanic-atmospheric processes and interactions. The scaling behavior was analyzed by using the detrended fluctuation analysis (DFA), which has revealed two different scaling regimes, separated by a crossover timescale at approximately 23 days. Flicker-noise process can describe the dynamics of the LOD time regime involving intermediate and long timescales, while Brownian dynamics characterizes the LOD time series for small timescales.

A Bayesian nonparametric approach to dynamical noise reduction

NASA Astrophysics Data System (ADS)

Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2018-06-01

We propose a Bayesian nonparametric approach for the noise reduction of a given chaotic time series contaminated by dynamical noise, based on Markov Chain Monte Carlo methods. The underlying unknown noise process (possibly) exhibits heavy tailed behavior. We introduce the Dynamic Noise Reduction Replicator model with which we reconstruct the unknown dynamic equations and in parallel we replicate the dynamics under reduced noise level dynamical perturbations. The dynamic noise reduction procedure is demonstrated specifically in the case of polynomial maps. Simulations based on synthetic time series are presented.

Magnetic Resonance Imaging (MRI): Dynamic Pelvic Floor

MedlinePlus

... Site Index A-Z Magnetic Resonance Imaging (MRI) – Dynamic Pelvic Floor Dynamic pelvic floor magnetic resonance imaging ( ... the limitations of pelvic floor MRI? What is dynamic pelvic floor MRI? Magnetic resonance imaging (MRI) is ...

Solar Coronal Jets Extending to High Altitudes Observed during the 2017 August 21 Total Eclipse

NASA Astrophysics Data System (ADS)

Hanaoka, Yoichiro; Hasuo, Ryuichi; Hirose, Tsukasa; Ikeda, Akiko C.; Ishibashi, Tsutomu; Manago, Norihiro; Masuda, Yukio; Morita, Sakuhiro; Nakazawa, Jun; Ohgoe, Osamu; Sakai, Yoshiaki; Sasaki, Kazuhiro; Takahashi, Koichi; Toi, Toshiyuki

2018-06-01

Coronal jets, which extend from the solar surface to beyond 2 R ⊙, were observed in the polar coronal hole regions during the total solar eclipse on 2017 August 21. In a time-series of white-light images of the corona spanning 70 minutes taken with our multi-site observations of this eclipse, six jets were found as narrow structures upwardly ejected with an apparent speed of about 450 km s‑1 in polar plumes. On the other hand, extreme-ultraviolet (EUV) images taken with the Atmospheric Image Assembly of the Solar Dynamics Observatory show that all of the eclipse jets were preceded by EUV jets. Conversely, all the EUV jets whose brightnesses are comparable to ordinary soft X-ray jets and that occurred in the polar regions near the eclipse period, were observed as eclipse jets. These results suggest that ordinary polar jets generally reach high altitudes and escape from the Sun as part of the solar wind.

Tomographic data fusion with CFD simulations associated with a planar sensor

NASA Astrophysics Data System (ADS)

Liu, J.; Liu, S.; Sun, S.; Zhou, W.; Schlaberg, I. H. I.; Wang, M.; Yan, Y.

2017-04-01

Tomographic techniques have great abilities to interrogate the combustion processes, especially when it is combined with the physical models of the combustion itself. In this study, a data fusion algorithm is developed to investigate the flame distribution of a swirl-induced environmental (EV) burner, a new type of burner for low NOx combustion. An electric capacitance tomography (ECT) system is used to acquire 3D flame images and computational fluid dynamics (CFD) is applied to calculate an initial distribution of the temperature profile for the EV burner. Experiments were also carried out to visualize flames at a series of locations above the burner. While the ECT images essentially agree with the CFD temperature distribution, discrepancies exist at a certain height. When data fusion is applied, the discrepancy is visibly reduced and the ECT images are improved. The methods used in this study can lead to a new route where combustion visualization can be much improved and applied to clean energy conversion and new burner development.

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

In vivo measurement of the average refractive index of the human crystalline lens using optical coherence tomography.

PubMed

de Freitas, Carolina; Ruggeri, Marco; Manns, Fabrice; Ho, Arthur; Parel, Jean-Marie

2013-01-15

We present a method for measuring the average group refractive index of the human crystalline lens in vivo using an optical coherence tomography (OCT) system which, allows full-length biometry of the eye. A series of OCT images of the eye including the anterior segment and retina were recorded during accommodation. Optical lengths of the anterior chamber, lens, and vitreous were measured dynamically along the central axis on the OCT images. The group refractive index of the crystalline lens along the central axis was determined using linear regression analysis of the intraocular optical length measurements. Measurements were acquired on three subjects of age 21, 24, and 35 years. The average group refractive index for the three subjects was, respectively, n=1.41, 1.43, and 1.39 at 835 nm.

Full-Sky Maps of the VHF Radio Sky with the Owens Valley Radio Observatory Long Wavelength Array

NASA Astrophysics Data System (ADS)

Eastwood, Michael W.; Hallinan, Gregg

2018-05-01

21-cm cosmology is a powerful new probe of the intergalactic medium at redshifts 20 >~ z >~ 6 corresponding to the Cosmic Dawn and Epoch of Reionization. Current observations of the highly-redshifted 21-cm transition are limited by the dynamic range they can achieve against foreground sources of low-frequency (<200 MHz) of radio emission. We used the Owens Valley Radio Observatory Long Wavelength Array (OVRO-LWA) to generate a series of new modern high-fidelity sky maps that capture emission on angular scales ranging from tens of degrees to ~15 arcmin, and frequencies between 36 and 73 MHz. These sky maps were generated from the application of Tikhonov-regularized m-mode analysis imaging, which is a new interferometric imaging technique that is uniquely suited for low-frequency, wide-field, drift-scanning interferometers.

WE-FG-202-01: Early Prediction of Radiotherapy Induced Skin Reactions Using Dynamic Infrared Imaging

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

Biswal, N; Cifter, G; Sun, J

Purpose: To predict radiotherapy induced skin reactions using dynamic infrared imaging. Methods: Thermal images were captured by our homebuilt system consisting of two flash lamps and an infrared (IR) camera. The surface temperature of the skin was first raised by ∼ 6 oC from ∼1 ms flashes. The camera then captured a series of IR images for 10 seconds. For each image, a baseline skin temperature was recorded for 0.5sec before heat impulse. The temporal temperature gradients were calculated between a reference point (immediately after the flash) and at a time point 9sec after that. Thermal effusivity, an intrinsic thermalmore » property of a material, was calculated from the surface temperature decay of skin. We present experimental data in five patients undergoing radiation therapy, of which 2 were Head & Neck, 1 was Sarcoma and 2 were Breast cancer patients. The prescribed doses were 45 – 60 Gy in 25 – 30 fractions. Each patient was imaged before treatment and after every fifth fraction until end of the treatment course. An area on the skin, outside the radiation field, was imaged as control region. During imaging, each patient’s irradiated skins were scored based on RTOG skin morbidity scoring criteria. Results: Temperature gradient, which is the temperature recovery rate, depends on the thermal properties of underlying tissue. It was observed that, the skin temperature and temporal temperature gradient increases with delivered radiation dose and skin RTOG score. The treatment does not change effusivity of superficial skin layer, however there was a significant difference in effusivity between treated and control areas at depth of ∼ 1.5 – 1.8 mm, increases with dose. Conclusion: The higher temporal temperature gradient and effusivity from irradiated areas suggest that there is more fluid under the irradiated skin, which causes faster temperature recovery. The mentioned effects may be predictors of Moist Desquamation.« less

JPEG2000 Image Compression on Solar EUV Images

NASA Astrophysics Data System (ADS)

Fischer, Catherine E.; Müller, Daniel; De Moortel, Ineke

2017-01-01

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bitrates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disc and off-limb coronal-loop oscillation time-series observed by AIA/SDO.

Semisupervised GDTW kernel-based fuzzy c-means algorithm for mapping vegetation dynamics in mining region using normalized difference vegetation index time series

NASA Astrophysics Data System (ADS)

Jia, Duo; Wang, Cangjiao; Lei, Shaogang

2018-01-01

Mapping vegetation dynamic types in mining areas is significant for revealing the mechanisms of environmental damage and for guiding ecological construction. Dynamic types of vegetation can be identified by applying interannual normalized difference vegetation index (NDVI) time series. However, phase differences and time shifts in interannual time series decrease mapping accuracy in mining regions. To overcome these problems and to increase the accuracy of mapping vegetation dynamics, an interannual Landsat time series for optimum vegetation growing status was constructed first by using the enhanced spatial and temporal adaptive reflectance fusion model algorithm. We then proposed a Markov random field optimized semisupervised Gaussian dynamic time warping kernel-based fuzzy c-means (FCM) cluster algorithm for interannual NDVI time series to map dynamic vegetation types in mining regions. The proposed algorithm has been tested in the Shengli mining region and Shendong mining region, which are typical representatives of China's open-pit and underground mining regions, respectively. Experiments show that the proposed algorithm can solve the problems of phase differences and time shifts to achieve better performance when mapping vegetation dynamic types. The overall accuracies for the Shengli and Shendong mining regions were 93.32% and 89.60%, respectively, with improvements of 7.32% and 25.84% when compared with the original semisupervised FCM algorithm.

Fluctuation of similarity to detect transitions between distinct dynamical regimes in short time series

NASA Astrophysics Data System (ADS)

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2014-06-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [N. Malik et al., Europhys. Lett. 97, 40009 (2012), 10.1209/0295-5075/97/40009], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In this work, we describe the details of the analytical relationships between this newly introduced measure and the well-known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method's robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the US crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980s and early 1990s, leading to increase in the dynamical complexity of these rates.

Optimization of Sample Preparation and Instrumental Parameters for the Rapid Analysis of Drugs of Abuse in Hair samples by MALDI-MS/MS Imaging

NASA Astrophysics Data System (ADS)

Flinders, Bryn; Beasley, Emma; Verlaan, Ricky M.; Cuypers, Eva; Francese, Simona; Bassindale, Tom; Clench, Malcolm R.; Heeren, Ron M. A.

2017-08-01

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) has been employed to rapidly screen longitudinally sectioned drug user hair samples for cocaine and its metabolites using continuous raster imaging. Optimization of the spatial resolution and raster speed were performed on intact cocaine contaminated hair samples. The optimized settings (100 × 150 μm at 0.24 mm/s) were subsequently used to examine longitudinally sectioned drug user hair samples. The MALDI-MS/MS images showed the distribution of the most abundant cocaine product ion at m/z 182. Using the optimized settings, multiple hair samples obtained from two users were analyzed in approximately 3 h: six times faster than the standard spot-to-spot acquisition method. Quantitation was achieved using longitudinally sectioned control hair samples sprayed with a cocaine dilution series. A multiple reaction monitoring (MRM) experiment was also performed using the `dynamic pixel' imaging method to screen for cocaine and a range of its metabolites, in order to differentiate between contaminated hairs and drug users. Cocaine, benzoylecgonine, and cocaethylene were detectable, in agreement with analyses carried out using the standard LC-MS/MS method. [Figure not available: see fulltext.

A JOINT FRAMEWORK FOR 4D SEGMENTATION AND ESTIMATION OF SMOOTH TEMPORAL APPEARANCE CHANGES.

PubMed

Gao, Yang; Prastawa, Marcel; Styner, Martin; Piven, Joseph; Gerig, Guido

2014-04-01

Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.

3D displacement time series in the Afar rift zone computed from SAR phase and amplitude information

NASA Astrophysics Data System (ADS)

Casu, Francesco; Manconi, Andrea

2013-04-01

Large and rapid deformations, such as those caused by earthquakes, eruptions, and landslides cannot be fully measured by using standard DInSAR applications. Indeed, the phase information often degrades and some areas of the interferograms are affected by high fringe rates, leading to difficulties in the phase unwrapping, and/or to complete loss of coherence due to significant misregistration errors. This limitation can be overcome by exploiting the SAR image amplitude information instead of the phase, and by calculating the Pixel-Offset (PO) field SAR image pairs, for both range and azimuth directions. Moreover, it is possible to combine the PO results by following the same rationale of the SBAS technique, to finally retrieve the offset-based deformation time series. Such technique, named PO-SBAS, permits to retrieve the deformation field in areas affected by very large displacements at an accuracy that, for ENVISAT data, correspond to 30 cm and 15 cm for the range and azimuth, respectively [1]. Moreover, the combination of SBAS and PO-SBAS time series can help to better study and model deformation phenomena characterized by spatial and temporal heterogeneities [2]. The Dabbahu rift segment of the Afar depression has been active since 2005 when a 2.5 km3 dyke intrusion and hundreds of earthquakes marked the onset a rifting episode which continues to date. The ENVISAT satellite has repeatedly imaged the Afar depression since 2003, generating a large SAR archive. In this work, we study the Afar rift region deformations by using both the phase and amplitude information of several sets of SAR images acquired from ascending and descending ENVISAT tracks. We combined sets of small baseline interferograms through the SBAS algorithm, and we generate both ground deformation maps and time series along the satellite Line-Of-Sight (LOS). In areas where the deformation gradient causes loss of coherence, we retrieve the displacement field through the amplitude information. Furthermore, we could also retrieve the full 3D deformation field, by considering the North-South displacement component obtained from the azimuth PO information. The combination of SBAS and PO-SBAS information permits to better retrieve and constrain the full deformation field due to repeated intrusions, fault movements, as well as the magma movements from individual magma chambers. [1] Casu, F., A. Manconi, A. Pepe and R. Lanari, 2011. Deformation time-series generation in areas characterized by large displacement dynamics: the SAR amplitude Pixel-Offset SBAS technique, IEEE Transaction on Geosciences and Remote Sensing. [2] Manconi, A. and F. Casu, 2012. Joint analysis of displacement time series retrieved from SAR phase and amplitude: impact on the estimation of volcanic source parameters, Geophysical Research Letters, doi:10.1029/2012GL052202.

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

PubMed Central

van Leeuwen, Willem J. D.

2008-01-01

This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests. PMID:27879809

ASPRS Digital Imagery Guideline Image Gallery Discussion

NASA Technical Reports Server (NTRS)

Ryan, Robert

2002-01-01

The objectives of the image gallery are to 1) give users and providers a simple means of identifying appropriate imagery for a given application/feature extraction; and 2) define imagery sufficiently to be described in engineering and acquisition terms. This viewgraph presentation includes a discussion of edge response and aliasing for image processing, and a series of images illustrating the effects of signal to noise ratio (SNR) on images. Another series of images illustrates how images are affected by varying the ground sample distances (GSD).

Dynamical complexity of short and noisy time series. Compression-Complexity vs. Shannon entropy

NASA Astrophysics Data System (ADS)

Nagaraj, Nithin; Balasubramanian, Karthi

2017-07-01

Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Imaging of the 3D dynamics of flagellar beating in human sperm.

PubMed

Silva-Villalobos, F; Pimentel, J A; Darszon, A; Corkidi, G

2014-01-01

The study of the mechanical and environmental factors that regulate a fundamental event such as fertilization have been subject of multiple studies. Nevertheless, the microscopical size of the spermatozoa and the high beating frequency of their flagella (up to 20 Hz) impose a series of technological challenges for the study of the mechanical factors implicated. Traditionally, due to the inherent characteristics of the rapid sperm movement, and to the technological limitations of microscopes (optical or confocal) to follow in three dimensions (3D) their movement, the analysis of their dynamics has been studied in two dimensions, when the head is confined to a surface. Flagella propel sperm and while their head can be confined to a surface, flagellar movement is not restricted to 2D, always displaying 3D components. In this work, we present a highly novel and useful tool to analyze sperm flagella dynamics in 3D. The basis of the method is a 100 Hz oscillating objective mounted on a bright field optical microscope covering a 16 microns depth space at a rate of ~ 5000 images per second. The best flagellum focused subregions were associated to their respective Z real 3D position. Unprecedented graphical results making evident the 3D movement of the flagella are shown in this work and supplemental material illustrating a 3D animation using the obtained experimental results is also included.

The "Chaos Theory" and nonlinear dynamics in heart rate variability analysis: does it work in short-time series in patients with coronary heart disease?

PubMed

Krstacic, Goran; Krstacic, Antonija; Smalcelj, Anton; Milicic, Davor; Jembrek-Gostovic, Mirjana

2007-04-01

Dynamic analysis techniques may quantify abnormalities in heart rate variability (HRV) based on nonlinear and fractal analysis (chaos theory). The article emphasizes clinical and prognostic significance of dynamic changes in short-time series applied on patients with coronary heart disease (CHD) during the exercise electrocardiograph (ECG) test. The subjects were included in the series after complete cardiovascular diagnostic data. Series of R-R and ST-T intervals were obtained from exercise ECG data after sampling digitally. The range rescaled analysis method determined the fractal dimension of the intervals. To quantify fractal long-range correlation's properties of heart rate variability, the detrended fluctuation analysis technique was used. Approximate entropy (ApEn) was applied to quantify the regularity and complexity of time series, as well as unpredictability of fluctuations in time series. It was found that the short-term fractal scaling exponent (alpha(1)) is significantly lower in patients with CHD (0.93 +/- 0.07 vs 1.09 +/- 0.04; P < 0.001). The patients with CHD had higher fractal dimension in each exercise test program separately, as well as in exercise program at all. ApEn was significant lower in CHD group in both RR and ST-T ECG intervals (P < 0.001). The nonlinear dynamic methods could have clinical and prognostic applicability also in short-time ECG series. Dynamic analysis based on chaos theory during the exercise ECG test point out the multifractal time series in CHD patients who loss normal fractal characteristics and regularity in HRV. Nonlinear analysis technique may complement traditional ECG analysis.

Exploration of the Energy Landscape of Acetylcholinesterase by Molecular Dynamics Simulation.

NASA Astrophysics Data System (ADS)

McCammon, J. Andrew

2002-03-01

Proteins have rough energy landscapes. Often more states than just the ground state are occupied and have biological functions. It is essential to study these conformational substates and the dynamical transitions among them. Acetylcholinesterase (AChE) is an important enzyme that has biological functions including the termination of synaptic transmission signals. X-ray structures show that it has an active site that is accessible only via a long and narrow channel from its surface. Therefore the fact that acetylcholine and larger ligands can reach the active site is believed to reflect the protein's structural fluctuation. We carried out long molecular dynamics simulations to investigate the dynamics of AChE and its relation to biological function, and compared our results with experiments. The results reveal several "doors" that open intermittantly between the active site and the surface. Instead of having simple exponential decay correlation functions, the time series of these channels reveal complex, fractal gating between conformations. We also compared the AChE dynamics data with those from an AchE-fasciculin complex. (Fasciculin is a small protein that is a natural inhibitor of AChE.) The results show remarkable effects of the protein-protein interaction, including allosteric and dynamical inhibition by fasciculin besides direct steric blocking. More information and images can be found at http://mccammon.ucsd.edu

Deducing multiple interfacial dynamics during polymeric foaming.

PubMed

Chandan, Mohammed Rehaan; Naskar, Nilanjon; Das, Anuja; Mukherjee, Rabibrata; Harikrishnan, Gopalakrishna Pillai

2018-06-15

Several interfacial phenomena are active during polymeric foaming, the dynamics of which significantly influence terminal stability, cell structure and in turn the thermo-mechanical properties of temporally evolved foam. Understanding these dynamics is important in achieving desired foam properties. Here, we introduce a method to simultaneously portray the time evolution of bubble growth, lamella thinning and Plateau border drainage, occurring during reactive polymeric foaming. In this method, we initially conduct bulk and surface shear rheology under polymerizing and non-foaming conditions. In a subsequent step, foaming experiments were conducted in a rheometer. The microscopic structural dimensions pertaining to the terminal values of the dynamics of each interfacial phenomena are then measured using a combination of scanning electron microscopy, optical microscopy and imaging ellipsometry, after the foaming is over. The measured surface and bulk rheological parameters are incorporated in time evolution equations that are derived from mass and momentum transport occurring when a model viscoelastic fluid is foamed by gas dispersion. Analytical and numerical solutions to these equations portray the dynamics. We demonstrate this method for a series of reactive polyurethane foams generated from different chemical sources. The effectiveness of our method is in simultaneously obtaining these dynamics that are difficult to directly monitor due to short active durations over multiple length scales.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Real-time bacterial microcolony counting using on-chip microscopy

NASA Astrophysics Data System (ADS)

Jung, Jae Hee; Lee, Jung Eun

2016-02-01

Observing microbial colonies is the standard method for determining the microbe titer and investigating the behaviors of microbes. Here, we report an automated, real-time bacterial microcolony-counting system implemented on a wide field-of-view (FOV), on-chip microscopy platform, termed ePetri. Using sub-pixel sweeping microscopy (SPSM) with a super-resolution algorithm, this system offers the ability to dynamically track individual bacterial microcolonies over a wide FOV of 5.7 mm × 4.3 mm without requiring a moving stage or lens. As a demonstration, we obtained high-resolution time-series images of S. epidermidis at 20-min intervals. We implemented an image-processing algorithm to analyze the spatiotemporal distribution of microcolonies, the development of which could be observed from a single bacterial cell. Test bacterial colonies with a minimum diameter of 20 μm could be enumerated within 6 h. We showed that our approach not only provides results that are comparable to conventional colony-counting assays but also can be used to monitor the dynamics of colony formation and growth. This microcolony-counting system using on-chip microscopy represents a new platform that substantially reduces the detection time for bacterial colony counting. It uses chip-scale image acquisition and is a simple and compact solution for the automation of colony-counting assays and microbe behavior analysis with applications in antibacterial drug discovery.

Real-time bacterial microcolony counting using on-chip microscopy

PubMed Central

Jung, Jae Hee; Lee, Jung Eun

2016-01-01

Observing microbial colonies is the standard method for determining the microbe titer and investigating the behaviors of microbes. Here, we report an automated, real-time bacterial microcolony-counting system implemented on a wide field-of-view (FOV), on-chip microscopy platform, termed ePetri. Using sub-pixel sweeping microscopy (SPSM) with a super-resolution algorithm, this system offers the ability to dynamically track individual bacterial microcolonies over a wide FOV of 5.7 mm × 4.3 mm without requiring a moving stage or lens. As a demonstration, we obtained high-resolution time-series images of S. epidermidis at 20-min intervals. We implemented an image-processing algorithm to analyze the spatiotemporal distribution of microcolonies, the development of which could be observed from a single bacterial cell. Test bacterial colonies with a minimum diameter of 20 μm could be enumerated within 6 h. We showed that our approach not only provides results that are comparable to conventional colony-counting assays but also can be used to monitor the dynamics of colony formation and growth. This microcolony-counting system using on-chip microscopy represents a new platform that substantially reduces the detection time for bacterial colony counting. It uses chip-scale image acquisition and is a simple and compact solution for the automation of colony-counting assays and microbe behavior analysis with applications in antibacterial drug discovery. PMID:26902822

Analysing the Image Building Effects of TV Advertisements Using Internet Community Data

NASA Astrophysics Data System (ADS)

Uehara, Hiroshi; Sato, Tadahiko; Yoshida, Kenichi

This paper proposes a method to measure the effects of TV advertisements on the Internet bulletin boards. It aims to clarify how the viewes' interests on TV advertisements are reflected on their images on the promoted products. Two kinds of time series data are generated based on the proposed method. First one represents the time series fluctuation of the interests on the TV advertisements. Another one represents the time series fluctuation of the images on the products. By analysing the correlations between these two time series data, we try to clarify the implicit relationship between the viewer's interests on the TV advertisement and their images on the promoted products. By applying the proposed method to an Internet bulletin board that deals with certain cosmetic brand, we show that the images on the products vary depending on the difference of the interests on each TV advertisement.

Dynamic Monitoring of Energy Services in Conflict Regions using Suomi-NPP VIIRS

NASA Astrophysics Data System (ADS)

Stokes, E.; Roman, M. O.

2015-12-01

While remote sensing data has proven useful for understanding the environmental conditions surrounding conflict, it can also present a more nuanced, dynamic picture inside conflict zones. This study investigates the use of global nighttime environmental products as derived from the Suomi-NPP satellite's Visible Infrared Imaging Radiometer Suite (VIIRS) to identify and track the location and timing of regional conflicts in the Middle East as reflected in changes to the region's energy infrastructure. The study focuses on a 43-month period (c. Jan 2012 - Aug 2015) over major urban centers in Iraq, Syria, Egypt, and Lebanon. The new daily dynamic products captured a series of striking downturns in energy service supply and demand that occurred in 2012 in the Syrian cities of Damascus (-50%) and Aleppo (-94%) corresponding to the onset of major military confrontations (The Battle of Aleppo on 7/15/2012 and The Damascus Bombing on 7/23/2012, respectively). Iraqi cities recently captured by the Islamic State of Iraq and the Levant (ISIL) (e.g. Mosul, Tikrit, Tal Afor, Ramadi), also showed marked average decreases in energy service provision (-84% since 4/1/2014) compared to their unoccupied counterparts (e.g., Baghdad and Sulaimaniya at +6%). A seasonal trend decomposition analysis is used to disentangle climactic, social, and political factors affecting the VIIRS time-series, distinguishing between energy patterns associated with conflict and those associated with cultural festivals, load shedding, seasonal weather, and socioeconomic factors.

Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks

PubMed Central

Nummenmaa, Lauri; Saarimäki, Heini; Glerean, Enrico; Gotsopoulos, Athanasios; Jääskeläinen, Iiro P.; Hari, Riitta; Sams, Mikko

2014-01-01

Speech provides a powerful means for sharing emotions. Here we implement novel intersubject phase synchronization and whole-brain dynamic connectivity measures to show that networks of brain areas become synchronized across participants who are listening to emotional episodes in spoken narratives. Twenty participants' hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI) while they listened to 45-s narratives describing unpleasant, neutral, and pleasant events spoken in neutral voice. After scanning, participants listened to the narratives again and rated continuously their feelings of pleasantness–unpleasantness (valence) and of arousal–calmness. Instantaneous intersubject phase synchronization (ISPS) measures were computed to derive both multi-subject voxel-wise similarity measures of hemodynamic activity and inter-area functional dynamic connectivity (seed-based phase synchronization, SBPS). Valence and arousal time series were subsequently used to predict the ISPS and SBPS time series. High arousal was associated with increased ISPS in the auditory cortices and in Broca's area, and negative valence was associated with enhanced ISPS in the thalamus, anterior cingulate, lateral prefrontal, and orbitofrontal cortices. Negative valence affected functional connectivity of fronto-parietal, limbic (insula, cingulum) and fronto-opercular circuitries, and positive arousal affected the connectivity of the striatum, amygdala, thalamus, cerebellum, and dorsal frontal cortex. Positive valence and negative arousal had markedly smaller effects. We propose that high arousal synchronizes the listeners' sound-processing and speech-comprehension networks, whereas negative valence synchronizes circuitries supporting emotional and self-referential processing. PMID:25128711

Spatial distribution of volcanic ash deposits of 2011 Puyehue-Cordón Caulle eruption in Patagonia as measured by a perturbation in NDVI temporal dynamics

NASA Astrophysics Data System (ADS)

Easdale, M. H.; Bruzzone, O.

2018-03-01

Volcanic ash fallout is a recurrent environmental disturbance in forests, arid and semi-arid rangelands of Patagonia, South America. The ash deposits over large areas are responsible for several impacts on ecological processes, agricultural production and health of local communities. Public policy decision making needs monitoring information of the affected areas by ash fallout, in order to better orient social, economic and productive aids. The aim of this study was to analyze the spatial distribution of volcanic ash deposits from the eruption of Puyehue-Cordón Caulle in 2011, by identifying a sudden change in the Normalized Difference Vegetation Index (NDVI) temporal dynamics, defined as a perturbation located in the time series. We applied a sparse-wavelet transform using the Basis Pursuit algorithm to NDVI time series obtained from the Moderate Resolution Image Spectroradiometer (MODIS) sensor, to identify perturbations at a pixel level. The spatial distribution of the perturbation promoted by ash deposits in Patagonia was successfully identified and characterized by means of a perturbation in NDVI temporal dynamics. Results are encouraging for the future development of a new platform, in combination with data from forecasting models and tracking of ash cloud trajectories and dispersion, to inform stakeholders to mitigate impact of volcanic ash on agricultural production and to orient public intervention strategies after a volcanic eruption followed by ash fallout over a wide region.

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

NASA Astrophysics Data System (ADS)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government policies in China on the changes of dynamics of GDP and the three industries adjustment. The work in our paper provides a new way to understand the dynamics of economic development.

Immersion and dry scanner extensions for sub-10nm production nodes

NASA Astrophysics Data System (ADS)

Weichselbaum, Stefan; Bornebroek, Frank; de Kort, Toine; Droste, Richard; de Graaf, Roelof F.; van Ballegoij, Rob; Botter, Herman; McLaren, Matthew G.; de Boeij, Wim P.

2015-03-01

Progressing towards the 10nm and 7nm imaging node, pattern-placement and layer-to-layer overlay requirements keep on scaling down and drives system improvements in immersion (ArFi) and dry (ArF/KrF) scanners. A series of module enhancements in the NXT platform have been introduced; among others, the scanner is equipped with exposure stages with better dynamics and thermal control. Grid accuracy improvements with respect to calibration, setup, stability, and layout dependency tighten MMO performance and enable mix and match scanner operation. The same platform improvements also benefit focus control. Improvements in detectability and reproducibility of low contrast alignment marks enhance the alignment solution window for 10nm logic processes and beyond. The system's architecture allows dynamic use of high-order scanner optimization based on advanced actuators of projection lens and scanning stages. This enables a holistic optimization approach for the scanner, the mask, and the patterning process. Productivity scanner design modifications esp. stage speeds and optimization in metrology schemes provide lower layer costs for customers using immersion lithography as well as conventional dry technology. Imaging, overlay, focus, and productivity data is presented, that demonstrates 10nm and 7nm node litho-capability for both (immersion & dry) platforms.

Stereo Refractive Imaging of Breaking Free-Surface Waves in the Surf Zone

NASA Astrophysics Data System (ADS)

Mandel, Tracy; Weitzman, Joel; Koseff, Jeffrey; Environmental Fluid Mechanics Laboratory Team

2014-11-01

Ocean waves drive the evolution of coastlines across the globe. Wave breaking suspends sediments, while wave run-up, run-down, and the undertow transport this sediment across the shore. Complex bathymetric features and natural biotic communities can influence all of these dynamics, and provide protection against erosion and flooding. However, our knowledge of the exact mechanisms by which this occurs, and how they can be modeled and parameterized, is limited. We have conducted a series of controlled laboratory experiments with the goal of elucidating these details. These have focused on quantifying the spatially-varying characteristics of breaking waves and developing more accurate techniques for measuring and predicting wave setup, setdown, and run-up. Using dynamic refraction stereo imaging, data on free-surface slope and height can be obtained over an entire plane. Wave evolution is thus obtained with high spatial precision. These surface features are compared with measures of instantaneous turbulence and mean currents within the water column. We then use this newly-developed ability to resolve three-dimensional surface features over a canopy of seagrass mimics, in order to validate theoretical formulations of wave-vegetation interactions in the surf zone.

Time-Series Photographs of the Sea Floor in Western Massachusetts Bay: June 1998 to May 1999

USGS Publications Warehouse

Butman, Bradford; Alexander, P. Soupy; Bothner, Michael H.

2004-01-01

This report presents time-series photographs of the sea floor obtained from an instrumented tripod deployed at Site A in western Massachusetts Bay (42? 22.6' N., 70? 47.0' W., 30 m water depth, figure 1) from June 1998 through May 1999. Site A is approximately 1 km south of an ocean outfall that began discharging treated sewage effluent from the Boston metropolitan area into Massachusetts Bay in September 2000. Time-series photographs and oceanographic observations were initiated at Site A in December 1989 and are anticipated to continue to September 2005. This one of a series of reports that present these images in digital form. The objective of these reports is to enable easy and rapid viewing of the photographs and to provide a medium-resolution digital archive. The images, obtained every 4 hours, are presented as a movie (in .avi format, which may be viewed using an image viewer such as QuickTime or Windows Media Player) and as individual images (.tif format). The images provide time-series observations of changes of the sea floor and near-bottom water properties.

Ground-based imaging spectrometry of canopy phenology and chemistry in a deciduous forest

NASA Astrophysics Data System (ADS)

Toomey, M. P.; Friedl, M. A.; Frolking, S. E.; Hilker, T.; O'Keefe, J.; Richardson, A. D.

2013-12-01

Phenology, annual life cycles of plants and animals, is a dynamic ecosystem attribute and an important feedback to climate change. Vegetation phenology is commonly monitored at canopy to continental scales using ground based digital repeat photography and satellite remote sensing, respectively. Existing systems which provide sufficient temporal resolution for phenological monitoring, however, lack the spectral resolution necessary to investigate the coupling of phenology with canopy chemistry (e.g. chlorophyll, nitrogen, lignin-cellulose content). Some researchers have used narrowband (<10 nm resolution) spectrometers at phenology monitoring sites, yielding new insights into seasonal changes in leaf biochemistry. Such instruments integrate the spectral characteristics of the entire canopy, however, masking considerable variability between species and plant functional types. There is an opportunity, then, for exploring the potential of imaging spectrometers to investigate the coupling of canopy phenology and the leaf biochemistry of individual trees. During the growing season of April-October 2013 we deployed an imaging spectrometer with a spectral range of 371-1042 nm and resolution of ~5 nm (Surface Optics Corporation 710; San Diego, CA) on a 35 m tall tower at the Harvard Forest, Massachusetts. The image resolution was ~0.25 megapixels and the field of view encompassed approximately 20 individual tree crowns at a distance of 20-40 m. The instrument was focused on a mixed hardwoods canopy composed of 4 deciduous tree species and one coniferous tree species. Scanning was performed daily with an acquisition frequency of 30 minutes during daylight hours. Derived imagery were used to calculate a suite of published spectral indices used to estimate foliar content of key pigments: cholorophyll, carotenoids and anthocyanins. Additionally, we calculated the photochemical reflectance index (PRI) as well as the position and slope of the red edge as indicators of mid- to late-summer plant stress. Changes in the spectral shape and indices throughout the growing season revealed coupling of leaf biochemistry and phenology, as visually observed in situ. Further, the spectrally rich imagery provided well calibrated reflectance data to simulate vegetation index time series of common spaceborne remote sensing platforms such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat. Comparisons between the simulated time series and in situ phenology observations yielded an enhanced interpretation of vegetation indices for determining phenological transition dates. This study demonstrates an advance in our ability to relate canopy phenology to leaf-level dynamics and demonstrates the role that ground-based imaging spectrometry can play in advancing spaceborne remote sensing of vegetation phenology.

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Scanning transmission electron microscopy through-focal tilt-series on biological specimens.

PubMed

Trepout, Sylvain; Messaoudi, Cédric; Perrot, Sylvie; Bastin, Philippe; Marco, Sergio

2015-10-01

Since scanning transmission electron microscopy can produce high signal-to-noise ratio bright-field images of thick (≥500 nm) specimens, this tool is emerging as the method of choice to study thick biological samples via tomographic approaches. However, in a convergent-beam configuration, the depth of field is limited because only a thin portion of the specimen (from a few nanometres to tens of nanometres depending on the convergence angle) can be imaged in focus. A method known as through-focal imaging enables recovery of the full depth of information by combining images acquired at different levels of focus. In this work, we compare tomographic reconstruction with the through-focal tilt-series approach (a multifocal series of images per tilt angle) with reconstruction with the classic tilt-series acquisition scheme (one single-focus image per tilt angle). We visualised the base of the flagellum in the protist Trypanosoma brucei via an acquisition and image-processing method tailored to obtain quantitative and qualitative descriptors of reconstruction volumes. Reconstructions using through-focal imaging contained more contrast and more details for thick (≥500 nm) biological samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

An evaluation of dynamic mutuality measurements and methods in cyclic time series

NASA Astrophysics Data System (ADS)

Xia, Xiaohua; Huang, Guitian; Duan, Na

2010-12-01

Several measurements and techniques have been developed to detect dynamic mutuality and synchronicity of time series in econometrics. This study aims to compare the performances of five methods, i.e., linear regression, dynamic correlation, Markov switching models, concordance index and recurrence quantification analysis, through numerical simulations. We evaluate the abilities of these methods to capture structure changing and cyclicity in time series and the findings of this paper would offer guidance to both academic and empirical researchers. Illustration examples are also provided to demonstrate the subtle differences of these techniques.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

Time series analyses of breathing patterns of lung cancer patients using nonlinear dynamical system theory.

PubMed

Tewatia, D K; Tolakanahalli, R P; Paliwal, B R; Tomé, W A

2011-04-07

The underlying requirements for successful implementation of any efficient tumour motion management strategy are regularity and reproducibility of a patient's breathing pattern. The physiological act of breathing is controlled by multiple nonlinear feedback and feed-forward couplings. It would therefore be appropriate to analyse the breathing pattern of lung cancer patients in the light of nonlinear dynamical system theory. The purpose of this paper is to analyse the one-dimensional respiratory time series of lung cancer patients based on nonlinear dynamics and delay coordinate state space embedding. It is very important to select a suitable pair of embedding dimension 'm' and time delay 'τ' when performing a state space reconstruction. Appropriate time delay and embedding dimension were obtained using well-established methods, namely mutual information and the false nearest neighbour method, respectively. Establishing stationarity and determinism in a given scalar time series is a prerequisite to demonstrating that the nonlinear dynamical system that gave rise to the scalar time series exhibits a sensitive dependence on initial conditions, i.e. is chaotic. Hence, once an appropriate state space embedding of the dynamical system has been reconstructed, we show that the time series of the nonlinear dynamical systems under study are both stationary and deterministic in nature. Once both criteria are established, we proceed to calculate the largest Lyapunov exponent (LLE), which is an invariant quantity under time delay embedding. The LLE for all 16 patients is positive, which along with stationarity and determinism establishes the fact that the time series of a lung cancer patient's breathing pattern is not random or irregular, but rather it is deterministic in nature albeit chaotic. These results indicate that chaotic characteristics exist in the respiratory waveform and techniques based on state space dynamics should be employed for tumour motion management.

Microsecond resolved single-molecule FRET time series measurements based on the line confocal optical system combined with hybrid photodetectors.

PubMed

Oikawa, Hiroyuki; Takahashi, Takumi; Kamonprasertsuk, Supawich; Takahashi, Satoshi

2018-01-31

Single-molecule (sm) fluorescence time series measurements based on the line confocal optical system are a powerful strategy for the investigation of the structure, dynamics, and heterogeneity of biological macromolecules. This method enables the detection of more than several thousands of fluorescence photons per millisecond from single fluorophores, implying that the potential time resolution for measurements of the fluorescence resonance energy transfer (FRET) efficiency is 10 μs. However, the necessity of using imaging photodetectors in the method limits the time resolution in the FRET efficiency measurements to approximately 100 μs. In this investigation, a new photodetector called a hybrid photodetector (HPD) was incorporated into the line confocal system to improve the time resolution without sacrificing the length of the time series detection. Among several settings examined, the system based on a slit width of 10 μm and a high-speed counting device made the best of the features of the line confocal optical system and the HPD. This method achieved a time resolution of 10 μs and an observation time of approximately 5 ms in the sm-FRET time series measurements. The developed device was used for the native state of the B domain of protein A.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations.

PubMed

Almog, Assaf; Besamusca, Ferry; MacMahon, Mel; Garlaschelli, Diego

2015-01-01

The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. The organization is determined by "communities" of units whose dynamics, represented by time series of activity, is more strongly correlated internally than with the rest of the system. Recent studies have shown that the binary projections of various financial and neural time series exhibit nontrivial dynamical features that resemble those of the original data. This implies that a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. Here, we explore whether the binary signatures of multiple time series can replicate the same complex community organization of the financial market, as the original weighted time series. We adopt a method that has been specifically designed to detect communities from cross-correlation matrices of time series data. Our analysis shows that the simpler binary representation leads to a community structure that is almost identical with that obtained using the full weighted representation. These results confirm that binary projections of financial time series contain significant structural information.

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

PubMed

Cai, Biao; Zille, Pascal; Stephen, Julia M; Wilson, Tony W; Calhoun, Vince D; Wang, Yu Ping

2018-05-01

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) time series, especially during resting state periods, provides a powerful tool to assess human brain functional architecture in health, disease, and developmental states. Recently, the focus of connectivity analysis has shifted toward the subnetworks of the brain, which reveals co-activating patterns over time. Most prior works produced a dense set of high-dimensional vectors, which are hard to interpret. In addition, their estimations to a large extent were based on an implicit assumption of spatial and temporal stationarity throughout the fMRI scanning session. In this paper, we propose an approach called dynamic sparse connectivity patterns (dSCPs), which takes advantage of both matrix factorization and time-varying fMRI time series to improve the estimation power of FC. The feasibility of analyzing dynamic FC with our model is first validated through simulated experiments. Then, we use our framework to measure the difference between young adults and children with real fMRI data set from the Philadelphia Neurodevelopmental Cohort (PNC). The results from the PNC data set showed significant FC differences between young adults and children in four different states. For instance, young adults had reduced connectivity between the default mode network and other subnetworks, as well as hyperconnectivity within the visual system in states 1 and 3, and hypoconnectivity in state 2. Meanwhile, they exhibited temporal correlation patterns that changed over time within functional subnetworks. In addition, the dSCPs model indicated that older people tend to spend more time within a relatively connected FC pattern. Overall, the proposed method provides a valid means to assess dynamic FC, which could facilitate the study of brain networks.

Sequential visibility-graph motifs

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Lacasa, Lucas

2016-04-01

Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of sequential visibility-graph motifs, smaller substructures of n consecutive nodes that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated with general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable of distinguishing among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification and description of physical, biological, and financial time series.

Detecting dynamical changes in time series by using the Jensen Shannon divergence

NASA Astrophysics Data System (ADS)

Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

2017-08-01

Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.

Coastline detection with time series of SAR images

NASA Astrophysics Data System (ADS)

Ao, Dongyang; Dumitru, Octavian; Schwarz, Gottfried; Datcu, Mihai

2017-10-01

For maritime remote sensing, coastline detection is a vital task. With continuous coastline detection results from satellite image time series, the actual shoreline, the sea level, and environmental parameters can be observed to support coastal management and disaster warning. Established coastline detection methods are often based on SAR images and wellknown image processing approaches. These methods involve a lot of complicated data processing, which is a big challenge for remote sensing time series. Additionally, a number of SAR satellites operating with polarimetric capabilities have been launched in recent years, and many investigations of target characteristics in radar polarization have been performed. In this paper, a fast and efficient coastline detection method is proposed which comprises three steps. First, we calculate a modified correlation coefficient of two SAR images of different polarization. This coefficient differs from the traditional computation where normalization is needed. Through this modified approach, the separation between sea and land becomes more prominent. Second, we set a histogram-based threshold to distinguish between sea and land within the given image. The histogram is derived from the statistical distribution of the polarized SAR image pixel amplitudes. Third, we extract continuous coastlines using a Canny image edge detector that is rather immune to speckle noise. Finally, the individual coastlines derived from time series of .SAR images can be checked for changes.

Characterization of Metalorganic Chemical Vapor Deposition

NASA Technical Reports Server (NTRS)

Jesser, W. A.

1998-01-01

A series of experimental and numerical investigations to develop a more complete understanding of the reactive fluid dynamics of chemical vapor deposition were conducted. In the experimental phases of the effort, a horizontal CVD reactor configuration was used for the growth of InP at UVA and for laser velocimetry measurements of the flow fields in the reactor at LaRC. This horizontal reactor configuration was developed for the growth of III-V semiconductors and has been used by our research group in the past to study the deposition of both GaAs and InP. While the ultimate resolution of many of the heat and mass transport issues will require access to a reduced-gravity environment, the series of groundbased research makes direct contributions to this area while attempting to answer the design questions for future experiments of how low must gravity be reduced and for how long must this gravity level be maintained to make the necessary measurements. It is hoped that the terrestrial experiments will be useful for the design of future microgravity experiments which likely will be designed to employ a core set of measurements for applications in the microgravity environment such as HOLOC, the Fluid Physics/Dynamics Facility, or the Schlieren photography, the Laser Imaging Velocimetry and the Laser Doppler Velocimetry instruments under development for the Advanced Fluids Experiment Module.

Facet Joint Osteoarthritis Affects Spinal Segmental Motion in Degenerative Spondylolisthesis.

PubMed

Kitanaka, Shigeyuki; Takatori, Ryota; Arai, Yuji; Nagae, Masateru; Tonomura, Hitoshi; Mikami, Yasuo; Inoue, Nozomu; Ogura, Taku; Fujiwara, Hiroyoshi; Kubo, Toshikazu

2018-06-15

This is a retrospective clinical case series (case-control study). To clarify the influence of facet joint osteoarthritis (FJOA) on the pathology of degenerative spondylolisthesis (DS) using in vivo 3-dimensional image analysis. There are no radical treatments to prevent progression of DS in patients with lumbar spinal canal stenosis associated with DS. Therefore, an effective treatment method based on the pathology of DS should be developed. In total, 50 patients with lumbar spinal canal stenosis involving L4/5 who underwent dynamic computed tomography were divided into 2 groups: with DS [spondylolisthesis (Sp) group; 12 male, 14 female; mean age, 74 y]; and without DS (non-Sp group; 15 male, 9 female; mean age, 70 y). Degeneration of the intervertebral disk and FJOA at L4/5 were evaluated using magnetic resonance imaging. Disk and intervertebral foramen heights, the distance between the craniocaudal edges of the facet joint, and the interspinous distance were measured on dynamic computed tomographic images. Also, in vivo 3-dimensional segmental motion was evaluated using the volume merge method. There were no significant differences in degenerative findings for the intervertebral disk; however, progressive FJOA was detected in the Sp group. Dynamic changes in the distance between the craniocaudal edges of the facet joints were significantly larger in the Sp group. In this study, progressive FJOA and larger segmental motion in the distance between the craniocaudal edges of the facet joints were found in the Sp group. We clarified for the first time that DS involves ligament laxity due to FJOA that affects spinal segmental motion in vivo. We consider that a treatment method based on FJOA would be useful for treating patients with DS. Level IV.

Slope effects on the fluid dynamics of a fire spreading across a fuel bed: PIV measurements and OH* chemiluminescence imaging

NASA Astrophysics Data System (ADS)

Morandini, F.; Silvani, X.; Honoré, D.; Boutin, G.; Susset, A.; Vernet, R.

2014-08-01

Slope is among the most influencing factor affecting the spread of wildfires. A contribution to the understanding of the fluid dynamics of a fire spreading in these terrain conditions is provided in the present paper. Coupled optical diagnostics are used to study the slope effects on the flow induced by a fire at laboratory scale. Optical diagnostics consist of particle image velocimetry, for investigating the 2D (vertical) velocity field of the reacting flow and chemiluminescence imaging, for visualizing the region of spontaneous emission of OH radical occurring during gaseous combustion processes. The coupling of these two techniques allows locating accurately the contour of the reaction zone within the computed velocity field. The series of experiments are performed across a bed of vegetative fuel, under both no-slope and 30° upslope conditions. The increase in the rate of fire spread with increasing slope is attributed to a significant change in fluid dynamics surrounding the flame. For horizontal fire spread, flame fronts exhibit quasi-vertical plume resulting in the buoyancy forces generated by the fire. These buoyancy effects induce an influx of ambient fresh air which is entrained laterally into the fire, equitably from both sides. For upward flame spread, the induced flow is strongly influenced by air entrainment on the burnt side of the fire and fire plume is tilted toward unburned vegetation. A particular attention is paid to the induced air flow ahead of the spreading flame. With increasing the slope angle beyond a threshold, highly dangerous conditions arise because this configuration induces wind blows away from the fire rather than toward it, suggesting the presence of convective heat transfers ahead of the fire front.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

PubMed Central

Stetter, Olav; Battaglia, Demian; Soriano, Jordi; Geisel, Theo

2012-01-01

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local. PMID:22927808

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Mapping forest height, foliage height profiles and disturbance characteristics with time series of gap-filled Landsat and ALI imagery

NASA Astrophysics Data System (ADS)

Helmer, E.; Ruzycki, T. S.; Wunderle, J. M.; Kwit, C.; Ewert, D. N.; Voggesser, S. M.; Brandeis, T. J.

2011-12-01

We mapped tropical dry forest height (RMSE = 0.9 m, R2 = 0.84, range 0.6-7 m) and foliage height profiles with a time series of gap-filled Landsat and Advanced Land Imager (ALI) imagery for the island of Eleuthera, The Bahamas. We also mapped disturbance type and age with decision tree classification of the image time series. Having mapped these variables in the context of studies of wintering habitat of an endangered Nearctic-Neotropical migrant bird, the Kirtland's Warbler (Dendroica kirtlandii), we then illustrated relationships between forest vertical structure, disturbance type and counts of forage species important to the Kirtland's Warbler. The ALI imagery and the Landsat time series were both critical to the result for forest height, which the strong relationship of forest height with disturbance type and age facilitated. Also unique to this study was that seven of the eight image time steps were cloud-gap-filled images: mosaics of the clear parts of several cloudy scenes, in which cloud gaps in a reference scene for each time step are filled with image data from alternate scenes. We created each cloud-cleared image, including a virtually seamless ALI image mosaic, with regression tree normalization of the image data that filled cloud gaps. We also illustrated how viewing time series imagery as red-green-blue composites of tasseled cap wetness (RGB wetness composites) aids reference data collection for classifying tropical forest disturbance type and age.

Automatic Generation of Wide Dynamic Range Image without Pseudo-Edge Using Integration of Multi-Steps Exposure Images

NASA Astrophysics Data System (ADS)

Migiyama, Go; Sugimura, Atsuhiko; Osa, Atsushi; Miike, Hidetoshi

Recently, digital cameras are offering technical advantages rapidly. However, the shot image is different from the sight image generated when that scenery is seen with the naked eye. There are blown-out highlights and crushed blacks in the image that photographed the scenery of wide dynamic range. The problems are hardly generated in the sight image. These are contributory cause of difference between the shot image and the sight image. Blown-out highlights and crushed blacks are caused by the difference of dynamic range between the image sensor installed in a digital camera such as CCD and CMOS and the human visual system. Dynamic range of the shot image is narrower than dynamic range of the sight image. In order to solve the problem, we propose an automatic method to decide an effective exposure range in superposition of edges. We integrate multi-step exposure images using the method. In addition, we try to erase pseudo-edges using the process to blend exposure values. Afterwards, we get a pseudo wide dynamic range image automatically.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

An Improved dem Construction Method for Mudflats Based on BJ-1 Small Satellite Images: a Case Study on Bohai Bay

NASA Astrophysics Data System (ADS)

Wu, D.; Du, Y.; Su, F.; Huang, W.; Zhang, L.

2018-04-01

The topographic measurement of muddy tidal flat is restricted by the difficulty of access to the complex, wide-range and dynamic tidal conditions. Then the waterline detection method (WDM) has the potential to investigate the morph-dynamics quantitatively by utilizing large archives of satellite images. The study explores the potential for using WDM with BJ-1 small satellite images to construct a digital elevation model (DEM) of a wide and grading mudflat. Three major conclusions of the study are as follows: (1) A new intelligent correlating model of waterline detection considering different tidal stages and local geographic conditions was explored. With this correlative algorithm waterline detection model, a series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of a year. The model proved to detect waterlines more efficiently and exactly. (2) The spatial structure of elevation superimposing on the points of waterlines was firstly constructed and a more accurate hydrodynamic ocean tide grid model was used. By the newly constructed abnormal hydrology evaluation model, a more reasonable and reliable set of waterline points was acquired to construct a smoother TIN and GRID DEM. (3) DEM maps of Bohai Bay, with a spatial resolution of about 30 m and height accuracy of about 0.35 m considering LiDAR and 0.19 m considering RTK surveying were constructed over an area of about 266 km2. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible and is an effective tool for monitoring the tidal flats.

PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

PubMed

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

A PRESTO-SENSE sequence with alternating partial-Fourier encoding for rapid susceptibility-weighted 3D MRI time series.

PubMed

Klarhöfer, Markus; Dilharreguy, Bixente; van Gelderen, Peter; Moonen, Chrit T W

2003-10-01

A 3D sequence for dynamic susceptibility imaging is proposed which combines echo-shifting principles (such as PRESTO), sensitivity encoding (SENSE), and partial-Fourier acquisition. The method uses a moderate SENSE factor of 2 and takes advantage of an alternating partial k-space acquisition in the "slow" phase encode direction allowing an iterative reconstruction using high-resolution phase estimates. Offering an isotropic spatial resolution of 4 x 4 x 4 mm(3), the novel sequence covers the whole brain including parts of the cerebellum in 0.5 sec. Its temporal signal stability is comparable to that of a full-Fourier, full-FOV EPI sequence having the same dynamic scan time but much less brain coverage. Initial functional MRI experiments showed consistent activation in the motor cortex with an average signal change slightly less than that of EPI. Copyright 2003 Wiley-Liss, Inc.

Gaussian process inference for estimating pharmacokinetic parameters of dynamic contrast-enhanced MR images.

PubMed

Wang, Shijun; Liu, Peter; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Summers, Ronald M

2012-01-01

In this paper, we propose a new pharmacokinetic model for parameter estimation of dynamic contrast-enhanced (DCE) MRI by using Gaussian process inference. Our model is based on the Tofts dual-compartment model for the description of tracer kinetics and the observed time series from DCE-MRI is treated as a Gaussian stochastic process. The parameter estimation is done through a maximum likelihood approach and we propose a variant of the coordinate descent method to solve this likelihood maximization problem. The new model was shown to outperform a baseline method on simulated data. Parametric maps generated on prostate DCE data with the new model also provided better enhancement of tumors, lower intensity on false positives, and better boundary delineation when compared with the baseline method. New statistical parameter maps from the process model were also found to be informative, particularly when paired with the PK parameter maps.

Highly-sensitive and large-dynamic diffuse optical tomography system for breast tumor detection

NASA Astrophysics Data System (ADS)

Du, Wenwen; Zhang, Limin; Yin, Guoyan; Zhang, Yanqi; Zhao, Huijuan; Gao, Feng

2018-02-01

Diffuse optical tomography (DOT) as a new functional imaging has important clinical applications in many aspects such as benign and malignant breast tumor detection, tumor staging and so on. For quantitative detection of breast tumor, a three-wavelength continuous-wave DOT prototype system combined the ultra-high sensitivity of the photon-counting detection and the measurement parallelism of the lock-in technique was developed to provide high temporal resolution, high sensitivity, large dynamic detection range and signal-to-noise ratio. Additionally, a CT-analogous scanning mode was proposed to cost-effectively increase the detection data. To evaluate the feasibility of the system, a series of assessments were conducted. The results demonstrate that the system can obtain high linearity, stability and negligible inter-wavelength crosstalk. The preliminary phantom experiments show the absorption coefficient is able to be successfully reconstructed, indicating that the system is one of the ideal platforms for optical breast tumor detection.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs - Space-Weather HMI Active Region Patches

NASA Astrophysics Data System (ADS)

Bobra, M. G.; Sun, X.; Hoeksema, J. T.; Turmon, M.; Liu, Y.; Hayashi, K.; Barnes, G.; Leka, K. D.

2014-09-01

A new data product from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) called Space-weather HMI Active Region Patches ( SHARPs) is now available. SDO/HMI is the first space-based instrument to map the full-disk photospheric vector magnetic field with high cadence and continuity. The SHARP data series provide maps in patches that encompass automatically tracked magnetic concentrations for their entire lifetime; map quantities include the photospheric vector magnetic field and its uncertainty, along with Doppler velocity, continuum intensity, and line-of-sight magnetic field. Furthermore, keywords in the SHARP data series provide several parameters that concisely characterize the magnetic-field distribution and its deviation from a potential-field configuration. These indices may be useful for active-region event forecasting and for identifying regions of interest. The indices are calculated per patch and are available on a twelve-minute cadence. Quick-look data are available within approximately three hours of observation; definitive science products are produced approximately five weeks later. SHARP data are available at jsoc.stanford.edu and maps are available in either of two different coordinate systems. This article describes the SHARP data products and presents examples of SHARP data and parameters.

A detail enhancement and dynamic range adjustment algorithm for high dynamic range images

NASA Astrophysics Data System (ADS)

Xu, Bo; Wang, Huachuang; Liang, Mingtao; Yu, Cong; Hu, Jinlong; Cheng, Hua

2014-08-01

Although high dynamic range (HDR) images contain large amounts of information, they have weak texture and low contrast. What's more, these images are difficult to be reproduced on low dynamic range displaying mediums. If much more information is to be acquired when these images are displayed on PCs, some specific transforms, such as compressing the dynamic range, enhancing the portions of little difference in original contrast and highlighting the texture details on the premise of keeping the parts of large contrast, are needed. To this ends, a multi-scale guided filter enhancement algorithm which derives from the single-scale guided filter based on the analysis of non-physical model is proposed in this paper. Firstly, this algorithm decomposes the original HDR images into base image and detail images of different scales, and then it adaptively selects a transform function which acts on the enhanced detail images and original images. By comparing the treatment effects of HDR images and low dynamic range (LDR) images of different scene features, it proves that this algorithm, on the basis of maintaining the hierarchy and texture details of images, not only improves the contrast and enhances the details of images, but also adjusts the dynamic range well. Thus, it is much suitable for human observation or analytical processing of machines.

PMG: online generation of high-quality molecular pictures and storyboarded animations

PubMed Central

Autin, Ludovic; Tufféry, Pierre

2007-01-01

The Protein Movie Generator (PMG) is an online service able to generate high-quality pictures and animations for which one can then define simple storyboards. The PMG can therefore efficiently illustrate concepts such as molecular motion or formation/dissociation of complexes. Emphasis is put on the simplicity of animation generation. Rendering is achieved using Dino coupled to POV-Ray. In order to produce highly informative images, the PMG includes capabilities of using different molecular representations at the same time to highlight particular molecular features. Moreover, sophisticated rendering concepts including scene definition, as well as modeling light and materials are available. The PMG accepts Protein Data Bank (PDB) files as input, which may include series of models or molecular dynamics trajectories and produces images or movies under various formats. PMG can be accessed at http://bioserv.rpbs.jussieu.fr/PMG.html. PMID:17478496

Development of Purine-Derived 18F-Labeled Pro-drug Tracers for Imaging of MRP1 Activity with PET

PubMed Central

2014-01-01

Multidrug resistance-associated protein 1 (MRP1) is a drug efflux transporter that has been implicated in the pathology of several neurological diseases and is associated with development of multidrug resistance. To enable measurement of MRP1 function in the living brain, a series of 6-halopurines decorated with fluorinated side chains have been synthesized and evaluated as putative pro-drug tracers. The tracers were designed to undergo conjugation with glutathione within the brain and hence form the corresponding MRP1 substrate tracers in situ. 6-Bromo-7-(2-[18F]fluoroethyl)purine showed good brain uptake and rapid metabolic conversion. Dynamic PET imaging demonstrated a marked difference in brain clearance rates between wild-type and mrp1 knockout mice, suggesting that the tracer can allow noninvasive assessment of MRP1 activity in vivo. PMID:24456310

Burst mode composite photography for dynamic physics demonstrations

NASA Astrophysics Data System (ADS)

Lincoln, James

2018-05-01

I am writing this article to raise awareness of burst mode photography as a fun and engaging way for teachers and students to experience physics demonstration activities. In the context of digital photography, "burst mode" means taking multiple photographs per second, and this is a feature that now comes standard on most digital cameras—including the iPhone. Sometimes the images are composited to imply motion from a series of still pictures. By analyzing the time between the photos, students can measure rates of velocity and acceleration of moving objects. Some of these composite photographs have already shown up in the AAPT High School Physics Photo Contest. In this article I discuss some ideas for using burst mode photography in the iPhone and provide a discussion of how to edit these photographs to create a composite image. I also compare the capabilities of the iPhone and GoPro cameras in creating these photographic composites.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Single-Molecule Imaging of RNA Splicing in Live Cells.

PubMed

Rino, José; Martin, Robert M; Carvalho, Célia; de Jesus, Ana C; Carmo-Fonseca, Maria

2015-01-01

Expression of genetic information in eukaryotes involves a series of interconnected processes that ultimately determine the quality and amount of proteins in the cell. Many individual steps in gene expression are kinetically coupled, but tools are lacking to determine how temporal relationships between chemical reactions contribute to the output of the final gene product. Here, we describe a strategy that permits direct measurements of intron dynamics in single pre-mRNA molecules in live cells. This approach reveals that splicing can occur much faster than previously proposed and opens new avenues for studying how kinetic mechanisms impact on RNA biogenesis. © 2015 Elsevier Inc. All rights reserved.

Synchrotron-based X-ray computed tomography during compression loading of cellular materials

DOE PAGES

Cordes, Nikolaus L.; Henderson, Kevin; Stannard, Tyler; ...

2015-04-29

Three-dimensional X-ray computed tomography (CT) of in situ dynamic processes provides internal snapshot images as a function of time. Tomograms are mathematically reconstructed from a series of radiographs taken in rapid succession as the specimen is rotated in small angular increments. In addition to spatial resolution, temporal resolution is important. Thus temporal resolution indicates how close together in time two distinct tomograms can be acquired. Tomograms taken in rapid succession allow detailed analyses of internal processes that cannot be obtained by other means. This article describes the state-of-the-art for such measurements acquired using synchrotron radiation as the X-ray source.

Enhanced visible and near-infrared capabilities of the JET mirror-linked divertor spectroscopy system

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

Lomanowski, B. A., E-mail: b.a.lomanowski@durham.ac.uk; Sharples, R. M.; Meigs, A. G.

2014-11-15

The mirror-linked divertor spectroscopy diagnostic on JET has been upgraded with a new visible and near-infrared grating and filtered spectroscopy system. New capabilities include extended near-infrared coverage up to 1875 nm, capturing the hydrogen Paschen series, as well as a 2 kHz frame rate filtered imaging camera system for fast measurements of impurity (Be II) and deuterium Dα, Dβ, Dγ line emission in the outer divertor. The expanded system provides unique capabilities for studying spatially resolved divertor plasma dynamics at near-ELM resolved timescales as well as a test bed for feasibility assessment of near-infrared spectroscopy.

High Resolution Spectroscopy and Dynamics: from Jet Cooled Radicals to Gas-Liquid Interfaces

NASA Astrophysics Data System (ADS)

Sharp-Williams, E.; Roberts, M. A.; Roscioli, J. R.; Gisler, A. W.; Ziemkiewicz, M.; Nesbitt, D. J.; Dong, F.; Perkins, B. G., Jr.

2010-06-01

This talk will attempt to reflect recent work in our group involving two quite different but complementary applications of high resolution molecular spectroscopy for detailed study of intramolecular as well as intermolecular dynamics in small molecules. The first is based on direct infrared absorption spectroscopy in a 100 KHz slit supersonic discharge, which provides a remarkably versatile and yet highly sensitive probe for study of important chemical transients such as open shell combustion species and molecular ions under jet cooled (10-20K), sub-Doppler conditions. For this talk will focus on gas phase spectroscopic results for a series of unsaturated hydrocarbon radical species (ethynyl, vinyl, and phenyl) reputed to be critical intermediates in soot formation. Secondly, we will discuss recent applications of high resolution IR and velocity map imaging spectroscopy toward quantum state resolved collision dynamics of jet cooled molecules from gas-room temperature ionic liquid (RTIL) and gas-self assembled monolayer (SAM) interfaces. Time permitting, we will also present new results on hyperthermal scattering of jet cooled NO radical from liquid Ga, which offer a novel window into non-adiabatic energy transfer and electron-hole pair dynamics at the gas-molten metal interface.

Time-series photographs of the sea floor in western Massachusetts Bay: June 1997 to June 1998

USGS Publications Warehouse

Butman, Bradford; Alexander, P. Soupy; Bothner, Michael H.

2004-01-01

This report presents time-series photographs of the sea floor obtained from an instrumented tripod deployed at Site A in western Massachusetts Bay (42° 22.6' N., 70? 47.0' W., 30 m water depth, from June 1997 through June 1998. Site A is approximately 1 km south of an ocean outfall that began discharging treated sewage effluent from the Boston metropolitan area into Massachusetts Bay in September 2000. Time-series photographs and oceanographic observations were initiated at Site A in December 1989 and are anticipated to continue to September 2005. This is the first in a series of reports planned to summarize and distribute these images in digital form. The objective of these reports is to enable easy and rapid viewing of the photographs and to provide a medium-resolution digital archive. The images, obtained every 4 hours, are presented as a movie (in .avi format, which may be viewed using an image viewer such as QuickTime or Windows Media Player) and as individual images (.tif format). The images provide time-series observations of changes of the sea floor and near-bottom water properties.

Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems

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

McCullough, Michael; Iu, Herbert Ho-Ching; Small, Michael

2015-05-15

We investigate a generalised version of the recently proposed ordinal partition time series to network transformation algorithm. First, we introduce a fixed time lag for the elements of each partition that is selected using techniques from traditional time delay embedding. The resulting partitions define regions in the embedding phase space that are mapped to nodes in the network space. Edges are allocated between nodes based on temporal succession thus creating a Markov chain representation of the time series. We then apply this new transformation algorithm to time series generated by the Rössler system and find that periodic dynamics translate tomore » ring structures whereas chaotic time series translate to band or tube-like structures—thereby indicating that our algorithm generates networks whose structure is sensitive to system dynamics. Furthermore, we demonstrate that simple network measures including the mean out degree and variance of out degrees can track changes in the dynamical behaviour in a manner comparable to the largest Lyapunov exponent. We also apply the same analysis to experimental time series generated by a diode resonator circuit and show that the network size, mean shortest path length, and network diameter are highly sensitive to the interior crisis captured in this particular data set.« less

Experimental Observations of Multiscale Dynamics of Viscous Fluid Behavior: Implications in Volcanic Systems

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, A.; Spina, L.; Scheu, B.; Dingwell, D. B.

2015-12-01

We have investigated the dynamics of Newtonian fluids with viscosities (10-1000 Pa s; corresponding to mafic to intermediate silicate melts) during slow decompression, in a Plexiglas shock tube. As an analogue fluid we used silicon oil saturated with Argon gas for 72 hours. Slow decompression, dropping from 10 MPa to ambient pressure, acts as the excitation mechanism, initiating several processes with their own distinct timescales. The evolution of this multi-timescale phenomenon generates complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit. Correlation analysis of these time series with the associated high-speed imaging enables characterization of distinct phases of the dynamics of these viscous fluids and the extraction of the time and the frequency characteristics of the individual processes. We have identified fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution in space. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the system. Our observations point to the great potential of this experimental approach in the understanding of volcanic processes and volcanic seismicity.

Assessing the kidney function parameters glomerular filtration rate and effective renal plasma flow with dynamic FDG-PET/MRI in healthy subjects.

PubMed

Geist, Barbara K; Baltzer, Pascal; Fueger, Barbara; Hamboeck, Martina; Nakuz, Thomas; Papp, Laszlo; Rasul, Sazan; Sundar, Lalith Kumar Shiyam; Hacker, Marcus; Staudenherz, Anton

2018-05-09

A method was developed to assess the kidney parameters glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) from 2-deoxy-2-[ 18 F]fluoro-D-glucose (FDG) concentration behavior in kidneys, measured with positron emission tomography (PET) scans. Twenty-four healthy adult subjects prospectively underwent dynamic simultaneous PET/magnetic resonance imaging (MRI) examination. Time activity curves (TACs) were obtained from the dynamic PET series, with the guidance of MR information. Patlak analysis was performed to determine the GFR, and based on integrals, ERPF was calculated. Results were compared to intra-individually obtained reference values determined from venous blood samples. Total kidney GFR and ERPF as estimated by dynamic PET/MRI were highly correlated to their reference values (r = 0.88/p < 0.0001 and r = 0.82/p < 0.0001, respectively) with no significant difference between their means. The study is a proof of concept that GFR and ERPF can be assessed with dynamic FDG PET/MRI scans in healthy kidneys. This has advantages for patients getting a routine scan, where additional examinations for kidney function estimation could be avoided. Further studies are required for transferring this PET/MRI method to PET/CT applications.

Digital image processing: a primer for JVIR authors and readers: Part 3: Digital image editing.

PubMed

LaBerge, Jeanne M; Andriole, Katherine P

2003-12-01

This is the final installment of a three-part series on digital image processing intended to prepare authors for online submission of manuscripts. In the first two articles of the series, the fundamentals of digital image architecture were reviewed and methods of importing images to the computer desktop were described. In this article, techniques are presented for editing images in preparation for online submission. A step-by-step guide to basic editing with use of Adobe Photoshop is provided and the ethical implications of this activity are explored.

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Dynamic Resting-State Functional Connectivity in Major Depression.

PubMed

Kaiser, Roselinde H; Whitfield-Gabrieli, Susan; Dillon, Daniel G; Goer, Franziska; Beltzer, Miranda; Minkel, Jared; Smoski, Moria; Dichter, Gabriel; Pizzagalli, Diego A

2016-06-01

Major depressive disorder (MDD) is characterized by abnormal resting-state functional connectivity (RSFC), especially in medial prefrontal cortical (MPFC) regions of the default network. However, prior research in MDD has not examined dynamic changes in functional connectivity as networks form, interact, and dissolve over time. We compared unmedicated individuals with MDD (n=100) to control participants (n=109) on dynamic RSFC (operationalized as SD in RSFC over a series of sliding windows) of an MPFC seed region during a resting-state functional magnetic resonance imaging scan. Among participants with MDD, we also investigated the relationship between symptom severity and RSFC. Secondary analyses probed the association between dynamic RSFC and rumination. Results showed that individuals with MDD were characterized by decreased dynamic (less variable) RSFC between MPFC and regions of parahippocampal gyrus within the default network, a pattern related to sustained positive connectivity between these regions across sliding windows. In contrast, the MDD group exhibited increased dynamic (more variable) RSFC between MPFC and regions of insula, and higher severity of depression was related to increased dynamic RSFC between MPFC and dorsolateral prefrontal cortex. These patterns of highly variable RSFC were related to greater frequency of strong positive and negative correlations in activity across sliding windows. Secondary analyses indicated that increased dynamic RSFC between MPFC and insula was related to higher levels of recent rumination. These findings provide initial evidence that depression, and ruminative thinking in depression, are related to abnormal patterns of fluctuating communication among brain systems involved in regulating attention and self-referential thinking.

An improved image alignment procedure for high-resolution transmission electron microscopy.

PubMed

Lin, Fang; Liu, Yan; Zhong, Xiaoyan; Chen, Jianghua

2010-06-01

Image alignment is essential for image processing methods such as through-focus exit-wavefunction reconstruction and image averaging in high-resolution transmission electron microscopy. Relative image displacements exist in any experimentally recorded image series due to the specimen drifts and image shifts, hence image alignment for correcting the image displacements has to be done prior to any further image processing. The image displacement between two successive images is determined by the correlation function of the two relatively shifted images. Here it is shown that more accurate image alignment can be achieved by using an appropriate aperture to filter the high-frequency components of the images being aligned, especially for a crystalline specimen with little non-periodic information. For the image series of crystalline specimens with little amorphous, the radius of the filter aperture should be as small as possible, so long as it covers the innermost lattice reflections. Testing with an experimental through-focus series of Si[110] images, the accuracies of image alignment with different correlation functions are compared with respect to the error functions in through-focus exit-wavefunction reconstruction based on the maximum-likelihood method. Testing with image averaging over noisy experimental images from graphene and carbon-nanotube samples, clear and sharp crystal lattice fringes are recovered after applying optimal image alignment. Copyright 2010 Elsevier Ltd. All rights reserved.

Retinex Preprocessing for Improved Multi-Spectral Image Classification

NASA Technical Reports Server (NTRS)

Thompson, B.; Rahman, Z.; Park, S.

2000-01-01

The goal of multi-image classification is to identify and label "similar regions" within a scene. The ability to correctly classify a remotely sensed multi-image of a scene is affected by the ability of the classification process to adequately compensate for the effects of atmospheric variations and sensor anomalies. Better classification may be obtained if the multi-image is preprocessed before classification, so as to reduce the adverse effects of image formation. In this paper, we discuss the overall impact on multi-spectral image classification when the retinex image enhancement algorithm is used to preprocess multi-spectral images. The retinex is a multi-purpose image enhancement algorithm that performs dynamic range compression, reduces the dependence on lighting conditions, and generally enhances apparent spatial resolution. The retinex has been successfully applied to the enhancement of many different types of grayscale and color images. We show in this paper that retinex preprocessing improves the spatial structure of multi-spectral images and thus provides better within-class variations than would otherwise be obtained without the preprocessing. For a series of multi-spectral images obtained with diffuse and direct lighting, we show that without retinex preprocessing the class spectral signatures vary substantially with the lighting conditions. Whereas multi-dimensional clustering without preprocessing produced one-class homogeneous regions, the classification on the preprocessed images produced multi-class non-homogeneous regions. This lack of homogeneity is explained by the interaction between different agronomic treatments applied to the regions: the preprocessed images are closer to ground truth. The principle advantage that the retinex offers is that for different lighting conditions classifications derived from the retinex preprocessed images look remarkably "similar", and thus more consistent, whereas classifications derived from the original images, without preprocessing, are much less similar.

Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations

PubMed Central

Almog, Assaf; Besamusca, Ferry; MacMahon, Mel; Garlaschelli, Diego

2015-01-01

The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. The organization is determined by “communities” of units whose dynamics, represented by time series of activity, is more strongly correlated internally than with the rest of the system. Recent studies have shown that the binary projections of various financial and neural time series exhibit nontrivial dynamical features that resemble those of the original data. This implies that a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. Here, we explore whether the binary signatures of multiple time series can replicate the same complex community organization of the financial market, as the original weighted time series. We adopt a method that has been specifically designed to detect communities from cross-correlation matrices of time series data. Our analysis shows that the simpler binary representation leads to a community structure that is almost identical with that obtained using the full weighted representation. These results confirm that binary projections of financial time series contain significant structural information. PMID:26226226

IDENTIFICATION OF REGIME SHIFTS IN TIME SERIES USING NEIGHBORHOOD STATISTICS

EPA Science Inventory

The identification of alternative dynamic regimes in ecological systems requires several lines of evidence. Previous work on time series analysis of dynamic regimes includes mainly model-fitting methods. We introduce two methods that do not use models. These approaches use state-...

37 CFR 150.1 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Property and Director of the United States Patent and Trademark Office (see § 1.9(j)). (b) Foreign... Commerce under 17 U.S.C. 914. (d) Mask work means a series of related images, however fixed or encoded— (1... series the relation of the images to one another is that each image has the pattern of the surface of one...

37 CFR 150.1 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Property and Director of the United States Patent and Trademark Office (see § 1.9(j)). (b) Foreign... Commerce under 17 U.S.C. 914. (d) Mask work means a series of related images, however fixed or encoded— (1... series the relation of the images to one another is that each image has the pattern of the surface of one...

37 CFR 150.1 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Property and Director of the United States Patent and Trademark Office (see § 1.9(j)). (b) Foreign... Commerce under 17 U.S.C. 914. (d) Mask work means a series of related images, however fixed or encoded— (1... series the relation of the images to one another is that each image has the pattern of the surface of one...

37 CFR 150.1 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Property and Director of the United States Patent and Trademark Office (see § 1.9(j)). (b) Foreign... Commerce under 17 U.S.C. 914. (d) Mask work means a series of related images, however fixed or encoded— (1... series the relation of the images to one another is that each image has the pattern of the surface of one...

37 CFR 150.1 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Property and Director of the United States Patent and Trademark Office (see § 1.9(j)). (b) Foreign... Commerce under 17 U.S.C. 914. (d) Mask work means a series of related images, however fixed or encoded— (1... series the relation of the images to one another is that each image has the pattern of the surface of one...

Max CAPR: high-resolution 3D contrast-enhanced MR angiography with acquisition times under 5 seconds.

PubMed

Haider, Clifton R; Borisch, Eric A; Glockner, James F; Mostardi, Petrice M; Rossman, Phillip J; Young, Phillip M; Riederer, Stephen J

2010-10-01

High temporal and spatial resolution is desired in imaging of vascular abnormalities having short arterial-to-venous transit times. Methods that exploit temporal correlation to reduce the observed frame time demonstrate temporal blurring, obfuscating bolus dynamics. Previously, a Cartesian acquisition with projection reconstruction-like (CAPR) sampling method has been demonstrated for three-dimensional contrast-enhanced angiographic imaging of the lower legs using two-dimensional sensitivity-encoding acceleration and partial Fourier acceleration, providing 1mm isotropic resolution of the calves, with 4.9-sec frame time and 17.6-sec temporal footprint. In this work, the CAPR acquisition is further undersampled to provide a net acceleration approaching 40 by eliminating all view sharing. The tradeoff of frame time and temporal footprint in view sharing is presented and characterized in phantom experiments. It is shown that the resultant 4.9-sec acquisition time, three-dimensional images sets have sufficient spatial and temporal resolution to clearly portray arterial and venous phases of contrast passage. It is further hypothesized that these short temporal footprint sequences provide diagnostic quality images. This is tested and shown in a series of nine contrast-enhanced MR angiography patient studies performed with the new method.

Experimental evaluation of dual multiple aperture devices for fluence field modulated x-ray computed tomography

NASA Astrophysics Data System (ADS)

Mathews, A. J.; Gang, G.; Levinson, R.; Zbijewski, W.; Kawamoto, S.; Siewerdsen, J. H.; Stayman, J. W.

2017-03-01

Acquisition of CT images with comparable diagnostic power can potentially be achieved with lower radiation exposure than the current standard of care through the adoption of hardware-based fluence-field modulation (e.g. dynamic bowtie filters). While modern CT scanners employ elements such as static bowtie filters and tube-current modulation, such solutions are limited in the fluence patterns that they can achieve, and thus are limited in their ability to adapt to broad classes of patient morphology. Fluence-field modulation also enables new applications such as region-of-interest imaging, task specific imaging, reducing measurement noise or improving image quality. The work presented in this paper leverages a novel fluence modulation strategy that uses "Multiple Aperture Devices" (MADs) which are, in essence, binary filters, blocking or passing x-rays on a fine scale. Utilizing two MAD devices in series provides the capability of generating a large number of fluence patterns via small relative motions between the MAD filters. We present the first experimental evaluation of fluence-field modulation using a dual-MAD system, and demonstrate the efficacy of this technique with a characterization of achievable fluence patterns and an investigation of experimental projection data.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

Nuclear Medicine at Berkeley Lab: From Pioneering Beginnings to Today (LBNL Summer Lecture Series)

ScienceCinema

Budinger, Thomas [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Dept. of Nuclear Medicine & Functional Imaging

2018-01-23

Summer Lecture Series 2006: Thomas Budinger, head of Berkeley Lab's Center for Functional Imaging, discusses Berkeley Lab's rich history pioneering the field of nuclear medicine, from radioisotopes to medical imaging.

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Treesearch

Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

2010-01-01

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform

NASA Astrophysics Data System (ADS)

Chen, Bangqian; Xiao, Xiangming; Li, Xiangping; Pan, Lianghao; Doughty, Russell; Ma, Jun; Dong, Jinwei; Qin, Yuanwei; Zhao, Bin; Wu, Zhixiang; Sun, Rui; Lan, Guoyu; Xie, Guishui; Clinton, Nicholas; Giri, Chandra

2017-09-01

Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer's accuracy greater than 95% when validated with ground reference data. In 2015, China's mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China.

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

Dynamic Shear Deformation and Failure of Ti-6Al-4V and Ti-5Al-5Mo-5V-1Cr-1Fe Alloys

PubMed Central

Chen, Pengwan

2018-01-01

To study the dynamic shear deformation and failure properties of Ti-6Al-4V (Ti-64) alloy and Ti-5Al-5Mo-5V-1Cr-1Fe (Ti-55511) alloy, a series of forced shear tests on flat hat shaped (FHS) specimens for the two investigated materials was performed using a split Hopkinson pressure bar setup. The evolution of shear deformation was monitored by an ultra-high-speed camera (Kirana-05M). Localized shear band is induced in the two investigated materials under forced shear tests. Our results indicate that severe strain localization (adiabatic shear) is accompanied by a loss in the load carrying capacity, i.e., by a sudden drop in loading. Three distinct stages can be identified using a digital image correlation technique for accurate shear strain measurement. The microstructural analysis reveals that the dynamic failure mechanisms for Ti-64 and Ti-55511 alloys within the shear band are of a cohesive and adhesive nature, respectively. PMID:29303988

Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands

NASA Astrophysics Data System (ADS)

Hidayat, Hidayat; Teuling, Adriaan J.; Vermeulen, Bart; Taufik, Muh; Kastner, Karl; Geertsema, Tjitske J.; Bol, Dinja C. C.; Hoekman, Dirk H.; Sri Haryani, Gadis; Van Lanen, Henny A. J.; Delinom, Robert M.; Dijksma, Roel; Anshari, Gusti Z.; Ningsih, Nining S.; Uijlenhoet, Remko; Hoitink, Antonius J. F.

2017-05-01

Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013-2015 and in the Mahakam over the period 2008-2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998-2015 to analyse the distribution of rainfall and the influence of El-Niño - Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.

The new Seafloor Observatory (OBSEA) for remote and long-term coastal ecosystem monitoring.

PubMed

Aguzzi, Jacopo; Mànuel, Antoni; Condal, Fernando; Guillén, Jorge; Nogueras, Marc; del Rio, Joaquin; Costa, Corrado; Menesatti, Paolo; Puig, Pere; Sardà, Francesc; Toma, Daniel; Palanques, Albert

2011-01-01

A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics.

The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring

PubMed Central

Aguzzi, Jacopo; Mànuel, Antoni; Condal, Fernando; Guillén, Jorge; Nogueras, Marc; del Rio, Joaquin; Costa, Corrado; Menesatti, Paolo; Puig, Pere; Sardà, Francesc; Toma, Daniel; Palanques, Albert

2011-01-01

A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics. PMID:22163931

Counter-streaming flows in a giant quiet-Sun filament observed in the extreme ultraviolet

NASA Astrophysics Data System (ADS)

Diercke, A.; Kuckein, C.; Verma, M.; Denker, C.

2018-03-01

Aim. The giant solar filament was visible on the solar surface from 2011 November 8-23. Multiwavelength data from the Solar Dynamics Observatory (SDO) were used to examine counter-streaming flows within the spine of the filament. Methods: We use data from two SDO instruments, the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI), covering the whole filament, which stretched over more than half a solar diameter. Hα images from the Kanzelhöhe Solar Observatory (KSO) provide context information of where the spine of the filament is defined and the barbs are located. We apply local correlation tracking (LCT) to a two-hour time series on 2011 November 16 of the AIA images to derive horizontal flow velocities of the filament. To enhance the contrast of the AIA images, noise adaptive fuzzy equalization (NAFE) is employed, which allows us to identify and quantify counter-streaming flows in the filament. We observe the same cool filament plasma in absorption in both Hα and EUV images. Hence, the counter-streaming flows are directly related to this filament material in the spine. In addition, we use directional flow maps to highlight the counter-streaming flows. Results: We detect counter-streaming flows in the filament, which are visible in the time-lapse movies in all four examined AIA wavelength bands (λ171 Å, λ193 Å, λ304 Å, and λ211 Å). In the time-lapse movies we see that these persistent flows lasted for at least two hours, although they became less prominent towards the end of the time series. Furthermore, by applying LCT to the images we clearly determine counter-streaming flows in time series of λ171 Å and λ193 Å images. In the λ304 Å wavelength band, we only see minor indications for counter-streaming flows with LCT, while in the λ211 Å wavelength band the counter-streaming flows are not detectable with this method. The diverse morphology of the filament in Hα and EUV images is caused by different absorption processes, i.e., spectral line absorption and absorption by hydrogen and helium continua, respectively. The horizontal flows reach mean flow speeds of about 0.5 km s-1 for all wavelength bands. The highest horizontal flow speeds are identified in the λ171 Å band with flow speeds of up to 2.5 km s-1. The results are averaged over a time series of 90 minutes. Because the LCT sampling window has finite width, a spatial degradation cannot be avoided leading to lower estimates of the flow velocities as compared to feature tracking or Doppler measurements. The counter-streaming flows cover about 15-20% of the whole area of the EUV filament channel and are located in the central part of the spine. Conclusions: Compared to the ground-based observations, the absence of seeing effects in AIA observations reveal counter-streaming flows in the filament even with a moderate image scale of 0. ''6 pixel-1. Using a contrast enhancement technique, these flows can be detected and quantified with LCT in different wavelengths. We confirm the omnipresence of counter-streaming flows also in giant quiet-Sun filaments. A movie associated to Fig. 6 is available at http://https://www.aanda.org

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

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

PubMed

Drobnitzky, Matthias; Klose, Uwe

2017-03-01

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

Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping.

PubMed

Sadeghi-Tehran, Pouria; Virlet, Nicolas; Sabermanesh, Kasra; Hawkesford, Malcolm J

2017-01-01

Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments. In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1) comparison with ground-truth images, (2) variation along a day with changes in ambient illumination, (3) comparison with manual measurements and (4) an estimation of performance along the full life cycle of a wheat canopy. The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.

Catalog of microscopic organisms of the Everglades, Part 1—The cyanobacteria

USGS Publications Warehouse

Rosen, Barry H.; Mareš, Jan

2016-07-27

The microscopic organisms of the Everglades include numerous prokaryotic organisms, including the eubacteria, such as the cyanobacteria and non-photosynthetic bacteria, as well as several eukaryotic algae and protozoa that form the base of the food web. This report is part 1 in a series of reports that describe microscopic organisms encountered during the examination of several hundred samples collected in the southern Everglades. Part 1 describes the cyanobacteria and includes a suite of images and the most current taxonomic treatment of each taxon. The majority of the images are of live organisms, allowing their true color to be represented. A number of potential new species are illustrated; however, corroborating evidence from a genetic analysis of the morphological characteristics is needed to confirm these designations as new species. Part 1 also includes images of eubacteria that resemble cyanobacteria. Additional parts of the report on microscopic organisms of the Everglades are currently underway, such as the green algae and diatoms. The report also serves as the basis for a taxonomic image database that will provide a digital record of the Everglades microscopic flora and fauna. It is anticipated that these images will facilitate current and future ecological studies on the Everglades, such as understanding food-web dynamics, sediment formation and accumulation, the effects of nutrients and flow, and climate change.

Simulation of Wake Vortex Radiometric Detection via Jet Exhaust Proxy

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.

2015-01-01

This paper describes an analysis of the potential of an airborne hyperspectral imaging IR instrument to infer wake vortices via turbine jet exhaust as a proxy. The goal was to determine the requirements for an imaging spectrometer or radiometer to effectively detect the exhaust plume, and by inference, the location of the wake vortices. The effort examines the gas spectroscopy of the various major constituents of turbine jet exhaust and their contributions to the modeled detectable radiance. Initially, a theoretical analysis of wake vortex proxy detection by thermal radiation was realized in a series of simulations. The first stage used the SLAB plume model to simulate turbine jet exhaust plume characteristics, including exhaust gas transport dynamics and concentrations. The second stage used these plume characteristics as input to the Line By Line Radiative Transfer Model (LBLRTM) to simulate responses from both an imaging IR hyperspectral spectrometer or radiometer. These numerical simulations generated thermal imagery that was compared with previously reported wake vortex temperature data. This research is a continuation of an effort to specify the requirements for an imaging IR spectrometer or radiometer to make wake vortex measurements. Results of the two-stage simulation will be reported, including instrument specifications for wake vortex thermal detection. These results will be compared with previously reported results for IR imaging spectrometer performance.

Functional magnetic resonance imaging phase synchronization as a measure of dynamic functional connectivity.

PubMed

Glerean, Enrico; Salmi, Juha; Lahnakoski, Juha M; Jääskeläinen, Iiro P; Sams, Mikko

2012-01-01

Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on an fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04-0.07 Hz) was used in the PS analysis to avoid artifactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A MATLAB toolbox FUNPSY ( http://becs.aalto.fi/bml/software.html ) is openly available for using these metrics in fMRI data 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.

A complex systems analysis of stick-slip dynamics of a laboratory fault

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

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Dynamical Analysis and Visualization of Tornadoes Time Series

PubMed Central

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns. PMID:25790281

Dynamical analysis and visualization of tornadoes time series.

PubMed

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

SU-E-J-273: Skin Temperature Recovery Rate as a Potential Predictor for Radiation-Induced Skin Reactions

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

Biswal, N C; Wu, Z; Chu, J

Purpose: To assess the potential of dynamic infrared imaging to evaluate early skin reactions during radiation therapy in cancer patients. Methods: Thermal images were captured by our home-built system consisting of two flash lamps and an infrared (IR) camera. The surface temperature of the skin was first raised by ∼ 6 °C from ∼1 ms short flashes; the camera then captured a series of IR images for 10 seconds. For each image series, a basal temperature was recorded for 0.5 seconds before flash was triggered. The temperature gradients (ε) were calculated between a reference point (immediately after the flash) andmore » at a time point of 2sec, 4sec and 9sec after that. A 1.0 cm region of interest (ROI) on the skin was drawn; the mean and standard deviations of the ROIs were calculated. The standard ε values for normal human skins were evaluated by imaging 3 healthy subjects with different skin colors. All of them were imaged on 3 separate days for consistency checks. Results: The temperature gradient, which is the temperature recovery rate, depends on the thermal properties of underlying tissue, i.e. thermal conductivity. The average ε for three volunteers averaged over 3 measurements were 0.64±0.1, 0.72±0.2 and 0.80±0.3 at 2sec, 4sec and 9sec respectively. The standard deviations were within 1.5%–3.2%. One of the volunteers had a prior small skin burn on the left wrist and the ε values for the burned site were around 9% (at 4sec) and 13% (at 9sec) lower than that from the nearby normal skin. Conclusion: The temperature gradients from the healthy subjects were reproducible within 1.5%–3.2 % and that from a burned skin showed a significant difference (9%–13%) from the normal skin. We have an IRB approved protocol to image head and neck patients scheduled for radiation therapy.« less

Comparison between two models of energy balance in coronal loops

NASA Astrophysics Data System (ADS)

Mac Cormack, C.; López Fuentes, M.; Vásquez, A. M.; Nuevo, F. A.; Frazin, R. A.; Landi, E.

2017-10-01

In this work we compare two models to analyze the energy balance along coronal magnetic loops. For the first stationary model we deduce an expression of the energy balance along the loops expressed in terms of quantities provided by the combination of differential emission measure tomography (DEMT) applied to EUV images time series and potential extrapolations of the coronal magnetic field. The second applied model is a 0D hydrodynamic model that provides the evolution of the average properties of the coronal plasma along the loops, using as input parameters the loop length and the heating rate obtained with the first model. We compare the models for two Carrington rotations (CR) corresponding to different periods of activity: CR 2081, corresponding to a period of minimum activity observed with the Extreme Ultraviolet Imager (EUVI) on board of the Solar Terrestrial Relations Observatory (STEREO), and CR 2099, corresponding to a period of activity increase observed with the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). The results of the models are consistent for both rotations.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Direct fluorescent-dye labeling of α-tubulin in mammalian cells for live cell and superresolution imaging

PubMed Central

Schvartz, Tomer; Aloush, Noa; Goliand, Inna; Segal, Inbar; Nachmias, Dikla; Arbely, Eyal; Elia, Natalie

2017-01-01

Genetic code expansion and bioorthogonal labeling provide for the first time a way for direct, site-specific labeling of proteins with fluorescent-dyes in live cells. Although the small size and superb photophysical parameters of fluorescent-dyes offer unique advantages for high-resolution microscopy, this approach has yet to be embraced as a tool in live cell imaging. Here we evaluated the feasibility of this approach by applying it for α-tubulin labeling. After a series of calibrations, we site-specifically labeled α-tubulin with silicon rhodamine (SiR) in live mammalian cells in an efficient and robust manner. SiR-labeled tubulin successfully incorporated into endogenous microtubules at high density, enabling video recording of microtubule dynamics in interphase and mitotic cells. Applying this labeling approach to structured illumination microscopy resulted in an increase in resolution, highlighting the advantages in using a smaller, brighter tag. Therefore, using our optimized assay, genetic code expansion provides an attractive tool for labeling proteins with a minimal, bright tag in quantitative high-resolution imaging. PMID:28835375

An Experimental Investigation on Bio-inspired Icephobic Coatings for Aircraft Icing Mitigation

NASA Astrophysics Data System (ADS)

Hu, Hui; Li, Haixing; Waldman, Rye

2016-11-01

By leveraging the Icing Research Tunnel available at Iowa State University (ISU-IRT), a series of experimental investigations were conducted to elucidate the underlying physics pertinent to aircraft icing phenomena. A suite of advanced flow diagnostic techniques, which include high-speed photographic imaging, digital image projection (DIP), and infrared (IR) imaging thermometry, were developed and applied to quantify the transient behavior of water droplet impingement, wind-driven surface water runback, unsteady heat transfer and dynamic ice accreting process over the surfaces of airfoil/wing models. The icephobic performance of various bio-inspired superhydrophobic coatings were evaluated quantitatively at different icing conditions. The findings derived from the icing physics studies can be used to improve current icing accretion models for more accurate prediction of ice formation and accretion on aircraft wings and to develop effective anti-/deicing strategies for safer and more efficient operation of aircraft in cold weather. The research work is partially supported by NASA with Grant Number NNX12AC21A and National Science Foundation under Award Numbers of CBET-1064196 and CBET-1435590.

Seabed images from Southern Ocean shelf regions off the northern Antarctic Peninsula and in the southeastern Weddell Sea

NASA Astrophysics Data System (ADS)

Piepenburg, Dieter; Buschmann, Alexander; Driemel, Amelie; Grobe, Hannes; Gutt, Julian; Schumacher, Stefanie; Segelken-Voigt, Alexandra; Sieger, Rainer

2017-07-01

Recent advances in underwater imaging technology allow for the gathering of invaluable scientific information on seafloor ecosystems, such as direct in situ views of seabed habitats and quantitative data on the composition, diversity, abundance, and distribution of epibenthic fauna. The imaging approach has been extensively used within the research project DynAMo (Dynamics of Antarctic Marine Shelf Ecosystems) at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research Bremerhaven (AWI), which aimed to comparatively assess the pace and quality of the dynamics of Southern Ocean benthos. Within this framework, epibenthic spatial distribution patterns have been comparatively investigated in two regions in the Atlantic sector of the Southern Ocean: the shelf areas off the northern tip of the Antarctic Peninsula, representing a region with above-average warming of surface waters and sea-ice reduction, and the shelves of the eastern Weddell Sea as an example of a stable high-Antarctic marine environment that is not (yet) affected by climate change. The AWI Ocean Floor Observation System (OFOS) was used to collect seabed imagery during two cruises of the German research vessel Polarstern, ANT-XXIX/3 (PS81) to the Antarctic Peninsula from January to March 2013 and ANT-XXXI/2 (PS96) to the Weddell Sea from December 2015 to February 2016. Here, we report on the image and data collections gathered during these cruises. During PS81, OFOS was successfully deployed at a total of 31 stations at water depths between 29 and 784 m. At most stations, series of 500 to 530 pictures ( > 15 000 in total, each depicting a seabed area of approximately 3.45 m2 or 2.3 × 1.5 m) were taken along transects approximately 3.7 km in length. During PS96, OFOS was used at a total of 13 stations at water depths between 200 and 754 m, yielding series of 110 to 293 photos (2670 in total) along transects 0.9 to 2.6 km in length. All seabed images taken during the two cruises, including metadata, are available from the data publisher PANGAEA via the two persistent identifiers at https://doi.org/10.1594/PANGAEA.872719 (for PS81) and https://doi.org/10.1594/PANGAEA.862097 (for PS96).

Solar Scientist Confirm Existence of Flux Ropes on the Sun

NASA Image and Video Library

2017-12-08

Caption: This is an image of magnetic loops on the sun, captured by NASA's Solar Dynamics Observatory (SDO). It has been processed to highlight the edges of each loop to make the structure more clear. A series of loops such as this is known as a flux rope, and these lie at the heart of eruptions on the sun known as coronal mass ejections (CMEs.) This is the first time scientists were able to discern the timing of a flux rope's formation. (Blended 131 Angstrom and 171 Angstrom images of July 19, 2012 flare and CME.) Credit: NASA/Goddard Space Flight Center/SDO ---- On July 18, 2012, a fairly small explosion of light burst off the lower right limb of the sun. Such flares often come with an associated eruption of solar material, known as a coronal mass ejection or CME – but this one did not. Something interesting did happen, however. Magnetic field lines in this area of the sun's atmosphere, the corona, began to twist and kink, generating the hottest solar material – a charged gas called plasma – to trace out the newly-formed slinky shape. The plasma glowed brightly in extreme ultraviolet images from the Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory (SDO) and scientists were able to watch for the first time the very formation of something they had long theorized was at the heart of many eruptive events on the sun: a flux rope. Eight hours later, on July 19, the same region flared again. This time the flux rope's connection to the sun was severed, and the magnetic fields escaped into space, dragging billions of tons of solar material along for the ride -- a classic CME. "Seeing this structure was amazing," says Angelos Vourlidas, a solar scientist at the Naval Research Laboratory in Washington, D.C. "It looks exactly like the cartoon sketches theorists have been drawing of flux ropes since the 1970s. It was a series of figure eights lined up to look like a giant slinky on the sun." To read more about this new discovery go to: 1.usa.gov/14UHsTt NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Prospective Evaluation of Prior Image Constrained Compressed Sensing (PICCS) Algorithm in Abdominal CT: A comparison of reduced dose with standard dose imaging

PubMed Central

Lubner, Meghan G.; Pickhardt, Perry J.; Kim, David H.; Tang, Jie; Munoz del Rio, Alejandro; Chen, Guang-Hong

2014-01-01

Purpose To prospectively study CT dose reduction using the “prior image constrained compressed sensing” (PICCS) reconstruction technique. Methods Immediately following routine standard dose (SD) abdominal MDCT, 50 patients (mean age, 57.7 years; mean BMI, 28.8) underwent a second reduced-dose (RD) scan (targeted dose reduction, 70-90%). DLP, CTDIvol and SSDE were compared. Several reconstruction algorithms (FBP, ASIR, and PICCS) were applied to the RD series. SD images with FBP served as reference standard. Two blinded readers evaluated each series for subjective image quality and focal lesion detection. Results Mean DLP, CTDIvol, and SSDE for RD series was 140.3 mGy*cm (median 79.4), 3.7 mGy (median 1.8), and 4.2 mGy (median 2.3) compared with 493.7 mGy*cm (median 345.8), 12.9 mGy (median 7.9 mGy) and 14.6 mGy (median 10.1) for SD series, respectively. Mean effective patient diameter was 30.1 cm (median 30), which translates to a mean SSDE reduction of 72% (p<0.001). RD-PICCS image quality score was 2.8±0.5, improved over the RD-FBP (1.7±0.7) and RD-ASIR(1.9±0.8)(p<0.001), but lower than SD (3.5±0.5)(p<0.001). Readers detected 81% (184/228) of focal lesions on RD-PICCS series, versus 67% (153/228) and 65% (149/228) for RD-FBP and RD-ASIR, respectively. Mean image noise was significantly reduced on RD-PICCS series (13.9 HU) compared with RD-FBP (57.2) and RD-ASIR (44.1) (p<0.001). Conclusion PICCS allows for marked dose reduction at abdominal CT with improved image quality and diagnostic performance over reduced-dose FBP and ASIR. Further study is needed to determine indication-specific dose reduction levels that preserve acceptable diagnostic accuracy relative to higher-dose protocols. PMID:24943136

Local processes and regional patterns - Interpreting a multi-decadal altimetry record of Greenland Ice Sheet changes

NASA Astrophysics Data System (ADS)

Csatho, B. M.; Schenk, A. F.; Babonis, G. S.; van den Broeke, M. R.; Kuipers Munneke, P.; van der Veen, C. J.; Khan, S. A.; Porter, D. F.

2016-12-01

This study presents a new, comprehensive reconstruction of Greenland Ice Sheet elevation changes, generated using the Surface Elevation And Change detection (SERAC) approach. 35-year long elevation-change time series (1980-2015) were obtained at more than 150,000 locations from observations acquired by NASA's airborne and spaceborne laser altimeters (ATM, LVIS, ICESat), PROMICE laser altimetry data (2007-2011) and a DEM covering the ice sheet margin derived from stereo aerial photographs (1970s-80s). After removing the effect of Glacial Isostatic Adjustment (GIA) and the elastic crustal response to changes in ice loading, the time series were partitioned into changes due to surface processes and ice dynamics and then converted into mass change histories. Using gridded products, we examined ice sheet elevation, and mass change patterns, and compared them with other estimates at different scales from individual outlet glaciers through large drainage basins, on to the entire ice sheet. Both the SERAC time series and the grids derived from these time series revealed significant spatial and temporal variations of dynamic mass loss and widespread intermittent thinning, indicating the complexity of ice sheet response to climate forcing. To investigate the regional and local controls of ice dynamics, we examined thickness change time series near outlet glacier grounding lines. Changes on most outlet glaciers were consistent with one or more episodes of dynamic thinning that propagates upstream from the glacier terminus. The spatial pattern of the onset, duration, and termination of these dynamic thinning events suggest a regional control, such as warming ocean and air temperatures. However, the intricate spatiotemporal pattern of dynamic thickness change suggests that, regardless of the forcing responsible for initial glacier acceleration and thinning, the response of individual glaciers is modulated by local conditions. We use statistical methods, such as principal component analysis and multivariate regression to analyze the dynamic ice-thickness change time series derived by SERAC and to investigate the primary forcings and controls on outlet glacier changes.

Reducing uncertainty on satellite image classification through spatiotemporal reasoning

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Nikolakaki, Natassa; Psillakis, Periklis; Miliaresis, George; Xanthakis, Michail

2014-05-01

The natural habitat constantly endures both inherent natural and human-induced influences. Remote sensing has been providing monitoring oriented solutions regarding the natural Earth surface, by offering a series of tools and methodologies which contribute to prudent environmental management. Processing and analysis of multi-temporal satellite images for the observation of the land changes include often classification and change-detection techniques. These error prone procedures are influenced mainly by the distinctive characteristics of the study areas, the remote sensing systems limitations and the image analysis processes. The present study takes advantage of the temporal continuity of multi-temporal classified images, in order to reduce classification uncertainty, based on reasoning rules. More specifically, pixel groups that temporally oscillate between classes are liable to misclassification or indicate problematic areas. On the other hand, constant pixel group growth indicates a pressure prone area. Computational tools are developed in order to disclose the alterations in land use dynamics and offer a spatial reference to the pressures that land use classes endure and impose between them. Moreover, by revealing areas that are susceptible to misclassification, we propose specific target site selection for training during the process of supervised classification. The underlying objective is to contribute to the understanding and analysis of anthropogenic and environmental factors that influence land use changes. The developed algorithms have been tested upon Landsat satellite image time series, depicting the National Park of Ainos in Kefallinia, Greece, where the unique in the world Abies cephalonica grows. Along with the minor changes and pressures indicated in the test area due to harvesting and other human interventions, the developed algorithms successfully captured fire incidents that have been historically confirmed. Overall, the results have shown that the use of the suggested procedures can contribute to the reduction of the classification uncertainty and support the existing knowledge regarding the pressure among land-use changes.

Cartographic Production for the FLaSH Map Study: Generation of Rugosity Grids, 2008

USGS Publications Warehouse

Robbins, Lisa L.; Knorr, Paul O.; Hansen, Mark

2010-01-01

Project Summary This series of raster data is a U.S. Geological Survey (USGS) Data Series release from the Florida Shelf Habitat Project (FLaSH). This disc contains two raster images in Environmental Systems Research Institute, Inc. (ESRI) raster grid format, jpeg image format, and Geo-referenced Tagged Image File Format (GeoTIFF). Data is also provided in non-image ASCII format. Rugosity grids at two resolutions (250 m and 1000 m) were generated for West Florida shelf waters to 250 m using a custom algorithm that follows the methods of Valentine and others (2004). The Methods portion of this document describes the specific steps used to generate the raster images. Rugosity, also referred to as roughness, ruggedness, or the surface-area ratio (Riley and others, 1999; Wilson and others, 2007), is a visual and quantitative measurement of terrain complexity, a common variable in ecological habitat studies. The rugosity of an area can affect biota by influencing habitat, providing shelter from elements, determining the quantity and type of living space, influencing the type and quantity of flora, affecting predator-prey relationships by providing cover and concealment, and, as an expression of vertical relief, can influence local environmental conditions such as temperature and moisture. In the marine environment rugosity can furthermore influence current flow rate and direction, increase the residence time of water in an area through eddying and current deflection, influence local water conditions such as chemistry, turbidity, and temperature, and influence the rate and nature of sedimentary deposition. State-of-the-art computer-mapping techniques and data-processing tools were used to develop shelf-wide raster and vector data layers. Florida Shelf Habitat (FLaSH) Mapping Project (http://coastal.er.usgs.gov/flash) endeavors to locate available data, identify data gaps, synthesize existing information, and expand our understanding of geologic processes in our dynamic coastal and marine systems.

Complexity multiscale asynchrony measure and behavior for interacting financial dynamics

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Niu, Hongli

2016-08-01

A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

Seismic and Aseismic Slip on the Cascadia Megathrust

NASA Astrophysics Data System (ADS)

Michel, S. G. R. M.; Gualandi, A.; Avouac, J. P.

2017-12-01

Our understanding of the dynamics governing aseismic and seismic slip hinges on our ability to image the time evolution of fault slip during and in between earthquakes and transients. Such kinematic descriptions are also pivotal to assess seismic hazard as, on the long term, elastic strain accumulating around a fault should be balanced by elastic strain released by seismic slip and aseismic transients. In this presentation, we will discuss how such kinematic descriptions can be obtained from the analysis and modelling of geodetic time series. We will use inversion methods based on Independent Component Analysis (ICA) decomposition of the time series to extract and model the aseismic slip (afterslip and slow slip events). We will show that this approach is very effective to identify, and filter out, non-tectonic sources of geodetic strain such as the strain due to surface loads, which can be estimated using gravimetric measurements from GRACE, and thermal strain. We will discuss in particular the application to the Cascadia subduction zone.

Observability of nonlinear dynamics: normalized results and a time-series approach.

PubMed

Aguirre, Luis A; Bastos, Saulo B; Alves, Marcela A; Letellier, Christophe

2008-03-01

This paper investigates the observability of nonlinear dynamical systems. Two difficulties associated with previous studies are dealt with. First, a normalized degree observability is defined. This permits the comparison of different systems, which was not generally possible before. Second, a time-series approach is proposed based on omnidirectional nonlinear correlation functions to rank a set of time series of a system in terms of their potential use to reconstruct the original dynamics without requiring the knowledge of the system equations. The two approaches proposed in this paper and a former method were applied to five benchmark systems and an overall agreement of over 92% was found.

Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat.

PubMed

Zhou, Ji; Applegate, Christopher; Alonso, Albor Dobon; Reynolds, Daniel; Orford, Simon; Mackiewicz, Michal; Griffiths, Simon; Penfield, Steven; Pullen, Nick

2017-01-01

Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic. Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat ( Triticum aestivum ) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way. Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases.

Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

PubMed

Adolf, Janne K; Voelkle, Manuel C; Brose, Annette; Schmiedek, Florian

2017-01-01

Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.

Time-series photographs of the sea floor in western Massachusetts Bay: May 1999 to September 1999; May 2000 to September 2000; and October 2001 to February 2002

USGS Publications Warehouse

Butman, Bradford; Alexander, P. Soupy; Bothner, Michael H.

2004-01-01

This report presents time-series photographs of the sea floor obtained from an instrumented tripod deployed at Site A in western Massachusetts Bay (42° 22.6' N., 70° 47.0' W., 30 m water depth) from May 1999 to September 1999; May 2000 to September 2000; and October 2001 to February 2002. Site A is approximately 1 km south of an ocean outfall that began discharging treated sewage effluent from the Boston metropolitan area into Massachusetts Bay in September 2000. Time-series photographs and oceanographic observations were initiated at Site A in December 1989 and are anticipated to continue to September 2005. This one of a series of reports that present these images in digital form. The objective of these reports is to enable easy and rapid viewing of the photographs and to provide a medium-resolution digital archive. The images, obtained every 4 hours, are presented as a movie (in .avi format, which may be viewed using an image viewer such as QuickTime or Windows Media Player) and as individual images (.tif format). The images provide time-series observations of changes of the sea floor and near-bottom water properties.

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on the GOES-R Satellite

NASA Technical Reports Server (NTRS)

Rafal, Marc D.; Clarke, Jared T.; Cholvibul, Ruth W.

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 microseconds) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

Post launch calibration and testing of the Geostationary Lightning Mapper on GOES-R satellite

NASA Astrophysics Data System (ADS)

Rafal, Marc; Clarke, Jared T.; Cholvibul, Ruth W.

2016-05-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 μs) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on GOES-R Satellite

NASA Technical Reports Server (NTRS)

Rafal, Marc; Cholvibul, Ruth; Clarke, Jared

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 s) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.

PubMed

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-31

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma

NASA Astrophysics Data System (ADS)

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-01

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

Application of process tomography in gas-solid fluidised beds in different scales and structures

NASA Astrophysics Data System (ADS)

Wang, H. G.; Che, H. Q.; Ye, J. M.; Tu, Q. Y.; Wu, Z. P.; Yang, W. Q.; Ocone, R.

2018-04-01

Gas-solid fluidised beds are commonly used in particle-related processes, e.g. for coal combustion and gasification in the power industry, and the coating and granulation process in the pharmaceutical industry. Because the operation efficiency depends on the gas-solid flow characteristics, it is necessary to investigate the flow behaviour. This paper is about the application of process tomography, including electrical capacitance tomography (ECT) and microwave tomography (MWT), in multi-scale gas-solid fluidisation processes in the pharmaceutical and power industries. This is the first time that both ECT and MWT have been applied for this purpose in multi-scale and complex structure. To evaluate the sensor design and image reconstruction and to investigate the effects of sensor structure and dimension on the image quality, a normalised sensitivity coefficient is introduced. In the meantime, computational fluid dynamic (CFD) analysis based on a computational particle fluid dynamic (CPFD) model and a two-phase fluid model (TFM) is used. Part of the CPFD-TFM simulation results are compared and validated by experimental results from ECT and/or MWT. By both simulation and experiment, the complex flow hydrodynamic behaviour in different scales is analysed. Time-series capacitance data are analysed both in time and frequency domains to reveal the flow characteristics.

Diagnosing dry eye with dynamic-area high-speed videokeratoscopy

NASA Astrophysics Data System (ADS)

Alonso-Caneiro, David; Turuwhenua, Jason; Iskander, D. Robert; Collins, Michael J.

2011-07-01

Dry eye syndrome is one of the most commonly reported eye health conditions. Dynamic-area high-speed videokeratoscopy (DA-HSV) represents a promising alternative to the most invasive clinical methods for the assessment of the tear film surface quality (TFSQ), particularly as Placido-disk videokeratoscopy is both relatively inexpensive and widely used for corneal topography assessment. Hence, improving this technique to diagnose dry eye is of clinical significance and the aim of this work. First, a novel ray-tracing model is proposed that simulates the formation of a Placido image. This model shows the relationship between tear film topography changes and the obtained Placido image and serves as a benchmark for the assessment of indicators of the ring's regularity. Further, a novel block-feature TFSQ indicator is proposed for detecting dry eye from a series of DA-HSV measurements. The results of the new indicator evaluated on data from a retrospective clinical study, which contains 22 normal and 12 dry eyes, have shown a substantial improvement of the proposed technique to discriminate dry eye from normal tear film subjects. The best discrimination was obtained under suppressed blinking conditions. In conclusion, this work highlights the potential of the DA-HSV as a clinical tool to diagnose dry eye syndrome.

Finite element modeling of hyper-viscoelasticity of peripheral nerve ultrastructures.

PubMed

Chang, Cheng-Tao; Chen, Yu-Hsing; Lin, Chou-Ching K; Ju, Ming-Shaung

2015-07-16

The mechanical characteristics of ultrastructures of rat sciatic nerves were investigated through animal experiments and finite element analyses. A custom-designed dynamic testing apparatus was used to conduct in vitro transverse compression experiments on the nerves. The optical coherence tomography (OCT) was utilized to record the cross-sectional images of nerve during the dynamic testing. Two-dimensional finite element models of the nerves were built based on their OCT images. A hyper-viscoelastic model was employed to describe the elastic and stress relaxation response of each ultrastructure of the nerve, namely the endoneurium, the perineurium and the epineurium. The first-order Ogden model was employed to describe the elasticity of each ultrastructure and a generalized Maxwell model for the relaxation. The inverse finite element analysis was used to estimate the material parameters of the ultrastructures. The results show the instantaneous shear modulus of the ultrastructures in decreasing order is perineurium, endoneurium, and epineurium. The FE model combined with the first-order Ogden model and the second-order Prony series is good enough for describing the compress-and-hold response of the nerve ultrastructures. The integration of OCT and the nonlinear finite element modeling may be applicable to study the viscoelasticity of peripheral nerve down to the ultrastructural level. Copyright © 2015 Elsevier Ltd. All rights reserved.

MIMO model of an interacting series process for Robust MPC via System Identification.

PubMed

Wibowo, Tri Chandra S; Saad, Nordin

2010-07-01

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

A Method for Comparing Multivariate Time Series with Different Dimensions

PubMed Central

Tapinos, Avraam; Mendes, Pedro

2013-01-01

In many situations it is desirable to compare dynamical systems based on their behavior. Similarity of behavior often implies similarity of internal mechanisms or dependency on common extrinsic factors. While there are widely used methods for comparing univariate time series, most dynamical systems are characterized by multivariate time series. Yet, comparison of multivariate time series has been limited to cases where they share a common dimensionality. A semi-metric is a distance function that has the properties of non-negativity, symmetry and reflexivity, but not sub-additivity. Here we develop a semi-metric – SMETS – that can be used for comparing groups of time series that may have different dimensions. To demonstrate its utility, the method is applied to dynamic models of biochemical networks and to portfolios of shares. The former is an example of a case where the dependencies between system variables are known, while in the latter the system is treated (and behaves) as a black box. PMID:23393554

Reconstruction of network topology using status-time-series data

NASA Astrophysics Data System (ADS)

Pandey, Pradumn Kumar; Badarla, Venkataramana

2018-01-01

Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.

Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results

NASA Astrophysics Data System (ADS)

Tanaka, R.; Sanada, S.; Oda, M.; Mitsutaka, M.; Suzuki, K.; Sakuta, K.; Kawashima, H.

2014-03-01

Rib movement during respiration is one of the diagnostic criteria in pulmonary impairments. In general, the rib movement is assessed in fluoroscopy. However, the shadows of lung vessels and bronchi overlapping ribs prevent accurate quantitative analysis of rib movement. Recently, an image-processing technique for separating bones from soft tissue in static chest radiographs, called "bone suppression technique", has been developed. Our purpose in this study was to evaluate the usefulness of dynamic bone images created by the bone suppression technique in quantitative analysis of rib movement. Dynamic chest radiographs of 10 patients were obtained using a dynamic flat-panel detector (FPD). Bone suppression technique based on a massive-training artificial neural network (MTANN) was applied to the dynamic chest images to create bone images. Velocity vectors were measured in local areas on the dynamic bone images, which formed a map. The velocity maps obtained with bone and original images for scoliosis and normal cases were compared to assess the advantages of bone images. With dynamic bone images, we were able to quantify and distinguish movements of ribs from those of other lung structures accurately. Limited rib movements of scoliosis patients appeared as reduced rib velocity vectors. Vector maps in all normal cases exhibited left-right symmetric distributions, whereas those in abnormal cases showed nonuniform distributions. In conclusion, dynamic bone images were useful for accurate quantitative analysis of rib movements: Limited rib movements were indicated as a reduction of rib movement and left-right asymmetric distribution on vector maps. Thus, dynamic bone images can be a new diagnostic tool for quantitative analysis of rib movements without additional radiation dose.

Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

PubMed

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2013-11-01

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. © 2012 Blackwell Verlag GmbH.

Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

NASA Astrophysics Data System (ADS)

Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

2014-05-01

Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross-correlations and Granger causality tests. Results have indicated that both models of GPP have shown a typical dynamic of the Dehesa in a Mediterranean climate in which there are primarily two layers, the arboreal and the herbaceous strata. However, MODIS underestimates the production of the Dehesa while our Site specific model has given more similar values and dynamics to those from the EC tower. Additionally, the analysis of the dynamic relationships has corroborated the strong dynamic link between GPP and available water for plant growth. In conclusion, we have managed to avoid the main sources of underestimation that has MODIS model with the implementation of a Site specific model. Thus, it seems that the different ecological and meteorological parameters used in MODIS model are the principally responsible for this underestimation. Finally, the Granger causality tests indicate that the prediction of GPP can improve if Precipitation or Soil Water is included in the models. References Monteith, J.L., 1972. Solar Radiation and Productivity in Tropical Ecosystems. J. Appl. Ecol. 9, 747-766.

Dynamic integral imaging technology for 3D applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Huang, Yi-Pai; Javidi, Bahram; Martínez-Corral, Manuel; Shieh, Han-Ping D.; Jen, Tai-Hsiang; Hsieh, Po-Yuan; Hassanfiroozi, Amir

2017-05-01

Depth and resolution are always the trade-off in integral imaging technology. With the dynamic adjustable devices, the two factors of integral imaging can be fully compensated with time-multiplexed addressing. Those dynamic devices can be mechanical or electrical driven. In this presentation, we will mainly focused on discussing various Liquid Crystal devices which can change the focal length, scan and shift the image position, or switched in between 2D/3D mode. By using the Liquid Crystal devices, dynamic integral imaging have been successfully applied on 3D Display, capturing, and bio-imaging applications.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging of the Metastatic Potential of Melanoma Xenografts

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

Ovrebo, Kirsti Marie; Ellingsen, Christine; Galappathi, Kanthi

2012-05-01

Purpose: Gadolinium diethylene-triamine penta-acetic acid (Gd-DTPA)-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been suggested as a useful noninvasive method for characterizing the physiologic microenvironment of tumors. In the present study, we investigated whether Gd-DTPA-based DCE-MRI has the potential to provide biomarkers for hypoxia-associated metastatic dissemination. Methods and Materials: C-10 and D-12 melanoma xenografts were used as experimental tumor models. Pimonidazole was used as a hypoxia marker. A total of 60 tumors were imaged, and parametric images of K{sup trans} (volume transfer constant of Gd-DTPA) and v{sub e} (fractional distribution volume of Gd-DTPA) were produced by pharmacokinetic analysis of themore » DCE-MRI series. The host mice were killed immediately after DCE-MRI, and the primary tumor and the lungs were resected and prepared for histologic assessment of the fraction of pimonidazole-positive hypoxic tissue and the presence of lung metastases, respectively. Results: Metastases were found in 11 of 26 mice with C-10 tumors and 14 of 34 mice with D-12 tumors. The primary tumors of the metastatic-positive mice had a greater fraction of hypoxic tissue (p = 0.00031, C-10; p < 0.00001, D-12), a lower median K{sup trans} (p = 0.0011, C-10; p < 0.00001, D-12), and a lower median v{sub e} (p = 0.014, C-10; p = 0.016, D-12) than the primary tumors of the metastatic-negative mice. Conclusions: These findings support the clinical attempts to establish DCE-MRI as a method for providing biomarkers for tumor aggressiveness and suggests that primary tumors characterized by low K{sup trans} and low v{sub e} values could have a high probability of hypoxia-associated metastatic spread.« less

Fire Monitoring from the New Generation of US Polar and Geostationary Satellites

NASA Astrophysics Data System (ADS)

Csiszar, I.; Justice, C. O.; Prins, E.; Schroeder, W.; Schmidt, C.; Giglio, L.

2012-04-01

Sensors on the new generation of US operational environmental satellites will provide measurements suitable for active fire detection and characterization. The NPOESS Preparatory Project (NPP) satellite, launched on October 28, 2011, carries the Visible Infrared Imager Radiometer Suite (VIIRS), which is expected to continue the active fire data record from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Terra and Aqua Satellites. Early evaluation of the VIIRS active fire product, including comparison to near-simultaneous MODIS data, is underway. The new generation of Geostationary Operational Environmental Satellite (GOES) series, starting with GOES-R to be launched in 2015, will carry the Advanced Baseline Imager (ABI), providing higher spatial and temporal resolution than the current GOES imager. The ABI will also include a dedicated band to provide radiance observations over a wider dynamic range to detect and characterize hot targets. In this presentation we discuss details of the monitoring capabilities from both VIIRS and ABI and the current status of the corresponding algorithm development and testing efforts. An integral part of this activity is explicit product validation, utilizing high resolution satellite and airborne imagery as reference data. The new capabilities also represent challenges to establish continuity with data records from heritage missions, and to coordinate compatible international missions towards a global multi-platform fire monitoring system. These objectives are pursued by the Fire Mapping and Monitoring Implementation Team of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) program, which also provides coordinated contribution to relevant initiatives by the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS) and the Global Climate Observing System (GCOS).

Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

NASA Astrophysics Data System (ADS)

Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu

2016-03-01

The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).

Land cover change mapping using MODIS time series to improve emissions inventories

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie

2016-04-01

MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.

A Clinical Evaluation of Cone Beam Computed Tomography

DTIC Science & Technology

2013-07-31

body of literature lacks in vivo studies comparing CBCT images with clinical findings. The purpose of this descriptive case series was to...All (18/18) bone measurements were underrepresented on CBCT images in this study . This case series also identified limitations in accuracy when... study was to compare pre-surgical CBCT images against the actual clinical presentation of the hard tissues. METHOD: Eleven patients requiring

9. THIRD IMAGE OF THE PANORAMIC SERIES WITH CONSIDERABLE OVERLAP. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

9. THIRD IMAGE OF THE PANORAMIC SERIES WITH CONSIDERABLE OVERLAP. A SETTLING TANK, SMOKESTACK FROM THE MILL'S BOILER ROOM, MILL ANNEX AND OTHER MILL OUT BUILDINGS ARE IN THE MIDDLE RIGHT OF THE IMAGE THE SUPERINTENDENTS HOUSE IS IN THE MIDDLE LEFT OF THE IMAGE SPANNING FROM LEFT TO RIGHT IN THE BACKGROUND IS THE TOWN OF BODIE. IN THE FAR BACKGROUND LEFT IS THE ROAD THAT IS THE ACCESS PARK. - Standard Gold Mill, East of Bodie Creek, Northeast of Bodie, Bodie, Mono County, CA

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

PubMed

Meng, Jie; Zhu, Lijing; Zhu, Li; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-01

Background Apparent diffusion coefficient (ADC) histogram analysis has been widely used in determining tumor prognosis. Purpose To investigate the dynamic changes of ADC histogram parameters during concurrent chemo-radiotherapy (CCRT) in patients with advanced cervical cancers. Material and Methods This prospective study enrolled 32 patients with advanced cervical cancers undergoing CCRT who received diffusion-weighted (DW) magnetic resonance imaging (MRI) before CCRT, at the end of the second and fourth week during CCRT and one month after CCRT completion. The ADC histogram for the entire tumor volume was generated, and a series of histogram parameters was obtained. Dynamic changes of those parameters in cervical cancers were investigated as early biomarkers for treatment response. Results All histogram parameters except AUC low showed significant changes during CCRT (all P < 0.05). There were three variable trends involving different parameters. The mode, 5th, 10th, and 25th percentiles showed similar early increase rates (33.33%, 33.99%, 34.12%, and 30.49%, respectively) at the end of the second week of CCRT. The pre-CCRT 5th and 25th percentiles of the complete response (CR) group were significantly lower than those of the partial response (PR) group. Conclusion A series of ADC histogram parameters of cervical cancers changed significantly at the early stage of CCRT, indicating their potential in monitoring early tumor response to therapy.