Improving lung cancer prognosis assessment by incorporating synthetic minority oversampling technique and score fusion method

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

Yan, Shiju; Qian, Wei; Guan, Yubao

2016-06-15

Purpose: This study aims to investigate the potential to improve lung cancer recurrence risk prediction performance for stage I NSCLS patients by integrating oversampling, feature selection, and score fusion techniques and develop an optimal prediction model. Methods: A dataset involving 94 early stage lung cancer patients was retrospectively assembled, which includes CT images, nine clinical and biological (CB) markers, and outcome of 3-yr disease-free survival (DFS) after surgery. Among the 94 patients, 74 remained DFS and 20 had cancer recurrence. Applying a computer-aided detection scheme, tumors were segmented from the CT images and 35 quantitative image (QI) features were initiallymore » computed. Two normalized Gaussian radial basis function network (RBFN) based classifiers were built based on QI features and CB markers separately. To improve prediction performance, the authors applied a synthetic minority oversampling technique (SMOTE) and a BestFirst based feature selection method to optimize the classifiers and also tested fusion methods to combine QI and CB based prediction results. Results: Using a leave-one-case-out cross-validation (K-fold cross-validation) method, the computed areas under a receiver operating characteristic curve (AUCs) were 0.716 ± 0.071 and 0.642 ± 0.061, when using the QI and CB based classifiers, respectively. By fusion of the scores generated by the two classifiers, AUC significantly increased to 0.859 ± 0.052 (p < 0.05) with an overall prediction accuracy of 89.4%. Conclusions: This study demonstrated the feasibility of improving prediction performance by integrating SMOTE, feature selection, and score fusion techniques. Combining QI features and CB markers and performing SMOTE prior to feature selection in classifier training enabled RBFN based classifier to yield improved prediction accuracy.« less

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

PubMed Central

Islam, Md. Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al. PMID:25114676

Feature and score fusion based multiple classifier selection for iris recognition.

PubMed

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

The new Zero-P implant can effectively reduce the risk of postoperative dysphagia and complications compared with the traditional anterior cage and plate: a systematic review and meta-analysis.

PubMed

Yin, Mengchen; Ma, Junming; Huang, Quan; Xia, Ye; Shen, Qixing; Zhao, Chenglong; Tao, Jun; Chen, Ni; Yu, Zhingxing; Ye, Jie; Mo, Wen; Xiao, Jianru

2016-10-18

The low-profile angle-stable spacer Zero-P is a new kind of cervical fusion system that is claimed to limit the potential drawbacks and complications. The purpose of this meta-analysis was to compare the clinical and radiological results of the new Zero-P implant with those of the traditional anterior cage and plate in the treatment of symptomatic cervical spondylosis, and provides clinicians with evidence on which to base their clinical decision making. The following electronic databases were searched: PMedline, PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, Evidence Based Medicine Reviews, VIP, and CNKI. Conference posters and abstracts were also electronically searched. The efficacy was evaluated in intraoperative time, intraoperative blood loss, fusion rate and dysphagia. For intraoperative time and intraoperative blood loss, the meta-analysis revealed that the Zero-P surgical technique is not superior to the cage and plate technique . For fusion rate, the two techniques both had good bone fusion, however, this difference is not statistically significant. For decrease of JOA and dysphagia, the pooled data showed that the Zero-P surgical technique is superior to the cage and plate technique. Zero-P interbody fusion can attain good clinical efficacy and a satisfactory fusion rate in the treatment of symptomatic cervical spondylosis. It also can effectively reduce the risk of postoperative dysphagia and its complications. However, owing to the lack of long-term follow-up, its long-term efficacy remains unknown.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

Olive oil sensory defects classification with data fusion of instrumental techniques and multivariate analysis (PLS-DA).

PubMed

Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

2016-07-15

Three instrumental techniques, headspace-mass spectrometry (HS-MS), mid-infrared spectroscopy (MIR) and UV-visible spectrophotometry (UV-vis), have been combined to classify virgin olive oil samples based on the presence or absence of sensory defects. The reference sensory values were provided by an official taste panel. Different data fusion strategies were studied to improve the discrimination capability compared to using each instrumental technique individually. A general model was applied to discriminate high-quality non-defective olive oils (extra-virgin) and the lowest-quality olive oils considered non-edible (lampante). A specific identification of key off-flavours, such as musty, winey, fusty and rancid, was also studied. The data fusion of the three techniques improved the classification results in most of the cases. Low-level data fusion was the best strategy to discriminate musty, winey and fusty defects, using HS-MS, MIR and UV-vis, and the rancid defect using only HS-MS and MIR. The mid-level data fusion approach using partial least squares-discriminant analysis (PLS-DA) scores was found to be the best strategy for defective vs non-defective and edible vs non-edible oil discrimination. However, the data fusion did not sufficiently improve the results obtained by a single technique (HS-MS) to classify non-defective classes. These results indicate that instrumental data fusion can be useful for the identification of sensory defects in virgin olive oils. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Indoor Positioning Method for Smartphones Using Landmarks and PDR.

PubMed

Wang, Xi; Jiang, Mingxing; Guo, Zhongwen; Hu, Naijun; Sun, Zhongwei; Liu, Jing

2016-12-15

Recently location based services (LBS) have become increasingly popular in indoor environments. Among these indoor positioning techniques providing LBS, a fusion approach combining WiFi-based and pedestrian dead reckoning (PDR) techniques is drawing more and more attention of researchers. Although this fusion method performs well in some cases, it still has some limitations, such as heavy computation and inconvenience for real-time use. In this work, we study map information of a given indoor environment, analyze variations of WiFi received signal strength (RSS), define several kinds of indoor landmarks, and then utilize these landmarks to correct accumulated errors derived from PDR. This fusion scheme, called Landmark-aided PDR (LaP), is proved to be light-weight and suitable for real-time implementation by running an Android application designed for the experiment. We compared LaP with other PDR-based fusion approaches. Experimental results show that the proposed scheme can achieve a significant improvement with an average accuracy of 2.17 m.

An Indoor Positioning Method for Smartphones Using Landmarks and PDR †

PubMed Central

Wang, Xi; Jiang, Mingxing; Guo, Zhongwen; Hu, Naijun; Sun, Zhongwei; Liu, Jing

2016-01-01

Recently location based services (LBS) have become increasingly popular in indoor environments. Among these indoor positioning techniques providing LBS, a fusion approach combining WiFi-based and pedestrian dead reckoning (PDR) techniques is drawing more and more attention of researchers. Although this fusion method performs well in some cases, it still has some limitations, such as heavy computation and inconvenience for real-time use. In this work, we study map information of a given indoor environment, analyze variations of WiFi received signal strength (RSS), define several kinds of indoor landmarks, and then utilize these landmarks to correct accumulated errors derived from PDR. This fusion scheme, called Landmark-aided PDR (LaP), is proved to be light-weight and suitable for real-time implementation by running an Android application designed for the experiment. We compared LaP with other PDR-based fusion approaches. Experimental results show that the proposed scheme can achieve a significant improvement with an average accuracy of 2.17 m. PMID:27983670

Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200

Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

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

Kevin McCarthy; Milos Manic

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presentsmore » an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.« less

Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation.

PubMed

Subudhi, Badri Narayan; Thangaraj, Veerakumar; Sankaralingam, Esakkirajan; Ghosh, Ashish

2016-11-01

In this article, a statistical fusion based segmentation technique is proposed to identify different abnormality in magnetic resonance images (MRI). The proposed scheme follows seed selection, region growing-merging and fusion of multiple image segments. In this process initially, an image is divided into a number of blocks and for each block we compute the phase component of the Fourier transform. The phase component of each block reflects the gray level variation among the block but contains a large correlation among them. Hence a singular value decomposition (SVD) technique is adhered to generate a singular value of each block. Then a thresholding procedure is applied on these singular values to identify edgy and smooth regions and some seed points are selected for segmentation. By considering each seed point we perform a binary segmentation of the complete MRI and hence with all seed points we get an equal number of binary images. A parcel based statistical fusion process is used to fuse all the binary images into multiple segments. Effectiveness of the proposed scheme is tested on identifying different abnormalities: prostatic carcinoma detection, tuberculous granulomas identification and intracranial neoplasm or brain tumor detection. The proposed technique is established by comparing its results against seven state-of-the-art techniques with six performance evaluation measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

PubMed

G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

2015-01-01

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of ECT inspection to the first wall of a fusion reactor with wavelet analysis

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

Chen, G.; Yoshida, Y.; Miya, K.

1994-12-31

The first wall of a fusion reactor will be subjected to intensive loads during fusion operations. Since these loads may cause defects in the first wall, nondestructive evaluation techniques of the first wall should be developed. In this paper, we try to apply eddy current testing (ECT) technique to the inspection of the first wall. A method based on current vector potential and wavelet analysis is proposed. Owing to the use of wavelet analysis, a new theory developed recently, the accuracy of the present method is shown to be better than a conventional one.

Multiscale image fusion using the undecimated wavelet transform with spectral factorization and nonorthogonal filter banks.

PubMed

Ellmauthaler, Andreas; Pagliari, Carla L; da Silva, Eduardo A B

2013-03-01

Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.

Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

USGS Publications Warehouse

Lemeshewsky, George P.; Schowengerdt, Robert A.

2000-01-01

Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks

PubMed Central

Fu, Jun-Song; Liu, Yun

2015-01-01

Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy. PMID:25608211

Speaker-independent phoneme recognition with a binaural auditory image model

NASA Astrophysics Data System (ADS)

Francis, Keith Ivan

1997-09-01

This dissertation presents phoneme recognition techniques based on a binaural fusion of outputs of the auditory image model and subsequent azimuth-selective phoneme recognition in a noisy environment. Background information concerning speech variations, phoneme recognition, current binaural fusion techniques and auditory modeling issues is explained. The research is constrained to sources in the frontal azimuthal plane of a simulated listener. A new method based on coincidence detection of neural activity patterns from the auditory image model of Patterson is used for azimuth-selective phoneme recognition. The method is tested in various levels of noise and the results are reported in contrast to binaural fusion methods based on various forms of correlation to demonstrate the potential of coincidence- based binaural phoneme recognition. This method overcomes smearing of fine speech detail typical of correlation based methods. Nevertheless, coincidence is able to measure similarity of left and right inputs and fuse them into useful feature vectors for phoneme recognition in noise.

Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

2016-05-01

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs. PMID:25587878

Dual-tree complex wavelet transform and image block residual-based multi-focus image fusion in visual sensor networks.

PubMed

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-11-26

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs.

Soft computing-based terrain visual sensing and data fusion for unmanned ground robotic systems

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2006-05-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

An investigation of density measurement method for yarn-dyed woven fabrics based on dual-side fusion technique

NASA Astrophysics Data System (ADS)

Zhang, Rui; Xin, Binjie

2016-08-01

Yarn density is always considered as the fundamental structural parameter used for the quality evaluation of woven fabrics. The conventional yarn density measurement method is based on one-side analysis. In this paper, a novel density measurement method is developed for yarn-dyed woven fabrics based on a dual-side fusion technique. Firstly, a lab-used dual-side imaging system is established to acquire both face-side and back-side images of woven fabric and the affine transform is used for the alignment and fusion of the dual-side images. Then, the color images of the woven fabrics are transferred from the RGB to the CIE-Lab color space, and the intensity information of the image extracted from the L component is used for texture fusion and analysis. Subsequently, three image fusion methods are developed and utilized to merge the dual-side images: the weighted average method, wavelet transform method and Laplacian pyramid blending method. The fusion efficacy of each method is evaluated by three evaluation indicators and the best of them is selected to do the reconstruction of the complete fabric texture. Finally, the yarn density of the fused image is measured based on the fast Fourier transform, and the yarn alignment image could be reconstructed using the inverse fast Fourier transform. Our experimental results show that the accuracy of density measurement by using the proposed method is close to 99.44% compared with the traditional method and the robustness of this new proposed method is better than that of conventional analysis methods.

Energy-Based Tissue Fusion for Sutureless Closure: Applications, Mechanisms, and Potential for Functional Recovery.

PubMed

Kramer, Eric A; Rentschler, Mark E

2018-06-04

As minimally invasive surgical techniques progress, the demand for efficient, reliable methods for vascular ligation and tissue closure becomes pronounced. The surgical advantages of energy-based vessel sealing exceed those of traditional, compression-based ligatures in procedures sensitive to duration, foreign bodies, and recovery time alike. Although the use of energy-based devices to seal or transect vasculature and connective tissue bundles is widespread, the breadth of heating strategies and energy dosimetry used across devices underscores an uncertainty as to the molecular nature of the sealing mechanism and induced tissue effect. Furthermore, energy-based techniques exhibit promise for the closure and functional repair of soft and connective tissues in the nervous, enteral, and dermal tissue domains. A constitutive theory of molecular bonding forces that arise in response to supraphysiological temperatures is required in order to optimize and progress the use of energy-based tissue fusion. While rapid tissue bonding has been suggested to arise from dehydration, dipole interactions, molecular cross-links, or the coagulation of cellular proteins, long-term functional tissue repair across fusion boundaries requires that the reaction to thermal damage be tailored to catalyze the onset of biological healing and remodeling. In this review, we compile and contrast findings from published thermal fusion research in an effort to encourage a molecular approach to characterization of the prevalent and promising energy-based tissue bond.

An accurate automated technique for quasi-optics measurement of the microwave diagnostics for fusion plasma

NASA Astrophysics Data System (ADS)

Hu, Jianqiang; Liu, Ahdi; Zhou, Chu; Zhang, Xiaohui; Wang, Mingyuan; Zhang, Jin; Feng, Xi; Li, Hong; Xie, Jinlin; Liu, Wandong; Yu, Changxuan

2017-08-01

A new integrated technique for fast and accurate measurement of the quasi-optics, especially for the microwave/millimeter wave diagnostic systems of fusion plasma, has been developed. Using the LabVIEW-based comprehensive scanning system, we can realize not only automatic but also fast and accurate measurement, which will help to eliminate the effects of temperature drift and standing wave/multi-reflection. With the Matlab-based asymmetric two-dimensional Gaussian fitting method, all the desired parameters of the microwave beam can be obtained. This technique can be used in the design and testing of microwave diagnostic systems such as reflectometers and the electron cyclotron emission imaging diagnostic systems of the Experimental Advanced Superconducting Tokamak.

Fusion-based multi-target tracking and localization for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

NASA Technical Reports Server (NTRS)

Czaja, Wojciech; Le Moigne-Stewart, Jacqueline

2014-01-01

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

A hybrid sensing approach for pure and adulterated honey classification.

PubMed

Subari, Norazian; Mohamad Saleh, Junita; Md Shakaff, Ali Yeon; Zakaria, Ammar

2012-10-17

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

NASA Astrophysics Data System (ADS)

Hannachi, Ammar; Kohler, Sophie; Lallement, Alex; Hirsch, Ernest

2015-04-01

3D modeling of scene contents takes an increasing importance for many computer vision based applications. In particular, industrial applications of computer vision require efficient tools for the computation of this 3D information. Routinely, stereo-vision is a powerful technique to obtain the 3D outline of imaged objects from the corresponding 2D images. As a consequence, this approach provides only a poor and partial description of the scene contents. On another hand, for structured light based reconstruction techniques, 3D surfaces of imaged objects can often be computed with high accuracy. However, the resulting active range data in this case lacks to provide data enabling to characterize the object edges. Thus, in order to benefit from the positive points of various acquisition techniques, we introduce in this paper promising approaches, enabling to compute complete 3D reconstruction based on the cooperation of two complementary acquisition and processing techniques, in our case stereoscopic and structured light based methods, providing two 3D data sets describing respectively the outlines and surfaces of the imaged objects. We present, accordingly, the principles of three fusion techniques and their comparison based on evaluation criterions related to the nature of the workpiece and also the type of the tackled application. The proposed fusion methods are relying on geometric characteristics of the workpiece, which favour the quality of the registration. Further, the results obtained demonstrate that the developed approaches are well adapted for 3D modeling of manufactured parts including free-form surfaces and, consequently quality control applications using these 3D reconstructions.

Fusion of 3D models derived from TLS and image-based techniques for CH enhanced documentation

NASA Astrophysics Data System (ADS)

Bastonero, P.; Donadio, E.; Chiabrando, F.; Spanò, A.

2014-05-01

Recognizing the various advantages offered by 3D new metric survey technologies in the Cultural Heritage documentation phase, this paper presents some tests of 3D model generation, using different methods, and their possible fusion. With the aim to define potentialities and problems deriving from integration or fusion of metric data acquired with different survey techniques, the elected test case is an outstanding Cultural Heritage item, presenting both widespread and specific complexities connected to the conservation of historical buildings. The site is the Staffarda Abbey, the most relevant evidence of medieval architecture in Piedmont. This application faced one of the most topical architectural issues consisting in the opportunity to study and analyze an object as a whole, from twice location of acquisition sensors, both the terrestrial and the aerial one. In particular, the work consists in the evaluation of chances deriving from a simple union or from the fusion of different 3D cloudmodels of the abbey, achieved by multi-sensor techniques. The aerial survey is based on a photogrammetric RPAS (Remotely piloted aircraft system) flight while the terrestrial acquisition have been fulfilled by laser scanning survey. Both techniques allowed to extract and process different point clouds and to generate consequent 3D continuous models which are characterized by different scale, that is to say different resolutions and diverse contents of details and precisions. Starting from these models, the proposed process, applied to a sample area of the building, aimed to test the generation of a unique 3Dmodel thorough a fusion of different sensor point clouds. Surely, the describing potential and the metric and thematic gains feasible by the final model exceeded those offered by the two detached models.

Collection Fusion Using Bayesian Estimation of a Linear Regression Model in Image Databases on the Web.

ERIC Educational Resources Information Center

Kim, Deok-Hwan; Chung, Chin-Wan

2003-01-01

Discusses the collection fusion problem of image databases, concerned with retrieving relevant images by content based retrieval from image databases distributed on the Web. Focuses on a metaserver which selects image databases supporting similarity measures and proposes a new algorithm which exploits a probabilistic technique using Bayesian…

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

PubMed

Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

2014-08-30

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques.

PubMed

Franchi, G; Angulo, J; Moreaud, M; Sorbier, L

2018-01-01

The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have discriminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Comparison of inert-gas-fusion and modified Kjeldahl techniques for determination of nitrogen in niobium alloys

NASA Technical Reports Server (NTRS)

Merkle, E. J.; Graab, J. W.; Davis, W. F.

1974-01-01

This report compares results obtained for the determination of nitrogen in a selected group of niobium-base alloys by the inert-gas-fusion and the Kjeldahl procedures. In the inert-gas-fusion procedure the sample is heated to approximately 2700 C in a helium atmosphere in a single-use graphite crucible. A platinum flux is used to facilitate melting of the sample. The Kjeldahl method consisted of a rapid decomposition with a mixture of hydrofluoric acid, phosphoric acid, and potassium chromate; distillation in the presence of sodium hydroxide; and highly sensitive spectrophotometry with nitroprusside-catalyzed indophenol. In the 30- to 80-ppm range, the relative standard deviation was 5 to 7 percent for the inert-gas-fusion procedure and 2 to 8 percent for the Kjeldahl procedure. The agreement of the nitrogen results obtained by the two techniques is considered satisfactory.

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Perspectives of SiC-Based Ceramic Composites and Their Applications to Fusion Reactors 5.Development of Evaluation and Application Techniques of SiC⁄SiC Composites for Fusion Reactors

NASA Astrophysics Data System (ADS)

Hinoki, Tatsuya

Evaluation techniques and mechanical properties of silicon carbide composites (SiC⁄SiC composites) reinforced with highly crystalline fibers are reviewed for fusion applications. The SiC⁄SiC composites used were fabricated by means of the CVI method. The evaluation includes in-plane tensile strength by in-plane tensile test, transthickness tensile strength by transthickness tensile test and diametral compression test and shear strength by compression test using double-notched specimen. All tests were successfully conducted using small specimens for neutron irradiation experiment. As application technique, the novel tungsten(W) coating technique on SiC is reviewed. The W powder melted by high power lamp in a few seconds and formed coating on SiC. No thick reaction layers of WC and W5Si3, which are formed by the other coating methods, were formed by this method.

Sensor fusion of monocular cameras and laser rangefinders for line-based Simultaneous Localization and Mapping (SLAM) tasks in autonomous mobile robots.

PubMed

Zhang, Xinzheng; Rad, Ahmad B; Wong, Yiu-Kwong

2012-01-01

This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method.

Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications

NASA Astrophysics Data System (ADS)

Paramanandham, Nirmala; Rajendiran, Kishore

2018-01-01

A novel image fusion technique is presented for integrating infrared and visible images. Integration of images from the same or various sensing modalities can deliver the required information that cannot be delivered by viewing the sensor outputs individually and consecutively. In this paper, a swarm intelligence based image fusion technique using discrete cosine transform (DCT) domain is proposed for surveillance application which integrates the infrared image with the visible image for generating a single informative fused image. Particle swarm optimization (PSO) is used in the fusion process for obtaining the optimized weighting factor. These optimized weighting factors are used for fusing the DCT coefficients of visible and infrared images. Inverse DCT is applied for obtaining the initial fused image. An enhanced fused image is obtained through adaptive histogram equalization for a better visual understanding and target detection. The proposed framework is evaluated using quantitative metrics such as standard deviation, spatial frequency, entropy and mean gradient. The experimental results demonstrate the outperformance of the proposed algorithm over many other state- of- the- art techniques reported in literature.

A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method

NASA Astrophysics Data System (ADS)

Zou, Yong Qiang; Gao, Xun Zhang; Li, Xiang; Liu, Yong Xiang

2016-01-01

Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR.

A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method

PubMed Central

Zou, Yong Qiang; Gao, Xun Zhang; Li, Xiang; Liu, Yong Xiang

2016-01-01

Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR. PMID:26781194

Infrared and visible image fusion with spectral graph wavelet transform.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Zong, Jing-guo

2015-09-01

Infrared and visible image fusion technique is a popular topic in image analysis because it can integrate complementary information and obtain reliable and accurate description of scenes. Multiscale transform theory as a signal representation method is widely used in image fusion. In this paper, a novel infrared and visible image fusion method is proposed based on spectral graph wavelet transform (SGWT) and bilateral filter. The main novelty of this study is that SGWT is used for image fusion. On the one hand, source images are decomposed by SGWT in its transform domain. The proposed approach not only effectively preserves the details of different source images, but also excellently represents the irregular areas of the source images. On the other hand, a novel weighted average method based on bilateral filter is proposed to fuse low- and high-frequency subbands by taking advantage of spatial consistency of natural images. Experimental results demonstrate that the proposed method outperforms seven recently proposed image fusion methods in terms of both visual effect and objective evaluation metrics.

Application of Advanced Nuclear Emulsion Technique to Fusion Neutron Diagnostics

NASA Astrophysics Data System (ADS)

Nakayama, Y.; Tomita, H.; Morishima, K.; Yamashita, F.; Hayashi, S.; Cheon, MunSeong; Isobe, M.; Ogawa, K.; Naka, T.; Nakano, T.; Nakamura, M.; Kawarabayashi, J.; Iguchi, T.; Ochiai, K.

In order to measure the 2.5 MeV neutrons produced by DD nuclear fusion reactions, we have developed a compact neutron detector based on nuclear emulsion. After optimization of development conditions, we evaluated the response of the detector to an accelerator-based DD neutron source. The absolute efficiency at an energy of 2.5 MeV was estimated to be (4.1±0.2)×10-6 tracks/neutron.

Research on the Automatic Fusion Strategy of Fixed Value Boundary Based on the Weak Coupling Condition of Grid Partition

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Dou, J. M.; Shen, H.; Li, J.; Yang, G. S.; Fan, R. Q.; Shen, Q.

2018-03-01

With the continuous strengthening of power grids, the network structure is becoming more and more complicated. An open and regional data modeling is used to complete the calculation of the protection fixed value based on the local region. At the same time, a high precision, quasi real-time boundary fusion technique is needed to seamlessly integrate the various regions so as to constitute an integrated fault computing platform which can conduct transient stability analysis of covering the whole network with high accuracy and multiple modes, deal with the impact results of non-single fault, interlocking fault and build “the first line of defense” of the power grid. The boundary fusion algorithm in this paper is an automatic fusion algorithm based on the boundary accurate coupling of the networking power grid partition, which takes the actual operation mode for qualification, complete the boundary coupling algorithm of various weak coupling partition based on open-loop mode, improving the fusion efficiency, truly reflecting its transient stability level, and effectively solving the problems of too much data, too many difficulties of partition fusion, and no effective fusion due to mutually exclusive conditions. In this paper, the basic principle of fusion process is introduced firstly, and then the method of boundary fusion customization is introduced by scene description. Finally, an example is given to illustrate the specific algorithm on how it effectively implements the boundary fusion after grid partition and to verify the accuracy and efficiency of the algorithm.

Proteins on exocytic vesicles mediate calcium-triggered fusion.

PubMed Central

Vogel, S S; Zimmerberg, J

1992-01-01

In many exocytic systems, micromolar concentrations of intracellular Ca2+ trigger fusion. We find that aggregates of secretory granules isolated from sea urchin eggs fuse together when perfused with greater than or equal to 10 microM free Ca2+. Mixing of membrane components was demonstrated by transfer of fluorescent lipophilic dye, and melding of granule contents was seen with differential interference microscopy. A technique based upon light scattering was developed to conveniently detect fusion. Two protein modifiers, trypsin and N-ethylmaleimide, inhibit granule-granule fusion at concentrations similar to those that inhibit granule-plasma membrane fusion. We suggest that molecular machinery sufficient for Ca(2+)-triggered fusion resides on secretory granules as purified and that at least some of these essential components are proteinaceous. Images PMID:1584814

An adaptive block-based fusion method with LUE-SSIM for multi-focus images

NASA Astrophysics Data System (ADS)

Zheng, Jianing; Guo, Yongcai; Huang, Yukun

2016-09-01

Because of the lenses' limited depth of field, digital cameras are incapable of acquiring an all-in-focus image of objects at varying distances in a scene. Multi-focus image fusion technique can effectively solve this problem. Aiming at the block-based multi-focus image fusion methods, the problem that blocking-artifacts often occurs. An Adaptive block-based fusion method based on lifting undistorted-edge structural similarity (LUE-SSIM) is put forward. In this method, image quality metrics LUE-SSIM is firstly proposed, which utilizes the characteristics of human visual system (HVS) and structural similarity (SSIM) to make the metrics consistent with the human visual perception. Particle swarm optimization(PSO) algorithm which selects LUE-SSIM as the object function is used for optimizing the block size to construct the fused image. Experimental results on LIVE image database shows that LUE-SSIM outperform SSIM on Gaussian defocus blur images quality assessment. Besides, multi-focus image fusion experiment is carried out to verify our proposed image fusion method in terms of visual and quantitative evaluation. The results show that the proposed method performs better than some other block-based methods, especially in reducing the blocking-artifact of the fused image. And our method can effectively preserve the undistorted-edge details in focus region of the source images.

Computational comparison of three posterior lumbar interbody fusion techniques by using porous titanium interbody cages with 50% porosity.

PubMed

Lee, Yung-Heng; Chung, Chi-Jen; Wang, Chih-Wei; Peng, Yao-Te; Chang, Chih-Han; Chen, Chih-Hsien; Chen, Yen-Nien; Li, Chun-Ting

2016-04-01

This study investigated the biomechanical response of porous cages and lumbar spine segments immediately after surgery and after bone fusion, in addition to the long-term effects of various posterior lumbar interbody fusion (PLIF) techniques, by using the finite element method. Lumbar L3-L4 models based on three PLIF techniques (a single cage at the center of the intervertebral space, a single cage half-anterior to the intervertebral space, and two cages bilateral to the intervertebral space) with and without bone ingrowth were used to determine the biomechanical response of porous cages and lumbar segments instrumented with porous titanium cages (cage porosity=50%, pore diameter=1mm). The results indicated that bone fusion enhanced the stability of the lumbar segments with porous cages without any posterior instrumentation and reduced the peak von Mises stress in the cortical bones and porous cages. Two cages placed bilateral to the intervertebral space achieved the highest structural stability in the lumbar segment and lowest von Mises stress in the cages under both bone fusion conditions. Under identical loading (2-Nm), the range of motion in the single cage at the center of the intervertebral space with bone fusion decreased by 11% (from 1.18° to 1.05°) during flexion and by 66.5% (from 4.46° to 1.5°) during extension in the single cage half-anterior to the intervertebral space with bone fusion compared with no-fusion models. Thus, two porous titanium cages with 50% porosity can achieve high stability of a lumbar segment with PLIF. If only one cage is available, placing the cage half-anterior to the intervertebral space is recommended for managing degenerated lumbar segments. Copyright © 2016 Elsevier Ltd. All rights reserved.

A fusion algorithm for infrared and visible based on guided filtering and phase congruency in NSST domain

NASA Astrophysics Data System (ADS)

Liu, Zhanwen; Feng, Yan; Chen, Hang; Jiao, Licheng

2017-10-01

A novel and effective image fusion method is proposed for creating a highly informative and smooth surface of fused image through merging visible and infrared images. Firstly, a two-scale non-subsampled shearlet transform (NSST) is employed to decompose the visible and infrared images into detail layers and one base layer. Then, phase congruency is adopted to extract the saliency maps from the detail layers and a guided filtering is proposed to compute the filtering output of base layer and saliency maps. Next, a novel weighted average technique is used to make full use of scene consistency for fusion and obtaining coefficients map. Finally the fusion image was acquired by taking inverse NSST of the fused coefficients map. Experiments show that the proposed approach can achieve better performance than other methods in terms of subjective visual effect and objective assessment.

Numerical Solution of the Electron Heat Transport Equation and Physics-Constrained Modeling of the Thermal Conductivity via Sequential Quadratic Programming Optimization in Nuclear Fusion Plasmas

NASA Astrophysics Data System (ADS)

Paloma, Cynthia S.

The plasma electron temperature (Te) plays a critical role in a tokamak nu- clear fusion reactor since temperatures on the order of 108K are required to achieve fusion conditions. Many plasma properties in a tokamak nuclear fusion reactor are modeled by partial differential equations (PDE's) because they depend not only on time but also on space. In particular, the dynamics of the electron temperature is governed by a PDE referred to as the Electron Heat Transport Equation (EHTE). In this work, a numerical method is developed to solve the EHTE based on a custom finite-difference technique. The solution of the EHTE is compared to temperature profiles obtained by using TRANSP, a sophisticated plasma transport code, for specific discharges from the DIII-D tokamak, located at the DIII-D National Fusion Facility in San Diego, CA. The thermal conductivity (also called thermal diffusivity) of the electrons (Xe) is a plasma parameter that plays a critical role in the EHTE since it indicates how the electron temperature diffusion varies across the minor effective radius of the tokamak. TRANSP approximates Xe through a curve-fitting technique to match experimentally measured electron temperature profiles. While complex physics-based model have been proposed for Xe, there is a lack of a simple mathematical model for the thermal diffusivity that could be used for control design. In this work, a model for Xe is proposed based on a scaling law involving key plasma variables such as the electron temperature (Te), the electron density (ne), and the safety factor (q). An optimization algorithm is developed based on the Sequential Quadratic Programming (SQP) technique to optimize the scaling factors appearing in the proposed model so that the predicted electron temperature and magnetic flux profiles match predefined target profiles in the best possible way. A simulation study summarizing the outcomes of the optimization procedure is presented to illustrate the potential of the proposed modeling method.

A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

PubMed Central

Subari, Norazian; Saleh, Junita Mohamad; Shakaff, Ali Yeon Md; Zakaria, Ammar

2012-01-01

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data. PMID:23202033

Real-time threat assessment for critical infrastructure protection: data incest and conflict in evidential reasoning

NASA Astrophysics Data System (ADS)

Brandon, R.; Page, S.; Varndell, J.

2012-06-01

This paper presents a novel application of Evidential Reasoning to Threat Assessment for critical infrastructure protection. A fusion algorithm based on the PCR5 Dezert-Smarandache fusion rule is proposed which fuses alerts generated by a vision-based behaviour analysis algorithm and a-priori watch-list intelligence data. The fusion algorithm produces a prioritised event list according to a user-defined set of event-type severity or priority weightings. Results generated from application of the algorithm to real data and Behaviour Analysis alerts captured at London's Heathrow Airport under the EU FP7 SAMURAI programme are presented. A web-based demonstrator system is also described which implements the fusion process in real-time. It is shown that this system significantly reduces the data deluge problem, and directs the user's attention to the most pertinent alerts, enhancing their Situational Awareness (SA). The end-user is also able to alter the perceived importance of different event types in real-time, allowing the system to adapt rapidly to changes in priorities as the situation evolves. One of the key challenges associated with fusing information deriving from intelligence data is the issue of Data Incest. Techniques for handling Data Incest within Evidential Reasoning frameworks are proposed, and comparisons are drawn with respect to Data Incest management techniques that are commonly employed within Bayesian fusion frameworks (e.g. Covariance Intersection). The challenges associated with simultaneously dealing with conflicting information and Data Incest in Evidential Reasoning frameworks are also discussed.

A methodology for hard/soft information fusion in the condition monitoring of aircraft

NASA Astrophysics Data System (ADS)

Bernardo, Joseph T.

2013-05-01

Condition-based maintenance (CBM) refers to the philosophy of performing maintenance when the need arises, based upon indicators of deterioration in the condition of the machinery. Traditionally, CBM involves equipping machinery with electronic sensors that continuously monitor components and collect data for analysis. The addition of the multisensory capability of human cognitive functions (i.e., sensemaking, problem detection, planning, adaptation, coordination, naturalistic decision making) to traditional CBM may create a fuller picture of machinery condition. Cognitive systems engineering techniques provide an opportunity to utilize a dynamic resource—people acting as soft sensors. The literature is extensive on techniques to fuse data from electronic sensors, but little work exists on fusing data from humans with that from electronic sensors (i.e., hard/soft fusion). The purpose of my research is to explore, observe, investigate, analyze, and evaluate the fusion of pilot and maintainer knowledge, experiences, and sensory perceptions with digital maintenance resources. Hard/soft information fusion has the potential to increase problem detection capability, improve flight safety, and increase mission readiness. This proposed project consists the creation of a methodology that is based upon the Living Laboratories framework, a research methodology that is built upon cognitive engineering principles1. This study performs a critical assessment of concept, which will support development of activities to demonstrate hard/soft information fusion in operationally relevant scenarios of aircraft maintenance. It consists of fieldwork, knowledge elicitation to inform a simulation and a prototype.

The effect of multispectral image fusion enhancement on human efficiency.

PubMed

Bittner, Jennifer L; Schill, M Trent; Mohd-Zaid, Fairul; Blaha, Leslie M

2017-01-01

The visual system can be highly influenced by changes to visual presentation. Thus, numerous techniques have been developed to augment imagery in an attempt to improve human perception. The current paper examines the potential impact of one such enhancement, multispectral image fusion, where imagery captured in varying spectral bands (e.g., visible, thermal, night vision) is algorithmically combined to produce an output to strengthen visual perception. We employ ideal observer analysis over a series of experimental conditions to (1) establish a framework for testing the impact of image fusion over the varying aspects surrounding its implementation (e.g., stimulus content, task) and (2) examine the effectiveness of fusion on human information processing efficiency in a basic application. We used a set of rotated Landolt C images captured with a number of individual sensor cameras and combined across seven traditional fusion algorithms (e.g., Laplacian pyramid, principal component analysis, averaging) in a 1-of-8 orientation task. We found that, contrary to the idea of fused imagery always producing a greater impact on perception, single-band imagery can be just as influential. Additionally, efficiency data were shown to fluctuate based on sensor combination instead of fusion algorithm, suggesting the need for examining multiple factors to determine the success of image fusion. Our use of ideal observer analysis, a popular technique from the vision sciences, provides not only a standard for testing fusion in direct relation to the visual system but also allows for comparable examination of fusion across its associated problem space of application.

Affordable non-traditional source data mining for context assessment to improve distributed fusion system robustness

NASA Astrophysics Data System (ADS)

Bowman, Christopher; Haith, Gary; Steinberg, Alan; Morefield, Charles; Morefield, Michael

2013-05-01

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data Fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and `big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

Method for PE Pipes Fusion Jointing Based on TRIZ Contradictions Theory

NASA Astrophysics Data System (ADS)

Sun, Jianguang; Tan, Runhua; Gao, Jinyong; Wei, Zihui

The core of the TRIZ theories is the contradiction detection and solution. TRIZ provided various methods for the contradiction solution, but all that is not systematized. Combined with the technique system conception, this paper summarizes an integration solution method for contradiction solution based on the TRIZ contradiction theory. According to the method, a flowchart of integration solution method for contradiction is given. As a casestudy, method of fusion jointing PE pipe is analysised.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

PubMed

Khelifi, Lazhar; Mignotte, Max

2017-08-01

Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.

Fusion of GFP and phase contrast images with complex shearlet transform and Haar wavelet-based energy rule.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Guo, Yanen; Xia, Shunren

2018-03-14

Image fusion techniques can integrate the information from different imaging modalities to get a composite image which is more suitable for human visual perception and further image processing tasks. Fusing green fluorescent protein (GFP) and phase contrast images is very important for subcellular localization, functional analysis of protein and genome expression. The fusion method of GFP and phase contrast images based on complex shearlet transform (CST) is proposed in this paper. Firstly the GFP image is converted to IHS model and its intensity component is obtained. Secondly the CST is performed on the intensity component and the phase contrast image to acquire the low-frequency subbands and the high-frequency subbands. Then the high-frequency subbands are merged by the absolute-maximum rule while the low-frequency subbands are merged by the proposed Haar wavelet-based energy (HWE) rule. Finally the fused image is obtained by performing the inverse CST on the merged subbands and conducting IHS-to-RGB conversion. The proposed fusion method is tested on a number of GFP and phase contrast images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. © 2018 Wiley Periodicals, Inc.

Improved Maturity and Ripeness Classifications of Magnifera Indica cv. Harumanis Mangoes through Sensor Fusion of an Electronic Nose and Acoustic Sensor

PubMed Central

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Saad, Fathinul Syahir Ahmad; Adom, Abdul Hamid; Ahmad, Mohd Noor; Jaafar, Mahmad Nor; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2012-01-01

In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied. PMID:22778629

Improved maturity and ripeness classifications of Magnifera Indica cv. Harumanis mangoes through sensor fusion of an electronic nose and acoustic sensor.

PubMed

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Saad, Fathinul Syahir Ahmad; Adom, Abdul Hamid; Ahmad, Mohd Noor; Jaafar, Mahmad Nor; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2012-01-01

In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied.

Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization.

PubMed

Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua

2015-01-05

Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m.

Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization

PubMed Central

Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua

2015-01-01

Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m. PMID:25569750

[Identification of the authentic quality of Longdanxiegan pill by systematic quantified fingerprint method based on three wavelength fusion chromatogram].

PubMed

Sun, Guoxiang; Zhang, Jingxian

2009-05-01

The three wavelength fusion high performance liquid chromatographic fingerprin (TWFFP) of Longdanxiegan pill (LDXGP) was established to identify the quality of LDXGP by the systematic quantified fingerprint method. The chromatographic fingerprints (CFPs) of the 12 batches of LDXGP were determined by reversed-phase high performance liquid chromatography. The technique of multi-wavelength fusion fingerprint was applied during processing the fingerprints. The TWFFPs containing 63 co-possessing peaks were obtained when choosing baicalin peak as the referential peak. The 12 batches of LDXGP were identified with hierarchical clustering analysis by using macro qualitative similarity (S(m)) as the variable. According to the results of classification, the referential fingerprint (RFP) was synthesized from 10 batches of LDXGP. Taking the RFP for the qualified model, all the 12 batches of LDXGP were evaluated by the systematic quantified fingerprint method. Among the 12 batches of LDXGP, 9 batches were completely qualified, the contents of 1 batch were obviously higher while the chemical constituents quantity and distributed proportion in 2 batches were not qualified. The systematic quantified fingerprint method based on the technique of multi-wavelength fusion fingerprint ca effectively identify the authentic quality of traditional Chinese medicine.

A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

SVM-based multi-sensor fusion for free-living physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty S

2011-01-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on the support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multi-sensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which the activity types and related energy expenditures are derived. The result shows that the method correctly recognized the 13 activity types 84.7% of the time, which is 26% higher than using a hip accelerometer alone. Also, the method predicted the associated energy expenditure with a root mean square error of 0.43 METs, 43% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor was added to the fusion model. These results demonstrate that the multi-sensor fusion technique presented is more effective in assessing activities of varying intensities than the traditional accelerometer-alone based methods.

Magneto-hydrodynamically stable axisymmetric mirrorsa)

NASA Astrophysics Data System (ADS)

Ryutov, D. D.; Berk, H. L.; Cohen, B. I.; Molvik, A. W.; Simonen, T. C.

2011-09-01

Making axisymmetric mirrors magnetohydrodynamically (MHD) stable opens up exciting opportunities for using mirror devices as neutron sources, fusion-fission hybrids, and pure-fusion reactors. This is also of interest from a general physics standpoint (as it seemingly contradicts well-established criteria of curvature-driven instabilities). The axial symmetry allows for much simpler and more reliable designs of mirror-based fusion facilities than the well-known quadrupole mirror configurations. In this tutorial, after a summary of classical results, several techniques for achieving MHD stabilization of the axisymmetric mirrors are considered, in particular: (1) employing the favorable field-line curvature in the end tanks; (2) using the line-tying effect; (3) controlling the radial potential distribution; (4) imposing a divertor configuration on the solenoidal magnetic field; and (5) affecting the plasma dynamics by the ponderomotive force. Some illuminative theoretical approaches for understanding axisymmetric mirror stability are described. The applicability of the various stabilization techniques to axisymmetric mirrors as neutron sources, hybrids, and pure-fusion reactors are discussed; and the constraints on the plasma parameters are formulated.

Knowledge Based System Applications for Guidance and Control (Application des Systemes a Base de Connaissances au Guidage-Pilotage)

DTIC Science & Technology

1991-01-01

techniques and integration concepts. Recent advances in digital computation techniques including data base management , represent the core enabling...tactical information management and effective pilot interaction are essential. Pilot decision aiding, combat automation, sensor fusion and ol-board...tactical battle management concepts offer the opportunity for substantial mission effectiveness improvements. Although real-time tactical military

Salvage of infected total knee fusion: the last option.

PubMed

Wiedel, Jerome D

2002-11-01

Currently the most common indication for an arthrodesis of the knee is a failed infected total knee prosthesis. Other causes of a failed total knee replacement that might necessitate a knee fusion include aseptic loosening, deficient extensor mechanism, poor soft tissues, and Charcot joint. Techniques available for achieving a knee fusion are external fixation and internal fixation methods. The external fixation compression devices have been the most widely used for knee fusion and have been successful until the indications for fusion changed to mostly failed prosthetic knee replacement. With failed total knee replacement, the problem of severe bone loss became an issue, and the external fixation compression devices, even including the biplane external fixators, have been the least successful method reported for gaining fusion. The Ilizarov technique has been shown to achieve rigid fixation despite this bone loss, and a review of reports are showing high fusion rates using this method. Internal fixation methods including plate fixation and intramedullary nails have had the best success in gaining fusion in the face of this bone loss and have replaced external fixation methods as the technique of choice for knee fusion when severe bone loss is present. A review of the literature and a discussion of different fusion techniques are presented including a discussion of the influence that infection has on the success of fusion.

Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

2001-01-01

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-01

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis.

PubMed

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-05

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms. Copyright © 2018 Elsevier B.V. All rights reserved.

Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems.

PubMed

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-07-23

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other.

Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems

PubMed Central

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-01-01

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other. PMID:26213932

Multisensor data fusion for physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John W; Freedson, Patty S

2012-03-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multisensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which activity type and energy expenditure are derived. The results show that the method correctly recognized the 13 activity types 88.1% of the time, which is 12.3% higher than using a hip accelerometer alone. Also, the method predicted energy expenditure with a root mean square error of 0.42 METs, 22.2% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor were added to the fusion model. These results demonstrate that the multisensor fusion technique presented is more effective in identifying activity type and energy expenditure than the traditional accelerometer-alone-based methods.

Fault diagnosis model for power transformers based on information fusion

NASA Astrophysics Data System (ADS)

Dong, Ming; Yan, Zhang; Yang, Li; Judd, Martin D.

2005-07-01

Methods used to assess the insulation status of power transformers before they deteriorate to a critical state include dissolved gas analysis (DGA), partial discharge (PD) detection and transfer function techniques, etc. All of these approaches require experience in order to correctly interpret the observations. Artificial intelligence (AI) is increasingly used to improve interpretation of the individual datasets. However, a satisfactory diagnosis may not be obtained if only one technique is used. For example, the exact location of PD cannot be predicted if only DGA is performed. However, using diverse methods may result in different diagnosis solutions, a problem that is addressed in this paper through the introduction of a fuzzy information infusion model. An inference scheme is proposed that yields consistent conclusions and manages the inherent uncertainty in the various methods. With the aid of information fusion, a framework is established that allows different diagnostic tools to be combined in a systematic way. The application of information fusion technique for insulation diagnostics of transformers is proved promising by means of examples.

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

NASA Technical Reports Server (NTRS)

Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Data fusion for CD metrology: heterogeneous hybridization of scatterometry, CDSEM, and AFM data

NASA Astrophysics Data System (ADS)

Hazart, J.; Chesneau, N.; Evin, G.; Largent, A.; Derville, A.; Thérèse, R.; Bos, S.; Bouyssou, R.; Dezauzier, C.; Foucher, J.

2014-04-01

The manufacturing of next generation semiconductor devices forces metrology tool providers for an exceptional effort in order to meet the requirements for precision, accuracy and throughput stated in the ITRS. In the past years hybrid metrology (based on data fusion theories) has been investigated as a new methodology for advanced metrology [1][2][3]. This paper provides a new point of view of data fusion for metrology through some experiments and simulations. The techniques are presented concretely in terms of equations to be solved. The first point of view is High Level Fusion which is the use of simple numbers with their associated uncertainty postprocessed by tools. In this paper, it is divided into two stages: one for calibration to reach accuracy, the second to reach precision thanks to Bayesian Fusion. From our perspective, the first stage is mandatory before applying the second stage which is commonly presented [1]. However a reference metrology system is necessary for this fusion. So, precision can be improved if and only if the tools to be fused are perfectly matched at least for some parameters. We provide a methodology similar to a multidimensional TMU able to perform this matching exercise. It is demonstrated on a 28 nm node backend lithography case. The second point of view is Deep Level Fusion which works on the contrary with raw data and their combination. In the approach presented here, the analysis of each raw data is based on a parametric model and connections between the parameters of each tool. In order to allow OCD/SEM Deep Level Fusion, a SEM Compact Model derived from [4] has been developed and compared to AFM. As far as we know, this is the first time such techniques have been coupled at Deep Level. A numerical study on the case of a simple stack for lithography is performed. We show strict equivalence of Deep Level Fusion and High Level Fusion when tools are sensitive and models are perfect. When one of the tools can be considered as a reference and the second is biased, High Level Fusion is far superior to standard Deep Level Fusion. Otherwise, only the second stage of High Level Fusion is possible (Bayesian Fusion) and do not provide substantial advantage. Finally, when OCD is equipped with methods for bias detection [5], Deep Level Fusion outclasses the two-stage High Level Fusion and will benefit to the industry for most advanced nodes production.

Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring

NASA Astrophysics Data System (ADS)

Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.

2016-03-01

Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.

Hybrid fusion of linear, non-linear and spectral models for the dynamic modeling of sEMG and skeletal muscle force: an application to upper extremity amputation.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Schoen, Marco P; Subbaram Naidu, D; Urfer, Alex; Chiu, Steve

2013-11-01

Estimating skeletal muscle (finger) forces using surface Electromyography (sEMG) signals poses many challenges. In general, the sEMG measurements are based on single sensor data. In this paper, two novel hybrid fusion techniques for estimating the skeletal muscle force from the sEMG array sensors are proposed. The sEMG signals are pre-processed using five different filters: Butterworth, Chebychev Type II, Exponential, Half-Gaussian and Wavelet transforms. Dynamic models are extracted from the acquired data using Nonlinear Wiener Hammerstein (NLWH) models and Spectral Analysis Frequency Dependent Resolution (SPAFDR) models based system identification techniques. A detailed comparison is provided for the proposed filters and models using 18 healthy subjects. Wavelet transforms give higher mean correlation of 72.6 ± 1.7 (mean ± SD) and 70.4 ± 1.5 (mean ± SD) for NLWH and SPAFDR models, respectively, when compared to the other filters used in this work. Experimental verification of the fusion based hybrid models with wavelet transform shows a 96% mean correlation and 3.9% mean relative error with a standard deviation of ± 1.3 and ± 0.9 respectively between the overall hybrid fusion algorithm estimated and the actual force for 18 test subjects' k-fold cross validation data. © 2013 Elsevier Ltd. All rights reserved.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Segmentation by fusion of histogram-based k-means clusters in different color spaces.

PubMed

Mignotte, Max

2008-05-01

This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable and accurate segmentation result. The different label fields to be fused in our application are given by the same and simple (K-means based) clustering technique on an input image expressed in different color spaces. Our fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation), and has been successfully applied on the Berkeley image database. The experiments herein reported in this paper illustrate the potential of this approach compared to the state-of-the-art segmentation methods recently proposed in the literature.

Novel splice techniques and micro-hole collapse effect in photonic crystal fibers

NASA Astrophysics Data System (ADS)

Xiao, Limin

Photonic crystal fibers (PCFs) represent one of the most active research areas today in the field of fiber optics. Because of the freedom they offer in their design and novel wave-guiding properties, PCFs have resulted in a number of applications that are difficult to achieve with conventional fibers. In practical applications, low-loss connection PCFs with conventional fibers is a key issue for integrating PCF devices into existing fiber optic systems. However, connecting PCFs to conventional fibers without incurring too much loss is a very challenging problem. Two novel techniques were proposed to solve this problem in the thesis. One is fusion splicing technique; the other is micro-tip technique. First, fusion splicing technique for PCFs is investigated. For fusion splicing SMFs and PCFs having similar mode field diameters, a low-loss joint with good mechanical strength can be formed by choosing a suitably weak fusion current, short fusion time, offset and overlap to minimize the collapse of air holes and well melt two fibers together. For small-core PCFs, an optimum mode field match and an adiabatic mode field variation can be achieved by repeated arc discharges. Low-loss fusion splicing of five different PCFs with SMFs are achieved, including large mode PCF, hollow-core PCF, nonlinear PCFs with low and high air-filling fraction and polarization maintaining PCF. The other novel technique is using micro-tips. The method is based on growing photopolymer micro-tips directly on the end face of SMFs. The shape and the size of the tips can be controlled, by adjusting the laser power, the exposure time and the oxygen diffusion concentration for polymerization, to match its mode field to the small-core PCFs. Micro-hole collapse effect can be used to fabricate selective injection PCFs. The suitable arc discharge energy can cause the cladding holes to collapse while leaving the central hollow core to remain open. Thus a simple method for selective filling the central hole of PCFs is developed. Hybrid PCF guides light by a novel guiding mechanism, which is a combination of index-guiding and bandgap-guiding. The properties of the hybrid PCF are systematically investigated.

Comparison of the resulting error in data fusion techniques when used with remote sensing, earth observation, and in-situ data sets for water quality applications

NASA Astrophysics Data System (ADS)

Ziemba, Alexander; El Serafy, Ghada

2016-04-01

Ecological modeling and water quality investigations are complex processes which can require a high level of parameterization and a multitude of varying data sets in order to properly execute the model in question. Since models are generally complex, their calibration and validation can benefit from the application of data and information fusion techniques. The data applied to ecological models comes from a wide range of sources such as remote sensing, earth observation, and in-situ measurements, resulting in a high variability in the temporal and spatial resolution of the various data sets available to water quality investigators. It is proposed that effective fusion into a comprehensive singular set will provide a more complete and robust data resource with which models can be calibrated, validated, and driven by. Each individual product contains a unique valuation of error resulting from the method of measurement and application of pre-processing techniques. The uncertainty and error is further compounded when the data being fused is of varying temporal and spatial resolution. In order to have a reliable fusion based model and data set, the uncertainty of the results and confidence interval of the data being reported must be effectively communicated to those who would utilize the data product or model outputs in a decision making process[2]. Here we review an array of data fusion techniques applied to various remote sensing, earth observation, and in-situ data sets whose domains' are varied in spatial and temporal resolution. The data sets examined are combined in a manner so that the various classifications, complementary, redundant, and cooperative, of data are all assessed to determine classification's impact on the propagation and compounding of error. In order to assess the error of the fused data products, a comparison is conducted with data sets containing a known confidence interval and quality rating. We conclude with a quantification of the performance of the data fusion techniques and a recommendation on the feasibility of applying of the fused products in operating forecast systems and modeling scenarios. The error bands and confidence intervals derived can be used in order to clarify the error and confidence of water quality variables produced by prediction and forecasting models. References [1] F. Castanedo, "A Review of Data Fusion Techniques", The Scientific World Journal, vol. 2013, pp. 1-19, 2013. [2] T. Keenan, M. Carbone, M. Reichstein and A. Richardson, "The model-data fusion pitfall: assuming certainty in an uncertain world", Oecologia, vol. 167, no. 3, pp. 587-597, 2011.

The use of 3D image fusion for percutaneous transluminal angioplasty and stenting of iliac artery obstructions: validation of the technique and systematic review of literature.

PubMed

Goudeketting, Seline R; Heinen, Stefan G; van den Heuvel, Daniel A; van Strijen, Marco J; de Haan, Michiel W; Slump, Cornelis H; de Vries, Jean-Paul P

2018-02-01

The effect of the insertion of guidewires and catheters on fusion accuracy of the three-dimensional (3D) image fusion technique during iliac percutaneous transluminal angioplasty (PTA) procedures has not yet been investigated. Technical validation of the 3D fusion technique was evaluated in 11 patients with common and/or external iliac artery lesions. A preprocedural contrast-enhanced magnetic resonance angiogram (CE-MRA) was segmented and manually registered to a cone-beam computed tomography image created at the beginning of the procedure for each patient. The treating physician visually scored the fusion accuracy (i.e., accurate [<2 mm], mismatch [2-5 mm], or inaccurate [>5 mm]) of the entire vasculature of the overlay with respect to the digital subtraction angiography (DSA) directly after the first obtained DSA. Contours of the vasculature of the fusion images and DSAs were drawn after the procedure. The cranial-caudal, lateral-medial, and absolute displacement were calculated between the vessel centerlines. To determine the influence of the catheters, displacement of the catheterized iliac trajectories were compared with the noncatheterized trajectories. Electronic databases were systematically searched for available literature published between January 2010 till August 2017. The mean registration error for all iliac trajectories (N.=20) was small (4.0±2.5 mm). No significant difference in fusion displacement was observed between catheterized (N.=11) and noncatheterized (N.=9) iliac arteries. The systematic literature search yielded 2 manuscripts with a total of 22 patients. The methodological quality of these studies was poor (≤11 MINORS Score), mainly due to a lack of a control group. Accurate image fusion based on preprocedural CE-MRA is possible and could potentially be of help in iliac PTA procedures. The flexible guidewires and angiographic catheters, routinely used during endovascular procedures of iliac arteries, did not cause significant displacement that influenced the image fusion. Current literature on 3D image fusion in iliac PTA procedures is of limited methodological quality.

Multimodal biometric approach for cancelable face template generation

NASA Astrophysics Data System (ADS)

Paul, Padma Polash; Gavrilova, Marina

2012-06-01

Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.

Robust regression on noisy data for fusion scaling laws

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

Verdoolaege, Geert, E-mail: geert.verdoolaege@ugent.be; Laboratoire de Physique des Plasmas de l'ERM - Laboratorium voor Plasmafysica van de KMS

2014-11-15

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.

Adaptive fusion of infrared and visible images in dynamic scene

NASA Astrophysics Data System (ADS)

Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

2011-11-01

Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

Focus measure method based on the modulus of the gradient of the color planes for digital microscopy

NASA Astrophysics Data System (ADS)

Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel

2018-02-01

The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.

Adult thoracolumbar and lumbar scoliosis treated with long vertebral fusion to the sacropelvis: a comparison between new hybrid selective spinal fusion versus anterior-posterior spinal instrumentation.

PubMed

Yagi, Mitsuru; Patel, Ravi; Lawhorne, Thomas W; Cunningham, Matthew E; Boachie-Adjei, Oheneba

2014-04-01

Combined anteroposterior spinal fusion with instrumentation has been used for many years to treat adult thoracolumbar/lumbar scoliosis. This surgery remains a technical challenge to spine surgeons, and current literature reports high complication rates. The purpose of this study is to validate a new hybrid technique (a combination of single-rod anterior instrumentation and a shorter posterior instrumentation to the sacrum) to treat adult thoracolumbar/lumbar scoliosis. This study is a retrospective consecutive case series of surgically treated patients with adult lumbar or thoracolumbar scoliosis. This is a retrospective study of 33 matched pairs of patients with adult scoliosis who underwent two different surgical procedures: a new hybrid technique versus a third-generation anteroposterior spinal fusion. Preoperative and postoperative outcome measures include self-report measures, physiological measures, and functional measures. In a retrospective case-control study, 33 patients treated with the hybrid technique were matched with 33 patients treated with traditional anteroposterior fusion based on preoperative radiographic parameters. Mean follow-up in the hybrid group was 5.3 years (range, 2-11 years), compared with 4.6 years (range, 2-10 years) in the control group. Operating room (OR) time, estimated blood loss, and levels fused were collected as surrogates for surgical morbidity. Radiographic parameters were collected preoperatively, postoperatively, and at final follow-up. The Scoliosis Research Society Patient Questionnaire (SRS-22r) and Oswestry Disability Index (ODI) scores were collected for clinical outcomes. Operating room time, EBL, and levels fused were significantly less in the hybrid group compared with the control group (p<.0001). The postoperative thoracic Cobb angle was similar between the hybrid and control techniques (p=.24); however, the hybrid technique showed significant improvement in the thoracolumbar/lumbar curves (p=.004) and the lumbosacral fractional curve (p<.0001). The major complication rate was less in the hybrid group compared with the control group (18% vs. 39%, p=.01). Clinical outcomes at final follow-up were not significantly different based on overall SRS-22r scores and ODI scores. The new hybrid technique demonstrates good long-term results, with less morbidity and fewer complications than traditional anteroposterior surgery select patients with thoracolumbar/lumbar scoliosis. This study received no funding. No potential conflict of interest-associated bias existed. Copyright © 2014 Elsevier Inc. All rights reserved.

Regular Deployment of Wireless Sensors to Achieve Connectivity and Information Coverage

PubMed Central

Cheng, Wei; Li, Yong; Jiang, Yi; Yin, Xipeng

2016-01-01

Coverage and connectivity are two of the most critical research subjects in WSNs, while regular deterministic deployment is an important deployment strategy and results in some pattern-based lattice WSNs. Some studies of optimal regular deployment for generic values of rc/rs were shown recently. However, most of these deployments are subject to a disk sensing model, and cannot take advantage of data fusion. Meanwhile some other studies adapt detection techniques and data fusion to sensing coverage to enhance the deployment scheme. In this paper, we provide some results on optimal regular deployment patterns to achieve information coverage and connectivity as a variety of rc/rs, which are all based on data fusion by sensor collaboration, and propose a novel data fusion strategy for deployment patterns. At first the relation between variety of rc/rs and density of sensors needed to achieve information coverage and connectivity is derived in closed form for regular pattern-based lattice WSNs. Then a dual triangular pattern deployment based on our novel data fusion strategy is proposed, which can utilize collaborative data fusion more efficiently. The strip-based deployment is also extended to a new pattern to achieve information coverage and connectivity, and its characteristics are deduced in closed form. Some discussions and simulations are given to show the efficiency of all deployment patterns, including previous patterns and the proposed patterns, to help developers make more impactful WSN deployment decisions. PMID:27529246

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering.

PubMed

Gong, Maoguo; Zhou, Zhiqiang; Ma, Jingjing

2012-04-01

This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image, wavelet fusion rules based on an average operator and minimum local area energy are chosen to fuse the wavelet coefficients for a low-frequency band and a high-frequency band, respectively. A reformulated fuzzy local-information C-means clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log-ratio operator and the mean-ratio operator and gains a better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences.

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

Applying data fusion techniques for benthic habitat mapping and monitoring in a coral reef ecosystem

NASA Astrophysics Data System (ADS)

Zhang, Caiyun

2015-06-01

Accurate mapping and effective monitoring of benthic habitat in the Florida Keys are critical in developing management strategies for this valuable coral reef ecosystem. For this study, a framework was designed for automated benthic habitat mapping by combining multiple data sources (hyperspectral, aerial photography, and bathymetry data) and four contemporary imagery processing techniques (data fusion, Object-based Image Analysis (OBIA), machine learning, and ensemble analysis). In the framework, 1-m digital aerial photograph was first merged with 17-m hyperspectral imagery and 10-m bathymetry data using a pixel/feature-level fusion strategy. The fused dataset was then preclassified by three machine learning algorithms (Random Forest, Support Vector Machines, and k-Nearest Neighbor). Final object-based habitat maps were produced through ensemble analysis of outcomes from three classifiers. The framework was tested for classifying a group-level (3-class) and code-level (9-class) habitats in a portion of the Florida Keys. Informative and accurate habitat maps were achieved with an overall accuracy of 88.5% and 83.5% for the group-level and code-level classifications, respectively.

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

PubMed Central

Pescaru, Dan; Curiac, Daniel-Ioan

2014-01-01

Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. PMID:24594614

Comparative Effectiveness of Targeted Prostate Biopsy Using Magnetic Resonance Imaging Ultrasound Fusion Software and Visual Targeting: a Prospective Study.

PubMed

Lee, Daniel J; Recabal, Pedro; Sjoberg, Daniel D; Thong, Alan; Lee, Justin K; Eastham, James A; Scardino, Peter T; Vargas, Hebert Alberto; Coleman, Jonathan; Ehdaie, Behfar

2016-09-01

We compared the diagnostic outcomes of magnetic resonance-ultrasound fusion and visually targeted biopsy for targeting regions of interest on prostate multiparametric magnetic resonance imaging. Patients presenting for prostate biopsy with regions of interest on multiparametric magnetic resonance imaging underwent magnetic resonance imaging targeted biopsy. For each region of interest 2 visually targeted cores were obtained, followed by 2 cores using a magnetic resonance-ultrasound fusion device. Our primary end point was the difference in the detection of high grade (Gleason 7 or greater) and any grade cancer between visually targeted and magnetic resonance-ultrasound fusion, investigated using McNemar's method. Secondary end points were the difference in detection rate by biopsy location using a logistic regression model and the difference in median cancer length using the Wilcoxon signed rank test. We identified 396 regions of interest in 286 men. The difference in the detection of high grade cancer between magnetic resonance-ultrasound fusion biopsy and visually targeted biopsy was -1.4% (95% CI -6.4 to 3.6, p=0.6) and for any grade cancer the difference was 3.5% (95% CI -1.9 to 8.9, p=0.2). Median cancer length detected by magnetic resonance-ultrasound fusion and visually targeted biopsy was 5.5 vs 5.8 mm, respectively (p=0.8). Magnetic resonance-ultrasound fusion biopsy detected 15% more cancers in the transition zone (p=0.046) and visually targeted biopsy detected 11% more high grade cancer at the prostate base (p=0.005). Only 52% of all high grade cancers were detected by both techniques. We found no evidence of a significant difference in the detection of high grade or any grade cancer between visually targeted and magnetic resonance-ultrasound fusion biopsy. However, the performance of each technique varied in specific biopsy locations and the outcomes of both techniques were complementary. Combining visually targeted biopsy and magnetic resonance-ultrasound fusion biopsy may optimize the detection of prostate cancer. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

PubMed Central

Pires, Ivan Miguel; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco

2016-01-01

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs). PMID:26848664

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

The Research on Dryland Crop Classification Based on the Fusion of SENTINEL-1A SAR and Optical Images

NASA Astrophysics Data System (ADS)

Liu, F.; Chen, T.; He, J.; Wen, Q.; Yu, F.; Gu, X.; Wang, Z.

2018-04-01

In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.

Distributed ISAR Subimage Fusion of Nonuniform Rotating Target Based on Matching Fourier Transform.

PubMed

Li, Yuanyuan; Fu, Yaowen; Zhang, Wenpeng

2018-06-04

In real applications, the image quality of the conventional monostatic Inverse Synthetic Aperture Radar (ISAR) for the maneuvering target is subject to the strong fluctuation of Radar Cross Section (RCS), as the target aspect varies enormously. Meanwhile, the maneuvering target introduces nonuniform rotation after translation motion compensation which degrades the imaging performance of the conventional Fourier Transform (FT)-based method in the cross-range dimension. In this paper, a method which combines the distributed ISAR technique and the Matching Fourier Transform (MFT) is proposed to overcome these problems. Firstly, according to the characteristics of the distributed ISAR, the multiple channel echoes of the nonuniform rotation target from different observation angles can be acquired. Then, by applying the MFT to the echo of each channel, the defocused problem of nonuniform rotation target which is inevitable by using the FT-based imaging method can be avoided. Finally, after preprocessing, scaling and rotation of all subimages, the noncoherent fusion image containing all the RCS information in all channels can be obtained. The accumulation coefficients of all subimages are calculated adaptively according to the their image qualities. Simulation and experimental data are used to validate the effectiveness of the proposed approach, and fusion image with improved recognizability can be obtained. Therefore, by using the distributed ISAR technique and MFT, subimages of high-maneuvering target from different observation angles can be obtained. Meanwhile, by employing the adaptive subimage fusion method, the RCS fluctuation can be alleviated and more recognizable final image can be obtained.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Investigation of complete and incomplete fusion in the 7Li+124Sn reaction near Coulomb barrier energies

NASA Astrophysics Data System (ADS)

Parkar, V. V.; Sharma, Sushil K.; Palit, R.; Upadhyaya, S.; Shrivastava, A.; Pandit, S. K.; Mahata, K.; Jha, V.; Santra, S.; Ramachandran, K.; Nag, T. N.; Rath, P. K.; Kanagalekar, Bhushan; Trivedi, T.

2018-01-01

The complete and incomplete fusion cross sections for the 7Li+124Sn reaction were measured using online and offline characteristic γ -ray detection techniques. The complete fusion (CF) cross sections at energies above the Coulomb barrier were found to be suppressed by ˜26 % compared to the coupled channel calculations. This suppression observed in complete fusion cross sections is found to be commensurate with the measured total incomplete fusion (ICF) cross sections. There is a distinct feature observed in the ICF cross sections, i.e., t capture is found to be dominant compared to α capture at all the measured energies. A simultaneous explanation of complete, incomplete, and total fusion (TF) data was also obtained from the calculations based on the continuum discretized coupled channel method with short range imaginary potentials. The cross section ratios of CF/TF and ICF/TF obtained from the data as well as the calculations showed the dominance of ICF at below-barrier energies and CF at above-barrier energies.

The fusion of large scale classified side-scan sonar image mosaics.

PubMed

Reed, Scott; Tena, Ruiz Ioseba; Capus, Chris; Petillot, Yvan

2006-07-01

This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.

A Comparison of Accuracy of Image- versus Hardware-based Tracking Technologies in 3D Fusion in Aortic Endografting.

PubMed

Rolls, A E; Maurel, B; Davis, M; Constantinou, J; Hamilton, G; Mastracci, T M

2016-09-01

Fusion of three-dimensional (3D) computed tomography and intraoperative two-dimensional imaging in endovascular surgery relies on manual rigid co-registration of bony landmarks and tracking of hardware to provide a 3D overlay (hardware-based tracking, HWT). An alternative technique (image-based tracking, IMT) uses image recognition to register and place the fusion mask. We present preliminary experience with an agnostic fusion technology that uses IMT, with the aim of comparing the accuracy of overlay for this technology with HWT. Data were collected prospectively for 12 patients. All devices were deployed using both IMT and HWT fusion assistance concurrently. Postoperative analysis of both systems was performed by three blinded expert observers, from selected time-points during the procedures, using the displacement of fusion rings, the overlay of vascular markings and the true ostia of renal arteries. The Mean overlay error and the deviation from mean error was derived using image analysis software. Comparison of the mean overlay error was made between IMT and HWT. The validity of the point-picking technique was assessed. IMT was successful in all of the first 12 cases, whereas technical learning curve challenges thwarted HWT in four cases. When independent operators assessed the degree of accuracy of the overlay, the median error for IMT was 3.9 mm (IQR 2.89-6.24, max 9.5) versus 8.64 mm (IQR 6.1-16.8, max 24.5) for HWT (p = .001). Variance per observer was 0.69 mm(2) and 95% limit of agreement ±1.63. In this preliminary study, the error of magnitude of displacement from the "true anatomy" during image overlay in IMT was less than for HWT. This confirms that ongoing manual re-registration, as recommended by the manufacturer, should be performed for HWT systems to maintain accuracy. The error in position of the fusion markers for IMT was consistent, thus may be considered predictable. Copyright © 2016 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

PubMed Central

Henninger, B.; Putzer, D.; Kendler, D.; Uprimny, C.; Virgolini, I.; Gunsilius, E.; Bale, R.

2012-01-01

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures. PMID:22654631

Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.

PubMed

Chavan, Satishkumar S; Mahajan, Abhishek; Talbar, Sanjay N; Desai, Subhash; Thakur, Meenakshi; D'cruz, Anil

2017-02-01

Neurocysticercosis (NCC) is a parasite infection caused by the tapeworm Taenia solium in its larvae stage which affects the central nervous system of the human body (a definite host). It results in the formation of multiple lesions in the brain at different locations during its various stages. During diagnosis of such symptomatic patients, these lesions can be better visualized using a feature based fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This paper presents a novel approach to Multimodality Medical Image Fusion (MMIF) used for the analysis of the lesions for the diagnostic purpose and post treatment review of NCC. The MMIF presented here is a technique of combining CT and MRI data of the same patient into a new slice using a Nonsubsampled Rotated Complex Wavelet Transform (NSRCxWT). The forward NSRCxWT is applied on both the source modalities separately to extract the complementary and the edge related features. These features are then combined to form a composite spectral plane using average and maximum value selection fusion rules. The inverse transformation on this composite plane results into a new, visually better, and enriched fused image. The proposed technique is tested on the pilot study data sets of patients infected with NCC. The quality of these fused images is measured using objective and subjective evaluation metrics. Objective evaluation is performed by estimating the fusion parameters like entropy, fusion factor, image quality index, edge quality measure, mean structural similarity index measure, etc. The fused images are also evaluated for their visual quality using subjective analysis with the help of three expert radiologists. The experimental results on 43 image data sets of 17 patients are promising and superior when compared with the state of the art wavelet based fusion algorithms. The proposed algorithm can be a part of computer-aided detection and diagnosis (CADD) system which assists the radiologists in clinical practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

PubMed Central

Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2016-01-01

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion. PMID:27472422

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

Fusion of Geophysical Images in the Study of Archaeological Sites

NASA Astrophysics Data System (ADS)

Karamitrou, A. A.; Petrou, M.; Tsokas, G. N.

2011-12-01

This paper presents results from different fusion techniques between geophysical images from different modalities in order to combine them into one image with higher information content than the two original images independently. The resultant image will be useful for the detection and mapping of buried archaeological relics. The examined archaeological area is situated in Kampana site (NE Greece) near the ancient theater of Maronia city. Archaeological excavations revealed an ancient theater, an aristocratic house and the temple of the ancient Greek God Dionysus. Numerous ceramic objects found in the broader area indicated the probability of the existence of buried urban structure. In order to accurately locate and map the latter, geophysical measurements performed with the use of the magnetic method (vertical gradient of the magnetic field) and of the electrical method (apparent resistivity). We performed a semi-stochastic pixel based registration method between the geophysical images in order to fine register them by correcting their local spatial offsets produced by the use of hand held devices. After this procedure we applied to the registered images three different fusion approaches. Image fusion is a relatively new technique that not only allows integration of different information sources, but also takes advantage of the spatial and spectral resolution as well as the orientation characteristics of each image. We have used three different fusion techniques, fusion with mean values, with wavelets by enhancing selected frequency bands and curvelets giving emphasis at specific bands and angles (according the expecting orientation of the relics). In all three cases the fused images gave significantly better results than each of the original geophysical images separately. The comparison of the results of the three different approaches showed that the fusion with the use of curvelets, giving emphasis at the features' orientation, seems to give the best fused image. In the resultant image appear clear linear and ellipsoid features corresponding to potential archaeological relics.

Lumbar interbody fusion: techniques, indications and comparison of interbody fusion options including PLIF, TLIF, MI-TLIF, OLIF/ATP, LLIF and ALIF

PubMed Central

Phan, Kevin; Malham, Greg; Seex, Kevin; Rao, Prashanth J.

2015-01-01

Degenerative disc and facet joint disease of the lumbar spine is common in the ageing population, and is one of the most frequent causes of disability. Lumbar spondylosis may result in mechanical back pain, radicular and claudicant symptoms, reduced mobility and poor quality of life. Surgical interbody fusion of degenerative levels is an effective treatment option to stabilize the painful motion segment, and may provide indirect decompression of the neural elements, restore lordosis and correct deformity. The surgical options for interbody fusion of the lumbar spine include: posterior lumbar interbody fusion (PLIF), transforaminal lumbar interbody fusion (TLIF), minimally invasive transforaminal lumbar interbody fusion (MI-TLIF), oblique lumbar interbody fusion/anterior to psoas (OLIF/ATP), lateral lumbar interbody fusion (LLIF) and anterior lumbar interbody fusion (ALIF). The indications may include: discogenic/facetogenic low back pain, neurogenic claudication, radiculopathy due to foraminal stenosis, lumbar degenerative spinal deformity including symptomatic spondylolisthesis and degenerative scoliosis. In general, traditional posterior approaches are frequently used with acceptable fusion rates and low complication rates, however they are limited by thecal sac and nerve root retraction, along with iatrogenic injury to the paraspinal musculature and disruption of the posterior tension band. Minimally invasive (MIS) posterior approaches have evolved in an attempt to reduce approach related complications. Anterior approaches avoid the spinal canal, cauda equina and nerve roots, however have issues with approach related abdominal and vascular complications. In addition, lateral and OLIF techniques have potential risks to the lumbar plexus and psoas muscle. The present study aims firstly to comprehensively review the available literature and evidence for different lumbar interbody fusion (LIF) techniques. Secondly, we propose a set of recommendations and guidelines for the indications for interbody fusion options. Thirdly, this article provides a description of each approach, and illustrates the potential benefits and disadvantages of each technique with reference to indication and spine level performed. PMID:27683674

Promoting Pre-college Science Education

NASA Astrophysics Data System (ADS)

Taylor, P. L.; Lee, R. L.

2000-10-01

The Fusion Education Program, with continued support from DOE, has strengthened its interactions with educators in promoting pre-college science education for students. Projects aggressively pursued this year include an on-site, college credited, laboratory-based 10-day educator workshop on plasma and fusion science; completion of `Starpower', a fusion power plant simulation on interactive CD; expansion of scientist visits to classrooms; broadened participation in an internet-based science olympiad; and enhancements to the tours of the DIII-D Facility. In the workshop, twelve teachers used bench top devices to explore basic plasma physics. Also included were radiation experiments, computer aided drafting, techniques to integrate fusion science and technology in the classroom, and visits to a University Physics lab and the San Diego Supercomputer Center. Our ``Scientist in a Classroom'' program reached more than 2200 students at 20 schools. Our `Starpower' CD allows a range of interactive learning from the effects of electric and magnetic fields on charged particles to operation of a Tokamak-based power plant. Continuing tours of the DIII-D facility were attended by more than 800 students this past year.

Laparoscopic bone dowel fusions of the lumbar spine.

PubMed

Silcox, D H

1998-10-01

Studies that show laparoscopic lumbar fusion to decrease cost or time of hospitalization or to increase the speed or incidence of return to activities are not currently available. Laparoscopic fusion of the lumbar spine appears to be a potentially attractive approach to treating axial back pain secondary to different causes. Although the technique is attractive because of its minimally invasive nature and marketing allure, it has yet to be established as to what the true clinical efficacy of this procedure will be. Further clinical study of these techniques with longer follow-up, and case-controlled studies should help clinicians to know the best fusion technique to offer patients.

Facial recognition using multisensor images based on localized kernel eigen spaces.

PubMed

Gundimada, Satyanadh; Asari, Vijayan K

2009-06-01

A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.

A Review on Inertia and Linear Friction Welding of Ni-Based Superalloys

NASA Astrophysics Data System (ADS)

Chamanfar, Ahmad; Jahazi, Mohammad; Cormier, Jonathan

2015-04-01

Inertia and linear friction welding are being increasingly used for near-net-shape manufacturing of high-value materials in aerospace and power generation gas turbines because of providing a better quality joint and offering many advantages over conventional fusion welding and mechanical joining techniques. In this paper, the published works up-to-date on inertia and linear friction welding of Ni-based superalloys are reviewed with the objective to make clarifications on discrepancies and uncertainties reported in literature regarding issues related to these two friction welding processes as well as microstructure, texture, and mechanical properties of the Ni-based superalloy weldments. Initially, the chemical composition and microstructure of Ni-based superalloys that contribute to the quality of the joint are reviewed briefly. Then, problems related to fusion welding of these alloys are addressed with due consideration of inertia and linear friction welding as alternative techniques. The fundamentals of inertia and linear friction welding processes are analyzed next with emphasis on the bonding mechanisms and evolution of temperature and strain rate across the weld interface. Microstructural features, texture development, residual stresses, and mechanical properties of similar and dissimilar polycrystalline and single crystal Ni-based superalloy weldments are discussed next. Then, application of inertia and linear friction welding for joining Ni-based superalloys and related advantages over fusion welding, mechanical joining, and machining are explained briefly. Finally, present scientific and technological challenges facing inertia and linear friction welding of Ni-based superalloys including those related to modeling of these processes are addressed.

Infrared and visible image fusion based on visual saliency map and weighted least square optimization

NASA Astrophysics Data System (ADS)

Ma, Jinlei; Zhou, Zhiqiang; Wang, Bo; Zong, Hua

2017-05-01

The goal of infrared (IR) and visible image fusion is to produce a more informative image for human observation or some other computer vision tasks. In this paper, we propose a novel multi-scale fusion method based on visual saliency map (VSM) and weighted least square (WLS) optimization, aiming to overcome some common deficiencies of conventional methods. Firstly, we introduce a multi-scale decomposition (MSD) using the rolling guidance filter (RGF) and Gaussian filter to decompose input images into base and detail layers. Compared with conventional MSDs, this MSD can achieve the unique property of preserving the information of specific scales and reducing halos near edges. Secondly, we argue that the base layers obtained by most MSDs would contain a certain amount of residual low-frequency information, which is important for controlling the contrast and overall visual appearance of the fused image, and the conventional "averaging" fusion scheme is unable to achieve desired effects. To address this problem, an improved VSM-based technique is proposed to fuse the base layers. Lastly, a novel WLS optimization scheme is proposed to fuse the detail layers. This optimization aims to transfer more visual details and less irrelevant IR details or noise into the fused image. As a result, the fused image details would appear more naturally and be suitable for human visual perception. Experimental results demonstrate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

Sensor Fusion Techniques for Phased-Array Eddy Current and Phased-Array Ultrasound Data

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

Arrowood, Lloyd F.

Sensor (or Data) fusion is the process of integrating multiple data sources to produce more consistent, accurate and comprehensive information than is provided by a single data source. Sensor fusion may also be used to combine multiple signals from a single modality to improve the performance of a particular inspection technique. Industrial nondestructive testing may utilize multiple sensors to acquire inspection data depending upon the object under inspection and the anticipated types of defects that can be identified. Sensor fusion can be performed at various levels of signal abstraction with each having its strengths and weaknesses. A multimodal data fusionmore » strategy first proposed by Heideklang and Shokouhi that combines spatially scattered detection locations to improve detection performance of surface-breaking and near-surface cracks in ferromagnetic metals is shown using a surface inspection example and is then extended for volumetric inspections. Utilizing data acquired from an Olympus Omniscan MX2 from both phased array eddy current and ultrasound probes on test phantoms, single and multilevel fusion techniques are employed to integrate signals from the two modalities. Preliminary results demonstrate how confidence in defect identification and interpretation benefit from sensor fusion techniques. Lastly, techniques for integrating data into radiographic and volumetric imagery from computed tomography are described and results are presented.« less

FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud.

PubMed

Márquez, Cristina; López, M Isabel; Ruisánchez, Itziar; Callao, M Pilar

2016-12-01

Two data fusion strategies (high- and mid-level) combined with a multivariate classification approach (Soft Independent Modelling of Class Analogy, SIMCA) have been applied to take advantage of the synergistic effect of the information obtained from two spectroscopic techniques: FT-Raman and NIR. Mid-level data fusion consists of merging some of the previous selected variables from the spectra obtained from each spectroscopic technique and then applying the classification technique. High-level data fusion combines the SIMCA classification results obtained individually from each spectroscopic technique. Of the possible ways to make the necessary combinations, we decided to use fuzzy aggregation connective operators. As a case study, we considered the possible adulteration of hazelnut paste with almond. Using the two-class SIMCA approach, class 1 consisted of unadulterated hazelnut samples and class 2 of samples adulterated with almond. Models performance was also studied with samples adulterated with chickpea. The results show that data fusion is an effective strategy since the performance parameters are better than the individual ones: sensitivity and specificity values between 75% and 100% for the individual techniques and between 96-100% and 88-100% for the mid- and high-level data fusion strategies, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Mosaicing of single plane illumination microscopy images using groupwise registration and fast content-based image fusion

NASA Astrophysics Data System (ADS)

Preibisch, Stephan; Rohlfing, Torsten; Hasak, Michael P.; Tomancak, Pavel

2008-03-01

Single Plane Illumination Microscopy (SPIM; Huisken et al., Nature 305(5686):1007-1009, 2004) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the living biological sample from multiple angles SPIM has the potential to achieve isotropic resolution throughout even relatively large biological specimens. For every angle, however, only a relatively shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. In order to produce a single, uniformly high resolution image, we propose here an image mosaicing algorithm that combines state of the art groupwise image registration for alignment with content-based image fusion to prevent degrading of the fused image due to regional blurring of the input images. For the registration stage, we introduce an application-specific groupwise transformation model that incorporates per-image as well as groupwise transformation parameters. We also propose a new fusion algorithm based on Gaussian filters, which is substantially faster than fusion based on local image entropy. We demonstrate the performance of our mosaicing method on data acquired from living embryos of the fruit fly, Drosophila, using four and eight angle acquisitions.

A novel fusion framework of visible light and infrared images based on singular value decomposition and adaptive DUAL-PCNN in NSST domain

NASA Astrophysics Data System (ADS)

Cheng, Boyang; Jin, Longxu; Li, Guoning

2018-06-01

Visible light and infrared images fusion has been a significant subject in imaging science. As a new contribution to this field, a novel fusion framework of visible light and infrared images based on adaptive dual-channel unit-linking pulse coupled neural networks with singular value decomposition (ADS-PCNN) in non-subsampled shearlet transform (NSST) domain is present in this paper. First, the source images are decomposed into multi-direction and multi-scale sub-images by NSST. Furthermore, an improved novel sum modified-Laplacian (INSML) of low-pass sub-image and an improved average gradient (IAVG) of high-pass sub-images are input to stimulate the ADS-PCNN, respectively. To address the large spectral difference between infrared and visible light and the occurrence of black artifacts in fused images, a local structure information operator (LSI), which comes from local area singular value decomposition in each source image, is regarded as the adaptive linking strength that enhances fusion accuracy. Compared with PCNN models in other studies, the proposed method simplifies certain peripheral parameters, and the time matrix is utilized to decide the iteration number adaptively. A series of images from diverse scenes are used for fusion experiments and the fusion results are evaluated subjectively and objectively. The results of the subjective and objective evaluation show that our algorithm exhibits superior fusion performance and is more effective than the existing typical fusion techniques.

Processing LiDAR Data to Predict Natural Hazards

NASA Technical Reports Server (NTRS)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Application of Magnetized Target Fusion to High-Energy Space Propulsion

NASA Technical Reports Server (NTRS)

Thio, Y. C. F.; Schmidt, G. R.; Kirkpatrick, R. C.; Rodgers, Stephen L. (Technical Monitor)

2001-01-01

Most fusion propulsion concepts that have been investigated in the past employ some form of inertial or magnetic confinement. Although the prospective performance of these concepts is excellent, the fusion processes on which these concepts are based still require considerable development before they can be seriously considered for actual applications. Furthermore, these processes are encumbered by the need for sophisticated plasma and power handling systems that are generally quite inefficient and have historically resulted in large, massive spacecraft designs. Here we present a comparatively new approach, Magnetized Target Fusion (MTF), which offers a nearer-term avenue for realizing the tremendous performance benefits of fusion propulsion'. The key advantage of MTF is its less demanding requirements for driver energy and power processing. Additional features include: 1) very low system masses and volumes, 2) high gain and relatively low waste heat, 3) substantial utilization of energy from product neutrons, 4) efficient, low peak-power drivers based on existing pulsed power technology, and 5) very high Isp, specific power and thrust. MTF overcomes many of the problems associated with traditional fusion techniques, thus making it particularly attractive for space applications. Isp greater than 50,000 seconds and specific powers greater than 50 kilowatts/kilogram appear feasible using relatively near-term pulse power and plasma gun technology.

Is the aligning prism measured with the Mallett unit correlated with fusional vergence reserves?

PubMed

Conway, Miriam L; Thomas, Jennifer; Subramanian, Ahalya

2012-01-01

The Mallett Unit is a clinical test designed to detect the fixation disparity that is most likely to occur in the presence of a decompensated heterophoria. It measures the associated phoria, which is the "aligning prism" needed to nullify the subjective disparity. The technique has gained widespread acceptance within professions such as optometry, for investigating suspected cases of decompensating heterophoria; it is, however, rarely used by orthoptists and ophthalmologists. The aim of this study was to investigate whether fusional vergence reserves, measured routinely by both orthoptists and ophthalmologists to detect heterophoria decompensation, were correlated with aligning prism (associated phoria) in a normal clinical population. Aligning prism (using the Mallett Unit) and fusional vergence reserves (using a prism bar) were measured in 500 participants (mean 41.63 years; standard deviation 11.86 years) at 40 cm and 6 m. At 40 cm a strong correlation (p<0.001) between base in aligning prism (Exo FD) and positive fusional reserves was found. Of the participants with zero aligning prism 30% had reduced fusional reserves. At 6 m a weak correlation between base out aligning prism (Eso FD) and negative fusional reserves was found to break (p = 0.01) and to recovery (p = 0.048). Of the participants with zero aligning prism 12% reported reduced fusional reserves. For near vision testing, the strong inverse correlation between base in aligning prism (Exo FD) and fusional vergence reserves supports the notion that both measures are indicators of decompensation of heterophoria. For distance vision testing and for those patients reporting zero aligning prism further research is required to determine why the relationship appears to be weak/non-existent?

Is the Aligning Prism Measured with the Mallett Unit Correlated with Fusional Vergence Reserves?

PubMed Central

Conway, Miriam L.; Thomas, Jennifer; Subramanian, Ahalya

2012-01-01

Background The Mallett Unit is a clinical test designed to detect the fixation disparity that is most likely to occur in the presence of a decompensated heterophoria. It measures the associated phoria, which is the “aligning prism” needed to nullify the subjective disparity. The technique has gained widespread acceptance within professions such as optometry, for investigating suspected cases of decompensating heterophoria; it is, however, rarely used by orthoptists and ophthalmologists. The aim of this study was to investigate whether fusional vergence reserves, measured routinely by both orthoptists and ophthalmologists to detect heterophoria decompensation, were correlated with aligning prism (associated phoria) in a normal clinical population. Methodology/Principal Findings Aligning prism (using the Mallett Unit) and fusional vergence reserves (using a prism bar) were measured in 500 participants (mean 41.63 years; standard deviation 11.86 years) at 40 cm and 6 m. At 40 cm a strong correlation (p<0.001) between base in aligning prism (Exo FD) and positive fusional reserves was found. Of the participants with zero aligning prism 30% had reduced fusional reserves. At 6 m a weak correlation between base out aligning prism (Eso FD) and negative fusional reserves was found to break (p = 0.01) and to recovery (p = 0.048). Of the participants with zero aligning prism 12% reported reduced fusional reserves. Conclusions/Significance For near vision testing, the strong inverse correlation between base in aligning prism (Exo FD) and fusional vergence reserves supports the notion that both measures are indicators of decompensation of heterophoria. For distance vision testing and for those patients reporting zero aligning prism further research is required to determine why the relationship appears to be weak/non-existent? PMID:22905174

Technologies for Army Knowledge Fusion

DTIC Science & Technology

2004-09-01

interpret it in context and understand the implications (Alberts et al., 2002). Note that the knowledge / information fusion issue arises immediately here...Army Knowledge Fusion Richard Scherl Department of Computer Science Monmouth University Dana L. Ulery Computational and Information Sciences...civilian and military sources. Knowledge fusion, also called information fusion and multisensor data fusion, names the body of techniques needed to

Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

NASA Astrophysics Data System (ADS)

Fan, Lei

Hyperspectral imaging provides the capability of increased sensitivity and discrimination over traditional imaging methods by combining standard digital imaging with spectroscopic methods. For each individual pixel in a hyperspectral image (HSI), a continuous spectrum is sampled as the spectral reflectance/radiance signature to facilitate identification of ground cover and surface material. The abundant spectrum knowledge allows all available information from the data to be mined. The superior qualities within hyperspectral imaging allow wide applications such as mineral exploration, agriculture monitoring, and ecological surveillance, etc. The processing of massive high-dimensional HSI datasets is a challenge since many data processing techniques have a computational complexity that grows exponentially with the dimension. Besides, a HSI dataset may contain a limited number of degrees of freedom due to the high correlations between data points and among the spectra. On the other hand, merely taking advantage of the sampled spectrum of individual HSI data point may produce inaccurate results due to the mixed nature of raw HSI data, such as mixed pixels, optical interferences and etc. Fusion strategies are widely adopted in data processing to achieve better performance, especially in the field of classification and clustering. There are mainly three types of fusion strategies, namely low-level data fusion, intermediate-level feature fusion, and high-level decision fusion. Low-level data fusion combines multi-source data that is expected to be complementary or cooperative. Intermediate-level feature fusion aims at selection and combination of features to remove redundant information. Decision level fusion exploits a set of classifiers to provide more accurate results. The fusion strategies have wide applications including HSI data processing. With the fast development of multiple remote sensing modalities, e.g. Very High Resolution (VHR) optical sensors, LiDAR, etc., fusion of multi-source data can in principal produce more detailed information than each single source. On the other hand, besides the abundant spectral information contained in HSI data, features such as texture and shape may be employed to represent data points from a spatial perspective. Furthermore, feature fusion also includes the strategy of removing redundant and noisy features in the dataset. One of the major problems in machine learning and pattern recognition is to develop appropriate representations for complex nonlinear data. In HSI processing, a particular data point is usually described as a vector with coordinates corresponding to the intensities measured in the spectral bands. This vector representation permits the application of linear and nonlinear transformations with linear algebra to find an alternative representation of the data. More generally, HSI is multi-dimensional in nature and the vector representation may lose the contextual correlations. Tensor representation provides a more sophisticated modeling technique and a higher-order generalization to linear subspace analysis. In graph theory, data points can be generalized as nodes with connectivities measured from the proximity of a local neighborhood. The graph-based framework efficiently characterizes the relationships among the data and allows for convenient mathematical manipulation in many applications, such as data clustering, feature extraction, feature selection and data alignment. In this thesis, graph-based approaches applied in the field of multi-source feature and data fusion in remote sensing area are explored. We will mainly investigate the fusion of spatial, spectral and LiDAR information with linear and multilinear algebra under graph-based framework for data clustering and classification problems.

Accuracy of implementing principles of fusion imaging in the follow up and surveillance of complex aneurysm repair.

PubMed

Martin-Gonzalez, Teresa; Penney, Graeme; Chong, Debra; Davis, Meryl; Mastracci, Tara M

2018-05-01

Fusion imaging is standard for the endovascular treatment of complex aortic aneurysms, but its role in follow up has not been explored. A critical issue is renal function deterioration over time. Renal volume has been used as a marker of renal impairment; however, it is not reproducible and remains a complex and resource-intensive procedure. The aim of this study is to determine the accuracy of a fusion-based software to automatically calculate the renal volume changes during follow up. In this study, computerized tomography (CT) scans of 16 patients who underwent complex aortic endovascular repair were analysed. Preoperative, 1-month and 1-year follow-up CT scans have been analysed using a conventional approach of semi-automatic segmentation, and a second approach with automatic segmentation. For each kidney and at each time point the percentage of change in renal volume was calculated using both techniques. After review, volume assessment was feasible for all CT scans. For the left kidney, the intraclass correlation coefficient (ICC) was 0.794 and 0.877 at 1 month and 1 year, respectively. For the right side, the ICC was 0.817 at 1 month and 0.966 at 1 year. The automated technique reliably detected a decrease in renal volume for the eight patients with occluded renal arteries during follow up. This is the first report of a fusion-based algorithm to detect changes in renal volume during postoperative surveillance using an automated process. Using this technique, the standardized assessment of renal volume could be implemented with greater ease and reproducibility and serve as a warning of potential renal impairment.

Regional distribution of forest height and biomass from multisensor data fusion

Treesearch

Yifan Yu; Sassan Saatch; Linda S. Heath; Elizabeth LaPoint; Ranga Myneni; Yuri Knyazikhin

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM...

Quantitative image fusion in infrared radiometry

NASA Astrophysics Data System (ADS)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

Green and Fast Laser Fusion Technique for Bulk Silicate Rock Analysis by Laser Ablation-Inductively Coupled Plasma Mass Spectrometry.

PubMed

Zhang, Chenxi; Hu, Zhaochu; Zhang, Wen; Liu, Yongsheng; Zong, Keqing; Li, Ming; Chen, Haihong; Hu, Shenghong

2016-10-18

Sample preparation of whole-rock powders is the major limitation for their accurate and precise elemental analysis by laser ablation inductively-coupled plasma mass spectrometry (ICPMS). In this study, a green, efficient, and simplified fusion technique using a high energy infrared laser was developed for major and trace elemental analysis. Fusion takes only tens of milliseconds for each sample. Compared to the pressed pellet sample preparation, the analytical precision of the developed laser fusion technique is higher by an order of magnitude for most elements in granodiorite GSP-2. Analytical results obtained for five USGS reference materials (ranging from mafic to intermediate to felsic) using the laser fusion technique generally agree with recommended values with discrepancies of less than 10% for most elements. However, high losses (20-70%) of highly volatile elements (Zn and Pb) and the transition metal Cu are observed. The achieved precision is within 5% for major elements and within 15% for most trace elements. Direct laser fusion of rock powders is a green and notably simple method to obtain homogeneous samples, which will significantly accelerate the application of laser ablation ICPMS for whole-rock sample analysis.

Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

PubMed

Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

2010-01-01

In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.

Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064

Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.

Multisource data fusion for documenting archaeological sites

NASA Astrophysics Data System (ADS)

Knyaz, Vladimir; Chibunichev, Alexander; Zhuravlev, Denis

2017-10-01

The quality of archaeological sites documenting is of great importance for cultural heritage preserving and investigating. The progress in developing new techniques and systems for data acquisition and processing creates an excellent basis for achieving a new quality of archaeological sites documenting and visualization. archaeological data has some specific features which have to be taken into account when acquiring, processing and managing. First of all, it is a needed to gather as full as possible information about findings providing no loss of information and no damage to artifacts. Remote sensing technologies are the most adequate and powerful means which satisfy this requirement. An approach to archaeological data acquiring and fusion based on remote sensing is proposed. It combines a set of photogrammetric techniques for obtaining geometrical and visual information at different scales and detailing and a pipeline for archaeological data documenting, structuring, fusion, and analysis. The proposed approach is applied for documenting of Bosporus archaeological expedition of Russian State Historical Museum.

Laser Light-field Fusion for Wide-field Lensfree On-chip Phase Contrast Microscopy of Nanoparticles

NASA Astrophysics Data System (ADS)

Kazemzadeh, Farnoud; Wong, Alexander

2016-12-01

Wide-field lensfree on-chip microscopy, which leverages holography principles to capture interferometric light-field encodings without lenses, is an emerging imaging modality with widespread interest given the large field-of-view compared to lens-based techniques. In this study, we introduce the idea of laser light-field fusion for lensfree on-chip phase contrast microscopy for detecting nanoparticles, where interferometric laser light-field encodings acquired using a lensfree, on-chip setup with laser pulsations at different wavelengths are fused to produce marker-free phase contrast images of particles at the nanometer scale. As a proof of concept, we demonstrate, for the first time, a wide-field lensfree on-chip instrument successfully detecting 300 nm particles across a large field-of-view of ~30 mm2 without any specialized or intricate sample preparation, or the use of synthetic aperture- or shift-based techniques.

Laser Light-field Fusion for Wide-field Lensfree On-chip Phase Contrast Microscopy of Nanoparticles.

PubMed

Kazemzadeh, Farnoud; Wong, Alexander

2016-12-13

Wide-field lensfree on-chip microscopy, which leverages holography principles to capture interferometric light-field encodings without lenses, is an emerging imaging modality with widespread interest given the large field-of-view compared to lens-based techniques. In this study, we introduce the idea of laser light-field fusion for lensfree on-chip phase contrast microscopy for detecting nanoparticles, where interferometric laser light-field encodings acquired using a lensfree, on-chip setup with laser pulsations at different wavelengths are fused to produce marker-free phase contrast images of particles at the nanometer scale. As a proof of concept, we demonstrate, for the first time, a wide-field lensfree on-chip instrument successfully detecting 300 nm particles across a large field-of-view of ~30 mm 2 without any specialized or intricate sample preparation, or the use of synthetic aperture- or shift-based techniques.

The da Vinci robotic surgical assisted anterior lumbar interbody fusion: technical development and case report.

PubMed

Beutler, William J; Peppelman, Walter C; DiMarco, Luciano A

2013-02-15

Technique development to use the da Vince Robotic Surgical System for anterior lumbar interbody fusion at L5-S1 is detailed. A case report is also presented. To evaluate and develop the da Vinci robotic assisted laparoscopic anterior lumbar stand-alone interbody fusion procedure. Anterior lumbar interbody fusion is a common procedure associated with potential morbidity related to the surgical approach. The da Vinci robot provides intra-abdominal dissection and visualization advantages compared with the traditional open and laparoscopic approach. The surgical techniques for approach to the anterior lumbar spine using the da Vinci robot were developed and modified progressively beginning with operative models followed by placement of an interbody fusion cage in the living porcine model. Development continued to progress with placement of fusion cage in a human cadaver, completed first in the laboratory setting and then in the operating room. Finally, the first patient with fusion completed using the da Vinci robot-assisted approach is presented. The anterior transperitoneal approach to the lumbar spine is accomplished with enhanced visualization and dissection capability, with maintenance of pneumoperitoneum using the da Vinci robot. Blood loss is minimal. The visualization inside the disc space and surrounding structures was considered better than current open and laparoscopic techniques. The da Vinci robot Surgical System technique continues to develop and is now described for the transperitoneal approach to the anterior lumbar spine. 4.

[Controversies about instrumented surgery and pain relief in degenerative lumbar spine pain. Results of scientific evidence].

PubMed

Robaina-Padrón, F J

2007-10-01

Investigation and development of new techniques for intrumented surgery of the spine is not free of conflicts of interest. The influence of financial forces in the development of new technologies an its immediately application to spine surgery, shows the relationship between the published results and the industry support. Even authors who have defend eagerly fusion techniques, it have been demonstrated that them are very much involved in the revision of new articles to be published and in the approval process of new spinal technologies. When we analyze the published results of spine surgery, we must bear in mind what have been call in the "American Stock and Exchange" as "the bubble of spine surgery". The scientific literature doesn't show clear evidence in the cost-benefit studies of most instrumented surgical interventions of the spine compare with the conservative treatments. It has not been yet demonstrated that fusion surgery and disc replacement are better options than the conservative treatment. It's necessary to point out that at present "there are relationships between the industry and back pain, and there is also an industry of the back pain". Nonetheless, the "market of the spine surgery" is growing up because patients are demanding solutions for their back problems. The tide of scientific evidence seams to go against the spinal fusions in the degenerative disc disease, discogenic pain and inespecific back pain. After decades of advances in this field, the results of spinal fusions are mediocre. New epidemiological studies show that "spinal fusion must be accepted as a non proved or experimental method for the treatment of back pain". The surgical literature on spinal fusion published in the last 20 years following the Cochrane's method establish that: 1- this is at least incomplete, not reliable and careless; 2- the instrumentation seems to slightly increase the fusion rate; 3- the instrumentation doesn't improve the clinical results in general, lacking studies in subgroups of patients. We still are needing randomized studies to compare the surgical results with the natural history of the disease, the placebo effect, or the conservative treatment. The European Guidelines for lumbar chronic pain management show a "strong evidence" indicating that complex and demanding spine surgery where different instrumentation is used, is not more effective than a simple, safer and cheaper posterolateral fusion without instrumentation. Recently, the literature published in this field is sending a message to use "minimally invasive techniques", abandon transpedicular fusions and clearly indicating that we must apply the knowledge accumulated at least along the last 20 years based on the scientific evidence. In conclusion, based in recent information, we must recommend the "abandon of the instrumented pathway" in a great number of present indications for degenerative spine surgery, and look for new strategies in the field of rehabilitation and conservative treatments correctly apply, using before the decompressive and instrumented surgery all the interventional and minimally invasive techniques that are presently offer in the field of modem lumbar chronic pain treatment.

Fusion of lens-free microscopy and mobile-phone microscopy images for high-color-accuracy and high-resolution pathology imaging

NASA Astrophysics Data System (ADS)

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2017-03-01

Digital pathology and telepathology require imaging tools with high-throughput, high-resolution and accurate color reproduction. Lens-free on-chip microscopy based on digital in-line holography is a promising technique towards these needs, as it offers a wide field of view (FOV >20 mm2) and high resolution with a compact, low-cost and portable setup. Color imaging has been previously demonstrated by combining reconstructed images at three discrete wavelengths in the red, green and blue parts of the visible spectrum, i.e., the RGB combination method. However, this RGB combination method is subject to color distortions. To improve the color performance of lens-free microscopy for pathology imaging, here we present a wavelet-based color fusion imaging framework, termed "digital color fusion microscopy" (DCFM), which digitally fuses together a grayscale lens-free microscope image taken at a single wavelength and a low-resolution and low-magnification color-calibrated image taken by a lens-based microscope, which can simply be a mobile phone based cost-effective microscope. We show that the imaging results of an H&E stained breast cancer tissue slide with the DCFM technique come very close to a color-calibrated microscope using a 40x objective lens with 0.75 NA. Quantitative comparison showed 2-fold reduction in the mean color distance using the DCFM method compared to the RGB combination method, while also preserving the high-resolution features of the lens-free microscope. Due to the cost-effective and field-portable nature of both lens-free and mobile-phone microscopy techniques, their combination through the DCFM framework could be useful for digital pathology and telepathology applications, in low-resource and point-of-care settings.

Multi-sensor information fusion method for vibration fault diagnosis of rolling bearing

NASA Astrophysics Data System (ADS)

Jiao, Jing; Yue, Jianhai; Pei, Di

2017-10-01

Bearing is a key element in high-speed electric multiple unit (EMU) and any defect of it can cause huge malfunctioning of EMU under high operation speed. This paper presents a new method for bearing fault diagnosis based on least square support vector machine (LS-SVM) in feature-level fusion and Dempster-Shafer (D-S) evidence theory in decision-level fusion which were used to solve the problems about low detection accuracy, difficulty in extracting sensitive characteristics and unstable diagnosis system of single-sensor in rolling bearing fault diagnosis. Wavelet de-nosing technique was used for removing the signal noises. LS-SVM was used to make pattern recognition of the bearing vibration signal, and then fusion process was made according to the D-S evidence theory, so as to realize recognition of bearing fault. The results indicated that the data fusion method improved the performance of the intelligent approach in rolling bearing fault detection significantly. Moreover, the results showed that this method can efficiently improve the accuracy of fault diagnosis.

[Possibilities of sonographic image fusion: Current developments].

PubMed

Jung, E M; Clevert, D-A

2015-11-01

For diagnostic and interventional procedures ultrasound (US) image fusion can be used as a complementary imaging technique. Image fusion has the advantage of real time imaging and can be combined with other cross-sectional imaging techniques. With the introduction of US contrast agents sonography and image fusion have gained more importance in the detection and characterization of liver lesions. Fusion of US images with computed tomography (CT) or magnetic resonance imaging (MRI) facilitates the diagnostics and postinterventional therapy control. In addition to the primary application of image fusion in the diagnosis and treatment of liver lesions, there are more useful indications for contrast-enhanced US (CEUS) in routine clinical diagnostic procedures, such as intraoperative US (IOUS), vascular imaging and diagnostics of other organs, such as the kidneys and prostate gland.

Classification of weld defect based on information fusion technology for radiographic testing system

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

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

A Study of Feature Combination for Vehicle Detection Based on Image Processing

PubMed Central

2014-01-01

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299

Fusion of laser and image sensory data for 3-D modeling of the free navigation space

NASA Technical Reports Server (NTRS)

Mass, M.; Moghaddamzadeh, A.; Bourbakis, N.

1994-01-01

A fusion technique which combines two different types of sensory data for 3-D modeling of a navigation space is presented. The sensory data is generated by a vision camera and a laser scanner. The problem of different resolutions for these sensory data was solved by reduced image resolution, fusion of different data, and use of a fuzzy image segmentation technique.

Evaluation of flow properties in the weldments of vanadium alloys using a novel indentation technique

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

Gubbi, A.N.; Rowcliffe, A.F.; Lee, E.H.

1996-10-01

Automated Ball Indentation (ABI) testing, was successfully employed to determine the flow properties of the fusion zone, heat affected zone (HAZ), and base metal of the gas tungsten arc (GTA) and electron beam (EB) welds of the V-4Cr-4Ti (large heat no. 832665) and the V-5Cr-5Ti (heat 832394) alloys. ABI test results showed a clear distinction among the properties of the fusion zone, HAZ, and base metal in both GTA and EB welds of the two alloys. GTA and EB welds of both V-4Cr-4Ti and V-5Cr-5Ti alloys show strengthening of both the fusion zone and the HAZ (compared to base metal)more » with the fusion zone having higher strength than the HAZ. These data correlate well with the Brinell hardness. On the other hand, GTA welds of both alloys, after a post-weld heat treatment of 950{degrees}C for 2 h, show a recovery of the properties to base metal values with V-5Cr-5Ti showing a higher degree of recovery compared to V-4Cr-4Ti. These measurements correlate with the reported recovery of the Charpy impact properties.« less

A comparison of the techniques of direct pars interarticularis repairs for spondylolysis and low-grade spondylolisthesis: a meta-analysis.

PubMed

Mohammed, Nasser; Patra, Devi Prasad; Narayan, Vinayak; Savardekar, Amey R; Dossani, Rimal Hanif; Bollam, Papireddy; Bir, Shyamal; Nanda, Anil

2018-01-01

OBJECTIVE Spondylosis with or without spondylolisthesis that does not respond to conservative management has an excellent outcome with direct pars interarticularis repair. Direct repair preserves the segmental spinal motion. A number of operative techniques for direct repair are practiced; however, the procedure of choice is not clearly defined. The present study aims to clarify the advantages and disadvantages of the different operative techniques and their outcomes. METHODS A meta-analysis was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The following databases were searched: PubMed, Cochrane Library, Web of Science, and CINAHL ( Cumulative Index to Nursing and Allied Health Literature). Studies of patients with spondylolysis with or without low-grade spondylolisthesis who underwent direct repair were included. The patients were divided into 4 groups based on the operative technique used: the Buck repair group, Scott repair group, Morscher repair group, and pedicle screw-based repair group. The pooled data were analyzed using the DerSimonian and Laird random-effects model. Tests for bias and heterogeneity were performed. The I 2 statistic was calculated, and the results were analyzed. Statistical analysis was performed using StatsDirect version 2. RESULTS Forty-six studies consisting of 900 patients were included in the study. The majority of the patients were in their 2nd decade of life. The Buck group included 19 studies with 305 patients; the Scott group had 8 studies with 162 patients. The Morscher method included 5 studies with 193 patients, and the pedicle group included 14 studies with 240 patients. The overall pooled fusion, complication, and outcome rates were calculated. The pooled rates for fusion for the Buck, Scott, Morscher, and pedicle screw groups were 83.53%, 81.57%, 77.72%, and 90.21%, respectively. The pooled complication rates for the Buck, Scott, Morscher, and pedicle screw groups were 13.41%, 22.35%, 27.42%, and 12.8%, respectively, and the pooled positive outcome rates for the Buck, Scott, Morscher, and pedicle screw groups were 84.33%, 82.49%, 80.30%, and 80.1%, respectively. The pedicle group had the best fusion rate and lowest complication rate. CONCLUSIONS The pedicle screw-based direct pars repair for spondylolysis and low-grade spondylolisthesis is the best choice of procedure, with the highest fusion and lowest complication rates, followed by the Buck repair. The Morscher and Scott repairs were associated with a high rate of complication and lower rates of fusion.

Lumbar lordosis restoration following single-level instrumented fusion comparing 4 commonly used techniques.

PubMed

Dimar, John R; Glassman, Steven D; Vemuri, Venu M; Esterberg, Justin L; Howard, Jennifer M; Carreon, Leah Y

2011-11-09

A major sequelae of lumbar fusion is acceleration of adjacent-level degeneration due to decreased lumbar lordosis. We evaluated the effectiveness of 4 common fusion techniques in restoring lordosis: instrumented posterolateral fusion, translumbar interbody fusion, anteroposterior fusion with posterior instrumentation, and anterior interbody fusion with lordotic threaded (LT) cages (Medtronic Sofamor Danek, Memphis, Tennessee). Radiographs were measured preoperatively, immediately postoperatively, and a minimum of 6 months postoperatively. Parameters measured included anterior and posterior disk space height, lumbar lordosis from L3 to S1, and surgical level lordosis.No significant difference in demographics existed among the 4 groups. All preoperative parameters were similar among the 4 groups. Lumbar lordosis at final follow-up showed no difference between the anteroposterior fusion with posterior instrumentation, translumbar interbody fusion, and LT cage groups, although the posterolateral fusion group showed a significant loss of lordosis (-10°) (P<.001). Immediately postoperatively and at follow-up, the LT cage group had a significantly greater amount of lordosis and showed maintenance of anterior and posterior disk space height postoperatively compared with the other groups. Instrumented posterolateral fusion produces a greater loss of lordosis compared with anteroposterior fusion with posterior instrumentation, translumbar interbody fusion, and LT cages. Maintenance of lordosis and anterior and posterior disk space height is significantly better with anterior interbody fusion with LT cages. Copyright 2011, SLACK Incorporated.

Development of next generation tempered and ODS reduced activation ferritic/martensitic steels for fusion energy applications

NASA Astrophysics Data System (ADS)

Zinkle, S. J.; Boutard, J. L.; Hoelzer, D. T.; Kimura, A.; Lindau, R.; Odette, G. R.; Rieth, M.; Tan, L.; Tanigawa, H.

2017-09-01

Reduced activation ferritic/martensitic steels are currently the most technologically mature option for the structural material of proposed fusion energy reactors. Advanced next-generation higher performance steels offer the opportunity for improvements in fusion reactor operational lifetime and reliability, superior neutron radiation damage resistance, higher thermodynamic efficiency, and reduced construction costs. The two main strategies for developing improved steels for fusion energy applications are based on (1) an evolutionary pathway using computational thermodynamics modelling and modified thermomechanical treatments (TMT) to produce higher performance reduced activation ferritic/martensitic (RAFM) steels and (2) a higher risk, potentially higher payoff approach based on powder metallurgy techniques to produce very high strength oxide dispersion strengthened (ODS) steels capable of operation to very high temperatures and with potentially very high resistance to fusion neutron-induced property degradation. The current development status of these next-generation high performance steels is summarized, and research and development challenges for the successful development of these materials are outlined. Material properties including temperature-dependent uniaxial yield strengths, tensile elongations, high-temperature thermal creep, Charpy impact ductile to brittle transient temperature (DBTT) and fracture toughness behaviour, and neutron irradiation-induced low-temperature hardening and embrittlement and intermediate-temperature volumetric void swelling (including effects associated with fusion-relevant helium and hydrogen generation) are described for research heats of the new steels.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Selection of Fusion Levels Using the Fulcrum Bending Radiograph for the Management of Adolescent Idiopathic Scoliosis Patients with Alternate Level Pedicle Screw Strategy: Clinical Decision-making and Outcomes.

PubMed

Samartzis, Dino; Leung, Yee; Shigematsu, Hideki; Natarajan, Deepa; Stokes, Oliver; Mak, Kin-Cheung; Yao, Guanfeng; Luk, Keith D K; Cheung, Kenneth M C

2015-01-01

Selecting fusion levels based on the Luk et al criteria for operative management of thoracic adolescent idiopathic scoliosis (AIS) with hook and hybrid systems yields acceptable curve correction and balance parameters; however, it is unknown whether utilizing a purely pedicle screw strategy is effective. Utilizing the fulcrum bending radiographic (FBR) to assess curve flexibility to select fusion levels, the following study assessed the efficacy of pedicle screw fixation with alternate level screw strategy (ALSS) for thoracic AIS. A retrospective study with prospective radiographic data collection/analyses (preoperative, postoperative 1-week and minimum 2-year follow-up) of 28 operative thoracic AIS patients undergoing ALSS was performed. Standing coronal/sagittal and FBR Cobb angles, FBR flexibility, fulcrum bending correction index (FBCI), trunkal shift, radiographic shoulder height (RSH), and list were assessed on x-rays. Fusion level selection was based on the Luk et al criteria and compared to conventional techniques. In the primary curve, the mean preoperative and postoperative 1 week and last follow-up standing coronal Cobb angles were 59.9, 17.2 and 20.0 degrees, respectively. Eighteen patients (64.3%) had distal levels saved (mean: 1.6 levels) in comparison to conventional techniques. Mean immediate and last follow-up FBCIs were 122.6% and 115.0%, respectively. Sagittal alignment did not statistically differ between any assessment intervals (p>0.05). A decrease in trunkal shift was noted from preoperative to last follow-up (p = 0.003). No statistically significant difference from preoperative to last follow-up was noted in RSH and list (p>0.05). No "add-on" of other vertebra or decompensation was noted and all patients achieved fusion. This is the first report to note that using the FBR for decision-making in selecting fusion levels in thoracic AIS patients undergoing management with pedicle screw constructs (e.g. ALSS) is a cost-effective strategy that can achieve clinically-relevant deformity correction that is maintained and without compromising fusion levels.

A survey of infrared and visual image fusion methods

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, Qian; Yao, Shaowen; Zhou, Dongming; Nie, Rencan; Hai, Jinjin; He, Kangjian

2017-09-01

Infrared (IR) and visual (VI) image fusion is designed to fuse multiple source images into a comprehensive image to boost imaging quality and reduce redundancy information, which is widely used in various imaging equipment to improve the visual ability of human and robot. The accurate, reliable and complementary descriptions of the scene in fused images make these techniques be widely used in various fields. In recent years, a large number of fusion methods for IR and VI images have been proposed due to the ever-growing demands and the progress of image representation methods; however, there has not been published an integrated survey paper about this field in last several years. Therefore, we make a survey to report the algorithmic developments of IR and VI image fusion. In this paper, we first characterize the IR and VI image fusion based applications to represent an overview of the research status. Then we present a synthesize survey of the state of the art. Thirdly, the frequently-used image fusion quality measures are introduced. Fourthly, we perform some experiments of typical methods and make corresponding analysis. At last, we summarize the corresponding tendencies and challenges in IR and VI image fusion. This survey concludes that although various IR and VI image fusion methods have been proposed, there still exist further improvements or potential research directions in different applications of IR and VI image fusion.

Simultaneous measurement of the HT and DT fusion burn histories in inertial fusion implosions

DOE PAGES

Zylstra, Alex B.; Herrmann, Hans W.; Kim, Yong Ho; ...

2017-05-23

Measuring the thermonuclear burn history is an important way to diagnose inertial fusion implosions. Here, using the gas Cherenkov detectors at the OMEGA laser facility, we measure the HT fusion burn in a H 2+T 2 gas-fueled implosion for the first time. Then, using multiple detectors with varied Cherenkov thresholds, we demonstrate a technique for simultaneously measuring both the HT and DT burn histories from an implosion where the total reaction yields are comparable. This new technique will be used to study material mixing and kinetic phenomena in implosions.

Simultaneous measurement of the HT and DT fusion burn histories in inertial fusion implosions

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

Zylstra, Alex B.; Herrmann, Hans W.; Kim, Yong Ho

Measuring the thermonuclear burn history is an important way to diagnose inertial fusion implosions. Here, using the gas Cherenkov detectors at the OMEGA laser facility, we measure the HT fusion burn in a H 2+T 2 gas-fueled implosion for the first time. Then, using multiple detectors with varied Cherenkov thresholds, we demonstrate a technique for simultaneously measuring both the HT and DT burn histories from an implosion where the total reaction yields are comparable. This new technique will be used to study material mixing and kinetic phenomena in implosions.

Occipitocervical fusions in children. Retrospective analysis and technical considerations.

PubMed

Rodgers, W B; Coran, D L; Emans, J B; Hresko, M T; Hall, J E

1999-07-01

This report presents a retrospective analysis of the authors' experience with occipitocervical fusions in children and adolescents during the last 2 decades. A description of an operative technique devised by the senior author (JEH), and a comparison of the results using this and other methods of fusion are given. Twenty-three patients underwent occipitocervical fusion. Fifteen of the patients were operated on using the authors' technique. To achieve stable fixation of the distal cervical vertebra a threaded Kirschner wire was passed transversely through the spinous process; occipital fixation was achieved by the traditional method of wiring corticocancellous bone graft to the skull through burr holes. The occipital wires then were wrapped around the Kirschner wire and the graft was cradled in the resulting nest. Halo immobilization was used in 10 patients for an average of 12.5 weeks (range, 6-24 weeks). Twenty-two patients achieved successful fusion at an average followup of 5.8 years (range, 1-14.33 years). Several complications, including transient quadriplegia in one patient, pseudarthrosis in two (one of which persists), hardware fixation failure in one, unintended distal extension of the fusion, pneumonia, wound infection, halo pin infection, skin breakdown under the halo vest, hydrocephalus, cerebrospinal fluid leak, and traumatic fusion fracture were encountered. Results using the technique described herein are comparable with or better than the results reported in the previous literature, and the results of the patients in this series in whom the technique was not used.

Flow Cytometric Immunobead Assay for Detection of BCR-ABL1 Fusion Proteins in Chronic Myleoid Leukemia: Comparison with FISH and PCR Techniques

PubMed Central

Recchia, Anna Grazia; Caruso, Nadia; Bossio, Sabrina; Pellicanò, Mariavaleria; De Stefano, Laura; Franzese, Stefania; Palummo, Angela; Abbadessa, Vincenzo; Lucia, Eugenio; Gentile, Massimo; Vigna, Ernesto; Caracciolo, Clementina; Agostino, Antolino; Galimberti, Sara; Levato, Luciano; Stagno, Fabio; Molica, Stefano; Martino, Bruno; Vigneri, Paolo; Di Raimondo, Francesco; Morabito, Fortunato

2015-01-01

Chronic Myeloid Leukemia (CML) is characterized by a balanced translocation juxtaposing the Abelson (ABL) and breakpoint cluster region (BCR) genes. The resulting BCR-ABL1 oncogene leads to increased proliferation and survival of leukemic cells. Successful treatment of CML has been accompanied by steady improvements in our capacity to accurately and sensitively monitor therapy response. Currently, measurement of BCR-ABL1 mRNA transcript levels by real-time quantitative PCR (RQ-PCR) defines critical response endpoints. An antibody-based technique for BCR-ABL1 protein recognition could be an attractive alternative to RQ-PCR. To date, there have been no studies evaluating whether flow-cytometry based assays could be of clinical utility in evaluating residual disease in CML patients. Here we describe a flow-cytometry assay that detects the presence of BCR-ABL1 fusion proteins in CML lysates to determine the applicability, reliability, and specificity of this method for both diagnosis and monitoring of CML patients for initial response to therapy. We show that: i) CML can be properly diagnosed at onset, (ii) follow-up assessments show detectable fusion protein (i.e. relative mean fluorescent intensity, rMFI%>1) when BCR-ABL1IS transcripts are between 1–10%, and (iii) rMFI% levels predict CCyR as defined by FISH analysis. Overall, the FCBA assay is a rapid technique, fully translatable to the routine management of CML patients. PMID:26111048

A testbed for architecture and fidelity trade studies in the Bayesian decision-level fusion of ATR products

NASA Astrophysics Data System (ADS)

Erickson, Kyle J.; Ross, Timothy D.

2007-04-01

Decision-level fusion is an appealing extension to automatic/assisted target recognition (ATR) as it is a low-bandwidth technique bolstered by a strong theoretical foundation that requires no modification of the source algorithms. Despite the relative simplicity of decision-level fusion, there are many options for fusion application and fusion algorithm specifications. This paper describes a tool that allows trade studies and optimizations across these many options, by feeding an actual fusion algorithm via models of the system environment. Models and fusion algorithms can be specified and then exercised many times, with accumulated results used to compute performance metrics such as probability of correct identification. Performance differences between the best of the contributing sources and the fused result constitute examples of "gain." The tool, constructed as part of the Fusion for Identifying Targets Experiment (FITE) within the Air Force Research Laboratory (AFRL) Sensors Directorate ATR Thrust, finds its main use in examining the relationships among conditions affecting the target, prior information, fusion algorithm complexity, and fusion gain. ATR as an unsolved problem provides the main challenges to fusion in its high cost and relative scarcity of training data, its variability in application, the inability to produce truly random samples, and its sensitivity to context. This paper summarizes the mathematics underlying decision-level fusion in the ATR domain and describes a MATLAB-based architecture for exploring the trade space thus defined. Specific dimensions within this trade space are delineated, providing the raw material necessary to define experiments suitable for multi-look and multi-sensor ATR systems.

Management of Type II Odontoid Fracture for Osteoporotic Bone Structure: Preliminary Report.

PubMed

Cosar, Murat; Ozer, A Fahir; Alkan, Bahadır; Guven, Mustafa; Akman, Tarık; Aras, Adem Bozkurt; Ceylan, Davut; Tokmak, Mehmet

2015-01-01

Anterior transodontoid screw fixation technique is generally chosen for the management of type II odontoid fractures. The nonunion of type II odontoid fractures is still a major problem especially in elderly and osteoporotic patients. Eleven osteoporotic type II odontoid fracured patients were presented in this article. We have divided 11 patients in two groups as classical and Ozer's technique. We have also compared (radiologically and clinically) the classical anterior transodontoid screw fixation (group II: 6 cases) and Ozer's transodontoid screw fixation technique (group I: 5 cases) retrospectively. There was no difference regaring the clinical features of the groups. However, the radiological results showed 100% fusion for Ozer's screw fixation technique and 83% fusion for the classical screw fixation technique. In conclusion, we suggest that Ozer's technique may help to increase the fusion capacity for osteoporotic type II odontoid fractures.

Improving cerebellar segmentation with statistical fusion

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; Yang, Zhen; Prince, Jerry L.; Claassen, Daniel O.; Landman, Bennett A.

2016-03-01

The cerebellum is a somatotopically organized central component of the central nervous system well known to be involved with motor coordination and increasingly recognized roles in cognition and planning. Recent work in multiatlas labeling has created methods that offer the potential for fully automated 3-D parcellation of the cerebellar lobules and vermis (which are organizationally equivalent to cortical gray matter areas). This work explores the trade offs of using different statistical fusion techniques and post hoc optimizations in two datasets with distinct imaging protocols. We offer a novel fusion technique by extending the ideas of the Selective and Iterative Method for Performance Level Estimation (SIMPLE) to a patch-based performance model. We demonstrate the effectiveness of our algorithm, Non- Local SIMPLE, for segmentation of a mixed population of healthy subjects and patients with severe cerebellar anatomy. Under the first imaging protocol, we show that Non-Local SIMPLE outperforms previous gold-standard segmentation techniques. In the second imaging protocol, we show that Non-Local SIMPLE outperforms previous gold standard techniques but is outperformed by a non-locally weighted vote with the deeper population of atlases available. This work advances the state of the art in open source cerebellar segmentation algorithms and offers the opportunity for routinely including cerebellar segmentation in magnetic resonance imaging studies that acquire whole brain T1-weighted volumes with approximately 1 mm isotropic resolution.

Intelligence Fusion Modeling. A Proposed Approach.

DTIC Science & Technology

1983-09-16

based techniques developed by artificial intelligence researchers. This paper describes the application of these techniques in the modeling of an... intelligence requirements, although the methods presented are applicable . We treat PIR/IR as given. -7- -- -W V"W v* 1.- . :71.,v It k*~ ~-- Movement...items from the PIR/IR/HVT decomposition are received from the CMDS. Formatted tactical intelligence reports are received from sensors of like types

Contemporary instrumentation and application of charge exchange neutral particle diagnostics in magnetic fusion energy experiments.

PubMed

Medley, S S; Donné, A J H; Kaita, R; Kislyakov, A I; Petrov, M P; Roquemore, A L

2008-01-01

An overview of the developments postcirca 1980s in the instrumentation and application of charge exchange neutral particle diagnostics on magnetic fusion energy experiments is presented. First, spectrometers that employ only electric fields and hence provide ion energy resolution but not mass resolution are discussed. Next, spectrometers that use various geometrical combinations of both electric and magnetic fields to provide both energy and mass resolutions are reviewed. Finally, neutral particle diagnostics based on utilization of time-of-flight techniques are presented.

Degenerative lumbar scoliosis in elderly patients: dynamic stabilization without fusion versus posterior instrumented fusion.

PubMed

Di Silvestre, Mario; Lolli, Francesco; Bakaloudis, Georgios

2014-01-01

Posterolateral fusion with pedicle screw instrumentation is currently the most widely accepted technique for degenerative lumbar scoliosis in elderly patients. However, a high incidence of complications has been reported in most series. Dynamic stabilization without fusion in patients older than 60 years has not previously been compared with the use of posterior fusion in degenerative lumbar scoliosis. To compare dynamic stabilization without fusion and posterior instrumented fusion in the treatment of degenerative lumbar scoliosis in elderly patients, in terms of perioperative findings, clinical outcomes, and adverse events. A retrospective study. Fifty-seven elderly patients were included. There were 45 women (78%) and 12 men (22%) with a mean age of 68.1 years (range, 61-78 years). All patients had degenerative de novo lumbar scoliosis, associated with vertebral canal stenosis in 51 cases (89.4%) and degenerative spondylolisthesis in 24 patients (42.1%). Clinical (Oswestry Disability Index, visual analog scale, Roland-Morris Disability Questionnaire) and radiological (scoliosis and lordosis corrections) outcomes as well as incidence of complications. Patients were divided into two groups: 32 patients (dynamic group) had dynamic stabilization without fusion and 25 patients (fusion group) underwent posterior instrumented fusion. All the patients' medical records and X-rays were reviewed. Preoperative, postoperative, and follow-up questionnaires were obtained to evaluate clinical outcomes. At an average follow-up of 64 months (range, 42-90 months), clinical results improved similarly in both groups of patients. Statistically superior scoliosis and final lordosis corrections were achieved with posterior fusion (56.9% vs. 37.3% and -46.8° vs. -35.8°, respectively). However, in the dynamic group, incidence of overall complications was lower (25% vs. 44%), and fewer patients required revision surgery (6.2% vs. 16%). Furthermore, lower average values of operative duration (190 vs. 240 minutes) and blood loss (950 vs. 1,400 cc) were observed in the dynamic group than in the fusion group. In elderly patients with degenerative lumbar scoliosis, pedicle screw-based dynamic stabilization was less invasive with shorter operative duration, less blood loss, and lower adverse event rates than instrumented posterior fusion. Scoliosis curve reduction and lumbar lordosis were superior after fusion; however, dynamic stabilization achieved satisfying values of both these parameters, and these results were stable after an average follow-up of more than 5 years. Furthermore, there was no difference between the two techniques in terms of functional clinical outcomes at the last follow-up. Copyright © 2014 Elsevier Inc. All rights reserved.

Aging time and brand determination of pasteurized milk using a multisensor e-nose combined with a voltammetric e-tongue.

PubMed

Bougrini, Madiha; Tahri, Khalid; Haddi, Zouhair; El Bari, Nezha; Llobet, Eduard; Jaffrezic-Renault, Nicole; Bouchikhi, Benachir

2014-12-01

A combined approach based on a multisensor system to get additional chemical information from liquid samples through the analysis of the solution and its headspace is illustrated and commented. In the present work, innovative analytical techniques, such as a hybrid e-nose and a voltammetric e-tongue were elaborated to differentiate between different pasteurized milk brands and for the exact recognition of their storage days through the data fusion technique of the combined system. The Principal Component Analysis (PCA) has shown an acceptable discrimination of the pasteurized milk brands on the first day of storage, when the two instruments were used independently. Contrariwise, PCA indicated that no clear storage day's discrimination can be drawn when the two instruments are applied separately. Mid-level of abstraction data fusion approach has demonstrated that results obtained by the data fusion approach outperformed the classification results of the e-nose and e-tongue taken individually. Furthermore, the Support Vector Machine (SVM) supervised method was applied to the new subset and confirmed that all storage days were correctly identified. This study can be generalized to several beverage and food products where their quality is based on the perception of odor and flavor. Copyright © 2014 Elsevier B.V. All rights reserved.

Northern Everglades, Florida, satellite image map

USGS Publications Warehouse

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Cost-utility analysis of posterior minimally invasive fusion compared with conventional open fusion for lumbar spondylolisthesis

PubMed Central

Rampersaud, Y. Raja; Gray, Randolph; Lewis, Steven J.; Massicotte, Eric M.; Fehlings, Michael G.

2011-01-01

Background The utility and cost of minimally invasive surgical (MIS) fusion remain controversial. The primary objective of this study was to compare the direct economic impact of 1- and 2-level fusion for grade I or II degenerative or isthmic spondylolisthesis via an MIS technique compared with conventional open posterior decompression and fusion. Methods A retrospective cohort study was performed by use of prospective data from 78 consecutive patients (37 with MIS technique by 1 surgeon and 41 with open technique by 3 surgeons). Independent review of demographic, intraoperative, and acute postoperative data was performed. Oswestry disability index (ODI) and Short Form 36 (SF-36) values were prospectively collected preoperatively and at 1 year postoperatively. Cost-utility analysis was performed by use of in-hospital micro-costing data (operating room, nursing, imaging, laboratories, pharmacy, and allied health cost) and change in health utility index (SF-6D) at 1 year. Results The groups were comparable in terms of age, sex, preoperative hemoglobin, comorbidities, and body mass index. Groups significantly differed (P < .01) regarding baseline ODI and SF-6D scores, as well as number of 2-level fusions (MIS, 12; open, 20) and number of interbody cages (MIS, 45; open, 14). Blood loss (200 mL vs 798 mL), transfusions (0% vs 17%), and length of stay (LOS) (6.1 days vs 8.4 days) were significantly (P < .01) lower in the MIS group. Complications were also fewer in the MIS group (4 vs 12, P < .02). The mean cost of an open fusion was 1.28 times greater than that of an MIS fusion (P = .001). Both groups had significant improvement in 1-year outcome. The changes in ODI and SF-6D scores were not statistically different between groups. Multivariate regression analysis showed that LOS and number of levels fused were independent predictors of cost. Age and MIS were the only predictors of LOS. Baseline outcomes and MIS were predictors of 1-year outcome. Conclusion MIS posterior fusion for spondylolisthesis does reduce blood loss, transfusion requirements, and LOS. Both techniques provided substantial clinical improvements at 1 year. The cost utility of the MIS technique was considered comparable to that of the open technique. Level of Evidence Level III. PMID:25802665

A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-09-01

Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in exascale simulations.

A review of data fusion techniques.

PubMed

Castanedo, Federico

2013-01-01

The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. We first enumerate and explain different classification schemes for data fusion. Then, the most common algorithms are reviewed. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Case presentation and short perspective on management of foraminal/far lateral discs and stenosis.

PubMed

Epstein, Nancy E

2018-01-01

The management of lumbar foraminal/far lateral discs (FOR/FLD) with stenosis remains controversial. Operative choices should be based on each patient's preoperative dynamic X-ray findings, magnetic resonance (MR), and computed tomography (CT) studies. Here we reviewed several options for decompression alone vs. decompression with fusion. Safe excision of FOR/FLD with stenosis should begin at the level above the disc herniation, as identification of the superior, foraminally, and far laterally exiting nerve root is critical. Performing an undercutting laminectomy and utilizing an operating microscope usually preserves the facet joints, and in many cases, avoids the need for fusion. Other decompressive techniques include; the intertransverse (ITT), and Wiltse approaches. Fusions following complete unilateral full facetectomy may be; noninstrumented (e.g., older, osteoporotic patients) vs. instrumented (e.g., posterolateral fusion or occasionally transforaminal lumbar interbody fusion). Here we present a patient with L2-L5 stenosis, and a left L3-L4 FOR/FLD, and multiple synovial cysts who was successfully managed with an l2-L5 laminecotmy, left L34 FOR/FLD diksectomy without fusion. Postoperatively, the patient was neurologically intact, and stability was maintained. Adjunctive measures for FOR/FLD diksectomy should include; intraoperative monitoring, use of the operating microscope, and an intraoperative film with a radiopaque marker in the correct disc space to confirm the correct level of diskectomy. There are multiple approaches to the excision of FOR/FLD with stenosis. These include; decompression alone vs. decompression with non-instrumented vs. instrumented fusion. Surgical choices must be based on individual patient's X-ray, MR, and CT findings. The aim should be to maximize the safety of disc excision with decompression of stenosis, and to preserve stability, reducing the need for fusion, while minimizing morbidity.

Review of early clinical results and complications associated with oblique lumbar interbody fusion (OLIF).

PubMed

Phan, Kevin; Maharaj, Monish; Assem, Yusuf; Mobbs, Ralph J

2016-09-01

Lumbar interbody fusion represents an effective surgical intervention for patients with lumbar degenerative diseases, spondylolisthesis, disc herniation, pseudoarthrosis and spinal deformities. Traditionally, conventional open anterior lumbar interbody fusion and posterior/transforaminal lumbar interbody fusion techniques have been employed with excellent results, but each with their own advantages and caveats. Most recently, the antero-oblique trajectory has been introduced, providing yet another corridor to access the lumbar spine. Termed the oblique lumbar interbody fusion, this approach accesses the spine between the anterior vessels and psoas muscles, avoiding both sets of structures to allow efficient clearance of the disc space and application of a large interbody device to afford distraction for foraminal decompression and endplate preparation for rapid and thorough fusion. This review aims to summarize the early clinical results and complications of this new technique and discusses potential future directions of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recombinational Cloning Using Gateway and In-Fusion Cloning Schemes

PubMed Central

Throop, Andrea L.; LaBaer, Joshua

2015-01-01

The comprehensive study of protein structure and function, or proteomics, depends on the obtainability of full-length cDNAs in species-specific expression vectors and subsequent functional analysis of the expressed protein. Recombinational cloning is a universal cloning technique based on site-specific recombination that is independent of the insert DNA sequence of interest, which differentiates this method from the classical restriction enzyme-based cloning methods. Recombinational cloning enables rapid and efficient parallel transfer of DNA inserts into multiple expression systems. This unit summarizes strategies for generating expression-ready clones using the most popular recombinational cloning technologies, including the commercially available Gateway® (Life Technologies) and In-Fusion® (Clontech) cloning technologies. PMID:25827088

Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

2015-12-01

A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each individual product and demonstrate the precipitation data fusion performance, both individual and fused QPE products are evaluated using rainfall measurements from a disdrometer and gauge network.

Knee arthrodesis using a short locked intramedullary nail. A new technique.

PubMed

Cheng, S L; Gross, A E

1995-01-01

This article reports on the use of a new intramedullary nail designed specifically for fixation of knee fusions. The nail is a short locked stainless steel nail that is inserted through a single anterior knee incision and uses an outrigger targeting rod to guide the insertion of the locking screws. The successful use of this technique is illustrated in two cases. The advantages of this nail compared with previously reported techniques of fixation for knee fusions are that the short locked nail avoids the second incision required for the insertion of long knee fusion nails, the bulkiness of the double plating technique in the relatively subcutaneous anterior knee area, and the difficulties inherent with the prolonged use of pins for external fixation.

Information fusion based techniques for HEVC

NASA Astrophysics Data System (ADS)

Fernández, D. G.; Del Barrio, A. A.; Botella, Guillermo; Meyer-Baese, Uwe; Meyer-Baese, Anke; Grecos, Christos

2017-05-01

Aiming at the conflict circumstances of multi-parameter H.265/HEVC encoder system, the present paper introduces the analysis of many optimizations' set in order to improve the trade-off between quality, performance and power consumption for different reliable and accurate applications. This method is based on the Pareto optimization and has been tested with different resolutions on real-time encoders.

Improving nondestructive characterization of dual phase steels using data fusion

NASA Astrophysics Data System (ADS)

Kahrobaee, Saeed; Haghighi, Mehdi Salkhordeh; Akhlaghi, Iman Ahadi

2018-07-01

The aim of this paper is to introduce a novel methodology for nondestructive determination of microstructural and mechanical properties (due to the various heat treatments), as well as thickness variations (as a result of corrosion effect) of dual phase steels. The characterizations are based on the variations in the electromagnetic properties extracted from magnetic hysteresis loop and eddy current methods which are coupled with a data fusion system. This study was conducted on six groups of samples (with different thicknesses, from 1 mm to 4 mm) subjected to the various intercritical annealing processes to produce different fractions of martensite/ferrite phases and consequently, changes in hardness, yield strength and ultra tensile strength (UTS). This study proposes a novel soft computing technique to increase accuracy of nondestructive measurements and resolving overlapped NDE outputs related to the various samples. The empirical results indicate that applying the proposed data fusion technique on the two electromagnetic NDE data sets nondestructively, causes an increase in the accuracy and reliability of determining material features including ferrite fraction, hardness, yield strength, UTS, as well as thickness variations.

Hardware implementation of hierarchical volume subdivision-based elastic registration.

PubMed

Dandekar, Omkar; Walimbe, Vivek; Shekhar, Raj

2006-01-01

Real-time, elastic and fully automated 3D image registration is critical to the efficiency and effectiveness of many image-guided diagnostic and treatment procedures relying on multimodality image fusion or serial image comparison. True, real-time performance will make many 3D image registration-based techniques clinically viable. Hierarchical volume subdivision-based image registration techniques are inherently faster than most elastic registration techniques, e.g. free-form deformation (FFD)-based techniques, and are more amenable for achieving real-time performance through hardware acceleration. Our group has previously reported an FPGA-based architecture for accelerating FFD-based image registration. In this article we show how our existing architecture can be adapted to support hierarchical volume subdivision-based image registration. A proof-of-concept implementation of the architecture achieved speedups of 100 for elastic registration against an optimized software implementation on a 3.2 GHz Pentium III Xeon workstation. Due to inherent parallel nature of the hierarchical volume subdivision-based image registration techniques further speedup can be achieved by using several computing modules in parallel.

Elastin-like-polypeptide based fusion proteins for osteogenic factor delivery in bone healing.

PubMed

McCarthy, Bryce; Yuan, Yuan; Koria, Piyush

2016-07-08

Modern treatments of bone injuries and diseases are becoming increasingly dependent on the usage of growth factors to stimulate bone growth. Bone morphogenetic protein-2 (BMP-2), a potent osteogenic inductive protein, exhibits promising results in treatment models, but recently has had its practical efficacy questioned due to the lack of local retention, ectopic bone formation, and potentially lethal inflammation. Where a new delivery technique of the BMP-2 is necessary, here we demonstrate the viability of an elastin-like peptide (ELP) fusion protein containing BMP-2 for delivery of the BMP-2. This fusion protein retains the performance characteristics of both the BMP-2 and ELP. The fusion protein was found to induce osteogenic differentiation of mesenchymal stem cells as evidenced by the production of alkaline phosphatase and extracellular calcium deposits in response to treatment by the fusion protein. Retention of the ELPs inverse phase transition property has allowed for expression of the fusion protein within a bacterial host (such as Escherichia coli) and easy and rapid purification using inverse transition cycling. The fusion protein formed self-aggregating nanoparticles at human-body temperature. The data collected suggests the viability of these fusion protein nanoparticles as a dosage-efficient and location-precise noncytotoxic delivery vehicle for BMP-2 in bone treatment. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1029-1037, 2016. © 2016 American Institute of Chemical Engineers.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China

PubMed Central

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R.

2017-01-01

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10 km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique. PMID:28599195

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PubMed

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R; Pan, Xiaochuan; Liu, Yang

2017-10-01

PM 2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM 2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM 2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM 2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R 2 of 0.95 and 0.94, respectively and PM 2.5 was overestimated by WRF-Chem (R 2 =0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM 2.5 . Current monitoring network in North China was dense enough to provide a reliable PM 2.5 prediction by interpolation technique. Copyright © 2017. Published by Elsevier Inc.

Fusion Energy Division progress report, 1 January 1990--31 December 1991

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

Sheffield, J.; Baker, C.C.; Saltmarsh, M.J.

1994-03-01

The Fusion Program of the Oak Ridge National Laboratory (ORNL), a major part of the national fusion program, encompasses nearly all areas of magnetic fusion research. The program is directed toward the development of fusion as an economical and environmentally attractive energy source for the future. The program involves staff from ORNL, Martin Marietta Energy systems, Inc., private industry, the academic community, and other fusion laboratories, in the US and abroad. Achievements resulting from this collaboration are documented in this report, which is issued as the progress report of the ORNL Fusion Energy Division; it also contains information from componentsmore » for the Fusion Program that are external to the division (about 15% of the program effort). The areas addressed by the Fusion Program include the following: experimental and theoretical research on magnetic confinement concepts; engineering and physics of existing and planned devices, including remote handling; development and testing of diagnostic tools and techniques in support of experiments; assembly and distribution to the fusion community of databases on atomic physics and radiation effects; development and testing of technologies for heating and fueling fusion plasmas; development and testing of superconducting magnets for containing fusion plasmas; development and testing of materials for fusion devices; and exploration of opportunities to apply the unique skills, technology, and techniques developed in the course of this work to other areas (about 15% of the Division`s activities). Highlights from program activities during 1990 and 1991 are presented.« less

A Review of Data Fusion Techniques

PubMed Central

2013-01-01

The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. We first enumerate and explain different classification schemes for data fusion. Then, the most common algorithms are reviewed. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion. PMID:24288502

Kinetic advantage of controlled intermediate nuclear fusion

NASA Astrophysics Data System (ADS)

Guo, Xiaoming

2012-09-01

The dominated process of controlled fusion is to let nuclei gain enough kinetic energy to overcome Coulomb barrier. As a result, a fusion scheme can consider two factors in its design: to increase kinetic energy of nuclei and to alter the Coulomb barrier. Cold Fusion and Hot fusion are all one-factor schemes while Intermediate Fusion is a twofactors scheme. This made CINF kinetically superior. Cold Fusion reduces deuteron-deuteron distance, addressing Coulomb barrier, and Hot Fusion heat up plasma into extreme high temperature, addressing kinetic energy. Without enough kinetic energy made Cold Fusion skeptical. Extreme high temperature made Hot Fusion very difficult to engineer. Because CIFN addresses both factors, CIFN is a more promising technique to be industrialized.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Information Fusion - Methods and Aggregation Operators

NASA Astrophysics Data System (ADS)

Torra, Vicenç

Information fusion techniques are commonly applied in Data Mining and Knowledge Discovery. In this chapter, we will give an overview of such applications considering their three main uses. This is, we consider fusion methods for data preprocessing, model building and information extraction. Some aggregation operators (i.e. particular fusion methods) and their properties are briefly described as well.

Multifocus watermarking approach based on discrete cosine transform.

PubMed

Waheed, Safa Riyadh; Alkawaz, Mohammed Hazim; Rehman, Amjad; Almazyad, Abdulaziz S; Saba, Tanzila

2016-05-01

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both "pertinent" and "immaterial" information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q(abf), standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. © 2016 Wiley Periodicals, Inc.

Summary of human social, cultural, behavioral (HSCB) modeling for information fusion panel discussion

NASA Astrophysics Data System (ADS)

Blasch, Erik; Salerno, John; Kadar, Ivan; Yang, Shanchieh J.; Fenstermacher, Laurie; Endsley, Mica; Grewe, Lynne

2013-05-01

During the SPIE 2012 conference, panelists convened to discuss "Real world issues and challenges in Human Social/Cultural/Behavioral modeling with Applications to Information Fusion." Each panelist presented their current trends and issues. The panel had agreement on advanced situation modeling, working with users for situation awareness and sense-making, and HSCB context modeling in focusing research activities. Each panelist added different perspectives based on the domain of interest such as physical, cyber, and social attacks from which estimates and projections can be forecasted. Also, additional techniques were addressed such as interest graphs, network modeling, and variable length Markov Models. This paper summarizes the panelists discussions to highlight the common themes and the related contrasting approaches to the domains in which HSCB applies to information fusion applications.

Inertial Confinement fusion targets

NASA Technical Reports Server (NTRS)

Hendricks, C. D.

1982-01-01

Inertial confinement fusion (ICF) targets are made as simple flat discs, as hollow shells or as complicated multilayer structures. Many techniques were devised for producing the targets. Glass and metal shells are made by using drop and bubble techniques. Solid hydrogen shells are also produced by adapting old methods to the solution of modern problems. Some of these techniques, problems, and solutions are discussed. In addition, the applications of many of the techniques to fabrication of ICF targets is presented.

Physics of Fusion Welding

NASA Technical Reports Server (NTRS)

Nunes, A. C., Jr.

1986-01-01

Applicabilities and limitations of three techniques analyzed. NASA technical memorandum discusses physics of electron-beam, gas/ tungsten-arc, and laser-beam welding. From comparison of capabilities and limitations of each technique with regard to various welding conditions and materials, possible to develop criteria for selecting best welding technique in specific application. All three techniques classified as fusion welding; small volume of workpiece melted by intense heat source. Heat source moved along seam, leaving in wake solid metal that joins seam edges together.

Mobile robots traversability awareness based on terrain visual sensory data fusion

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2007-04-01

In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain spatial and textural cues.

POF-IMU sensor system: A fusion between inertial measurement units and POF sensors for low-cost and highly reliable systems

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Vargas-Valencia, Laura; dos Santos, Wilian M.; Schneider, Felipe B. A.; Siqueira, Adriano A. G.; Pontes, Maria José; Frizera, Anselmo

2018-07-01

This paper presents a low cost and highly reliable system for angle measurement based on a sensor fusion between inertial and fiber optic sensors. The system consists of the sensor fusion through Kalman filter of two inertial measurement units (IMUs) and an intensity variation-based polymer optical fiber (POF) curvature sensor. In addition, the IMU was applied as a reference for a compensation technique of POF curvature sensor hysteresis. The proposed system was applied on the knee angle measurement of a lower limb exoskeleton in flexion/extension cycles and in gait analysis. Results show the accuracy of the system, where the Root Mean Square Error (RMSE) between the POF-IMU sensor system and the encoder was below 4° in the worst case and about 1° in the best case. Then, the POF-IMU sensor system was evaluated as a wearable sensor for knee joint angle assessment without the exoskeleton, where its suitability for this purpose was demonstrated. The results obtained in this paper pave the way for future applications of sensor fusion between electronic and fiber optic sensors in movement analysis.

Single-Scale Fusion: An Effective Approach to Merging Images.

PubMed

Ancuti, Codruta O; Ancuti, Cosmin; De Vleeschouwer, Christophe; Bovik, Alan C

2017-01-01

Due to its robustness and effectiveness, multi-scale fusion (MSF) based on the Laplacian pyramid decomposition has emerged as a popular technique that has shown utility in many applications. Guided by several intuitive measures (weight maps) the MSF process is versatile and straightforward to be implemented. However, the number of pyramid levels increases with the image size, which implies sophisticated data management and memory accesses, as well as additional computations. Here, we introduce a simplified formulation that reduces MSF to only a single level process. Starting from the MSF decomposition, we explain both mathematically and intuitively (visually) a way to simplify the classical MSF approach with minimal loss of information. The resulting single-scale fusion (SSF) solution is a close approximation of the MSF process that eliminates important redundant computations. It also provides insights regarding why MSF is so effective. While our simplified expression is derived in the context of high dynamic range imaging, we show its generality on several well-known fusion-based applications, such as image compositing, extended depth of field, medical imaging, and blending thermal (infrared) images with visible light. Besides visual validation, quantitative evaluations demonstrate that our SSF strategy is able to yield results that are highly competitive with traditional MSF approaches.

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Bayesian Fusion of Color and Texture Segmentations

NASA Technical Reports Server (NTRS)

Manduchi, Roberto

2000-01-01

In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach

PubMed Central

Girrbach, Fabian; Hol, Jeroen D.; Bellusci, Giovanni; Diehl, Moritz

2017-01-01

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem. PMID:28534857

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach.

PubMed

Girrbach, Fabian; Hol, Jeroen D; Bellusci, Giovanni; Diehl, Moritz

2017-05-19

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem.

Development of laser-based techniques for in situ characterization of the first wall in ITER and future fusion devices

NASA Astrophysics Data System (ADS)

Philipps, V.; Malaquias, A.; Hakola, A.; Karhunen, J.; Maddaluno, G.; Almaviva, S.; Caneve, L.; Colao, F.; Fortuna, E.; Gasior, P.; Kubkowska, M.; Czarnecka, A.; Laan, M.; Lissovski, A.; Paris, P.; van der Meiden, H. J.; Petersson, P.; Rubel, M.; Huber, A.; Zlobinski, M.; Schweer, B.; Gierse, N.; Xiao, Q.; Sergienko, G.

2013-09-01

Analysis and understanding of wall erosion, material transport and fuel retention are among the most important tasks for ITER and future devices, since these questions determine largely the lifetime and availability of the fusion reactor. These data are also of extreme value to improve the understanding and validate the models of the in vessel build-up of the T inventory in ITER and future D-T devices. So far, research in these areas is largely supported by post-mortem analysis of wall tiles. However, access to samples will be very much restricted in the next-generation devices (such as ITER, JT-60SA, W7-X, etc) with actively cooled plasma-facing components (PFC) and increasing duty cycle. This has motivated the development of methods to measure the deposition of material and retention of plasma fuel on the walls of fusion devices in situ, without removal of PFC samples. For this purpose, laser-based methods are the most promising candidates. Their feasibility has been assessed in a cooperative undertaking in various European associations under EFDA coordination. Different laser techniques have been explored both under laboratory and tokamak conditions with the emphasis to develop a conceptual design for a laser-based wall diagnostic which is integrated into an ITER port plug, aiming to characterize in situ relevant parts of the inner wall, the upper region of the inner divertor, part of the dome and the upper X-point region.

Preparation and characterization of fusion processed solid dispersions containing a viscous thermally labile polymeric carrier.

PubMed

Hughey, Justin R; Keen, Justin M; Miller, Dave A; Brough, Chris; McGinity, James W

2012-11-15

The primary aim of the present study was to investigate the ability of hydroxypropyl and methoxyl substituted cellulose ethers to stabilize supersaturated concentrations of itraconazole (ITZ), a poorly water-soluble weak base, after an acid-to-neutral pH transition. A secondary aim of the study was to evaluate the effect of fusion processes on polymer stability and molecular weight. Polymer screening studies showed that stabilization of ITZ supersaturation was related to the molecular weight of the polymer and levels of hydroxypropyl and methoxyl substitution. METHOCEL E50LV (E50LV), which is characterized as having a high melt viscosity, was selected for solid dispersion formulation studies. Hot-melt extrusion processing of E50LV based compositions resulted in high torque loads, low material throughput and polymer degradation. KinetiSol Dispersing, a novel fusion based processing technique, was evaluated as a method to prepare the solid dispersions with reduced levels of polymer degradation. An experimental design revealed that polymer molecular weight was sensitive to shearing forces and high temperatures. However, optimal processing conditions resulted in significantly reduced E50LV degradation relative to HME processing. The technique was effectively utilized to prepare homogenous solid solutions of E50LV and ITZ, characterized as having a single glass transition temperature over a wide range of drug loadings. All prepared compositions provided for a high degree of ITZ supersaturation stabilization. Copyright © 2012 Elsevier B.V. All rights reserved.

Probabilistic sparse matching for robust 3D/3D fusion in minimally invasive surgery.

PubMed

Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan

2015-01-01

Classical surgery is being overtaken by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm computed tomography (CT) and C-arm fluoroscopy are routinely used in clinical practice for intraoperative guidance. However, due to constraints regarding acquisition time and device configuration, intraoperative modalities have limited soft tissue image quality and reliable assessment of the cardiac anatomy typically requires contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a probabilistic sparse matching approach to fuse high-quality preoperative CT images and nongated, noncontrast intraoperative C-arm CT images by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the preoperative CT and mapped to the intraoperative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments on 95 clinical datasets demonstrate that our model-based fusion approach has an average execution time of 1.56 s, while the accuracy of 5.48 mm between the anchor anatomy in both images lies within expert user confidence intervals. In direct comparison with image-to-image registration based on an open-source state-of-the-art medical imaging library and a recently proposed quasi-global, knowledge-driven multi-modal fusion approach for thoracic-abdominal images, our model-based method exhibits superior performance in terms of registration accuracy and robustness with respect to both target anatomy and anchor anatomy alignment errors.

Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection.

PubMed

Ferreira, Anselmo; Felipussi, Siovani C; Alfaro, Carlos; Fonseca, Pablo; Vargas-Munoz, John E; Dos Santos, Jefersson A; Rocha, Anderson

2016-07-20

The detection of copy-move image tampering is of paramount importance nowadays, mainly due to its potential use for misleading the opinion forming process of the general public. In this paper, we go beyond traditional forgery detectors and aim at combining different properties of copy-move detection approaches by modeling the problem on a multiscale behavior knowledge space, which encodes the output combinations of different techniques as a priori probabilities considering multiple scales of the training data. Afterwards, the conditional probabilities missing entries are properly estimated through generative models applied on the existing training data. Finally, we propose different techniques that exploit the multi-directionality of the data to generate the final outcome detection map in a machine learning decision-making fashion. Experimental results on complex datasets, comparing the proposed techniques with a gamut of copy-move detection approaches and other fusion methodologies in the literature show the effectiveness of the proposed method and its suitability for real-world applications.

Nonperturbative measurement of the local magnetic field using pulsed polarimetry for fusion reactor conditions (invited)a)

NASA Astrophysics Data System (ADS)

Smith, Roger J.

2008-10-01

A novel diagnostic technique for the remote and nonperturbative sensing of the local magnetic field in reactor relevant plasmas is presented. Pulsed polarimetry [Patent No. 12/150,169 (pending)] combines optical scattering with the Faraday effect. The polarimetric light detection and ranging (LIDAR)-like diagnostic has the potential to be a local Bpol diagnostic on ITER and can achieve spatial resolutions of millimeters on high energy density (HED) plasmas using existing lasers. The pulsed polarimetry method is based on nonlocal measurements and subtle effects are introduced that are not present in either cw polarimetry or Thomson scattering LIDAR. Important features include the capability of simultaneously measuring local Te, ne, and B∥ along the line of sight, a resiliency to refractive effects, a short measurement duration providing near instantaneous data in time, and location for real-time feedback and control of magnetohydrodynamic (MHD) instabilities and the realization of a widely applicable internal magnetic field diagnostic for the magnetic fusion energy program. The technique improves for higher neB∥ product and higher ne and is well suited for diagnosing the transient plasmas in the HED program. Larger devices such as ITER and DEMO are also better suited to the technique, allowing longer pulse lengths and thereby relaxing key technology constraints making pulsed polarimetry a valuable asset for next step devices. The pulsed polarimetry technique is clarified by way of illustration on the ITER tokamak and plasmas within the magnetized target fusion program within present technological means.

Mass Producing Targets for Nuclear Fusion

NASA Technical Reports Server (NTRS)

Wang, T. G.; Elleman, D. D.; Kendall, J. M.

1983-01-01

Metal-encapsulating technique advances prospects of controlling nuclear fusion. Prefilled fusion targets form at nozzle as molten metal such as tin flows through outer channel and pressurized deuterium/tritium gas flows through inner channel. Molten metal completely encloses gas charge as it drops off nozzle.

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

Guo Xiaoming

The dominated process of controlled fusion is to let nuclei gain enough kinetic energy to overcome Coulomb barrier. As a result, a fusion scheme can consider two factors in its design: to increase kinetic energy of nuclei and to alter the Coulomb barrier. Cold Fusion and Hot fusion are all one-factor schemes while Intermediate Fusion is a twofactors scheme. This made CINF kinetically superior. Cold Fusion reduces deuteron-deuteron distance, addressing Coulomb barrier, and Hot Fusion heat up plasma into extreme high temperature, addressing kinetic energy. Without enough kinetic energy made Cold Fusion skeptical. Extreme high temperature made Hot Fusion verymore » difficult to engineer. Because CIFN addresses both factors, CIFN is a more promising technique to be industrialized.« less

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

Comparison of atlas-based techniques for whole-body bone segmentation.

PubMed

Arabi, Hossein; Zaidi, Habib

2017-02-01

We evaluate the accuracy of whole-body bone extraction from whole-body MR images using a number of atlas-based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI-guided derivation of PET attenuation maps in whole-body PET/MRI. To this end, a variety of atlas-based segmentation strategies commonly used in medical image segmentation and pseudo-CT generation were implemented and evaluated in terms of whole-body bone segmentation accuracy. Bone segmentation was performed on 23 whole-body CT/MR image pairs via leave-one-out cross validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel-wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross-correlation (NCC) and mean square distance (MSD) as image similarity measures for calculating the weighting factors, along with other atlas-dependent algorithms, such as (v) shape-based averaging (SBA) and (vi) Hofmann's pseudo-CT generation method. The performance evaluation of the different segmentation techniques was carried out in terms of estimating bone extraction accuracy from whole-body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice criterion, global weighting atlas fusion methods provided moderate improvement of whole-body bone segmentation (DSC= 0.65 ± 0.05) compared to non-weighted IA (DSC= 0.60 ± 0.02). The local weighed atlas fusion approach using the MSD similarity measure outperformed the other strategies by achieving a DSC of 0.81 ± 0.03 while using the NCC and NMI measures resulted in a DSC of 0.78 ± 0.05 and 0.75 ± 0.04, respectively. Despite very long computation time, the extracted bone obtained from both SBA (DSC= 0.56 ± 0.05) and Hofmann's methods (DSC= 0.60 ± 0.02) exhibited no improvement compared to non-weighted IA. Finding the optimum parameters for implementation of the atlas fusion approach, such as weighting factors and image similarity patch size, have great impact on the performance of atlas-based segmentation approaches. The voxel-wise atlas fusion approach exhibited excellent performance in terms of cancelling out the non-systematic registration errors leading to accurate and reliable segmentation results. Denoising and normalization of MR images together with optimization of the involved parameters play a key role in improving bone extraction accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems.

PubMed

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martin, Consuelo; Marcello-Ruiz, Javier; Garcia-Pedrero, Angel; Rodriguez-Esparragon, Dionisio

2017-01-25

Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources' reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ' à trous ' through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ' à trous ' through fractal dimension maps as the best fusion algorithm for this ecosystem.

Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems

PubMed Central

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martin, Consuelo; Marcello-Ruiz, Javier; Garcia-Pedrero, Angel; Rodriguez-Esparragon, Dionisio

2017-01-01

Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources’ reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ‘à trous’ through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ‘à trous’ through fractal dimension maps as the best fusion algorithm for this ecosystem. PMID:28125055

A hybrid localization technique for patient tracking.

PubMed

Rodionov, Denis; Kolev, George; Bushminkin, Kirill

2013-01-01

Nowadays numerous technologies are employed for tracking patients and assets in hospitals or nursing homes. Each of them has advantages and drawbacks. For example, WiFi localization has relatively good accuracy but cannot be used in case of power outage or in the areas with poor WiFi coverage. Magnetometer positioning or cellular network does not have such problems but they are not as accurate as localization with WiFi. This paper describes technique that simultaneously employs different localization technologies for enhancing stability and average accuracy of localization. The proposed algorithm is based on fingerprinting method paired with data fusion and prediction algorithms for estimating the object location. The core idea of the algorithm is technology fusion using error estimation methods. For testing accuracy and performance of the algorithm testing simulation environment has been implemented. Significant accuracy improvement was showed in practical scenarios.

Multi-Source Sensor Fusion for Small Unmanned Aircraft Systems Using Fuzzy Logic

NASA Technical Reports Server (NTRS)

Cook, Brandon; Cohen, Kelly

2017-01-01

As the applications for using small Unmanned Aircraft Systems (sUAS) beyond visual line of sight (BVLOS) continue to grow in the coming years, it is imperative that intelligent sensor fusion techniques be explored. In BVLOS scenarios the vehicle position must accurately be tracked over time to ensure no two vehicles collide with one another, no vehicle crashes into surrounding structures, and to identify off-nominal scenarios. Therefore, in this study an intelligent systems approach is used to estimate the position of sUAS given a variety of sensor platforms, including, GPS, radar, and on-board detection hardware. Common research challenges include, asynchronous sensor rates and sensor reliability. In an effort to realize these challenges, techniques such as a Maximum a Posteriori estimation and a Fuzzy Logic based sensor confidence determination are used.

South Florida Everglades: satellite image map

USGS Publications Warehouse

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant.

PubMed

Camplani, M; Malizia, A; Gelfusa, M; Barbato, F; Antonelli, L; Poggi, L A; Ciparisse, J F; Salgado, L; Richetta, M; Gaudio, P

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant

NASA Astrophysics Data System (ADS)

Camplani, M.; Malizia, A.; Gelfusa, M.; Barbato, F.; Antonelli, L.; Poggi, L. A.; Ciparisse, J. F.; Salgado, L.; Richetta, M.; Gaudio, P.

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

A scale space feature based registration technique for fusion of satellite imagery

NASA Technical Reports Server (NTRS)

Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

1997-01-01

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

NASA Astrophysics Data System (ADS)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

PubMed Central

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain–computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method. PMID:28558002

Virtual pathology of cervical radiculopathy based on 3D MR/CT fusion images: impingement, flattening or twisted condition of the compressed nerve root in three cases.

PubMed

Kamogawa, Junji; Kato, Osamu; Morizane, Tatsunori; Hato, Taizo

2015-01-01

There have been several imaging studies of cervical radiculopathy, but no three-dimensional (3D) images have shown the path, position, and pathological changes of the cervical nerve roots and spinal root ganglion relative to the cervical bony structure. The objective of this study was to introduce a technique that enables the virtual pathology of the nerve root to be assessed using 3D magnetic resonance (MR)/computed tomography (CT) fusion images that show the compression of the proximal portion of the cervical nerve root by both the herniated disc and the preforaminal or foraminal bony spur in patients with cervical radiculopathy. MR and CT images were obtained from three patients with cervical radiculopathy. 3D MR images were placed onto 3D CT images using a computer workstation. The entire nerve root could be visualized in 3D with or without the vertebrae. The most important characteristic evident on the images was flattening of the nerve root by a bony spur. The affected root was constricted at a pre-ganglion site. In cases of severe deformity, the flattened portion of the root seemed to change the angle of its path, resulting in twisted condition. The 3D MR/CT fusion imaging technique enhances visualization of pathoanatomy in cervical hidden area that is composed of the root and intervertebral foramen. This technique provides two distinct advantages for diagnosis of cervical radiculopathy. First, the isolation of individual vertebra clarifies the deformities of the whole root groove, including both the uncinate process and superior articular process in the cervical spine. Second, the tortuous or twisted condition of a compressed root can be visualized. The surgeon can identify the narrowest face of the root if they view the MR/CT fusion image from the posterolateral-inferior direction. Surgeons use MR/CT fusion images as a pre-operative map and for intraoperative navigation. The MR/CT fusion images can also be used as educational materials for all hospital staff and for patients and patients' families who provide informed consent for treatments.

Fusion with stem cell makes the hepatocellular carcinoma cells similar to liver tumor-initiating cells.

PubMed

Wang, Ran; Chen, Shuxun; Li, Changxian; Ng, Kevin Tak Pan; Kong, Chi-wing; Cheng, Jinping; Cheng, Shuk Han; Li, Ronald A; Lo, Chung Mau; Man, Kwan; Sun, Dong

2016-02-04

Cell fusion is a fast and highly efficient technique for cells to acquire new properties. The fusion of somatic cells with stem cells can reprogram somatic cells to a pluripotent state. Our research on the fusion of stem cells and cancer cells demonstrates that the fused cells can exhibit stemness and cancer cell-like characteristics. Thus, tumor-initiating cell-like cells are generated. We employed laser-induced single-cell fusion technique to fuse the hepatocellular carcinoma cells and human embryonic stem cells (hESC). Real-time RT-PCR, flow cytometry and in vivo tumorigenicity assay were adopted to identify the gene expression difference. We successfully produced a fused cell line that coalesces the gene expression information of hepatocellular carcinoma cells and stem cells. Experimental results showed that the fused cells expressed cancer and stemness markers as well as exhibited increased resistance to drug treatment and enhanced tumorigenesis. Fusion with stem cells transforms liver cancer cells into tumor initiating-like cells. Results indicate that fusion between cancer cell and stem cell may generate tumor initiating-like cells.

Morphological filtering and multiresolution fusion for mammographic microcalcification detection

NASA Astrophysics Data System (ADS)

Chen, Lulin; Chen, Chang W.; Parker, Kevin J.

1997-04-01

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

The role of data fusion in predictive maintenance using digital twin

NASA Astrophysics Data System (ADS)

Liu, Zheng; Meyendorf, Norbert; Mrad, Nezih

2018-04-01

Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called "Digital Twin." The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

Mapping Forest Height in Gabon Using UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Lidar Fusion

NASA Astrophysics Data System (ADS)

Simard, M.; Denbina, M. W.

2017-12-01

Using data collected by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Land, Vegetation, and Ice Sensor (LVIS) lidar, we have estimated forest canopy height for a number of study areas in the country of Gabon using a new machine learning data fusion approach. Using multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data collected by UAVSAR, forest heights can be estimated using the random volume over ground model. In the case of multi-baseline UAVSAR data consisting of many repeat passes with spatially separated flight tracks, we can estimate different forest height values for each different image pair, or baseline. In order to choose the best forest height estimate for each pixel, the baselines must be selected or ranked, taking care to avoid baselines with unsuitable spatial separation, or severe temporal decorrelation effects. The current baseline selection algorithms in the literature use basic quality metrics derived from the PolInSAR data which are not necessarily indicative of the true height accuracy in all cases. We have developed a new data fusion technique which treats PolInSAR baseline selection as a supervised classification problem, where the classifier is trained using a sparse sampling of lidar data within the PolInSAR coverage area. The classifier uses a large variety of PolInSAR-derived features as input, including radar backscatter as well as features based on the PolInSAR coherence region shape and the PolInSAR complex coherences. The resulting data fusion method produces forest height estimates which are more accurate than a purely radar-based approach, while having a larger coverage area than the input lidar training data, combining some of the strengths of each sensor. The technique demonstrates the strong potential for forest canopy height and above-ground biomass mapping using fusion of PolInSAR with data from future spaceborne lidar missions such as the upcoming Global Ecosystems Dynamics Investigation (GEDI) lidar.

The quest for a z-pinch based fusion energy source—a historical perspective

NASA Astrophysics Data System (ADS)

Sethian, John

1997-05-01

Ever since 1958, when Oscar Anderson observed copious neutrons emanating from a "magnetically self-constricted column of deuterium plasma," scientists have attempted to develop the simple linear pinch into a fusion power source. After all, simple calculations show that if one can pass a current of slightly less than 2 million amperes through a stable D-T plasma, then one could achieve not just thermonuclear break-even, but thermonuclear gain. Moreover, several reactor studies have shown that a simple linear pinch could be the basis for a very attractive fusion system. The problem is, of course, that the seemingly simple act of passing 2 MA through a stable pinch has proven to be quite difficult to accomplish. The pinch tends to disrupt due to instabilities, either by the m=0 (sausage) or m=1 (kink) modes. Curtailing the growth of these instabilities has been the primary thrust of z-pinch fusion research, and over the years a wide variety of formation techniques have been tried. The early pinches were driven by relatively slow capacitive discharges and were formed by imploding a plasma column. The advent of fast pulsed power technology brought on a whole new repertoire of formation techniques, including: fast implosions, laser or field-enhanced breakdown in a uniform volume of gas, a discharge inside a small capillary, a frozen deuterium fiber isolated by vacuum, and staged concepts in which one pinch implodes upon another. And although none of these have yet to be successful, some have come tantalizingly close. This paper will review the history of this four-decade long quest for fusion power.

Intraoperative mechanical bone strength determination in tibiotalocalcaneal fusion: a biomechanical investigation.

PubMed

Klos, Kajetan; Windolf, Markus; Schwieger, Karsten; Kuhn, Philipp; Hänni, Markus; Gueorguiev, Boyko; Hofmann, Gunther O; Mückley, Thomas

2009-12-01

Bone strength is currently measured with indirect techniques. We investigated the use of an intraoperative mechanical measurement for local bone strength determination and prediction of intramedullary-nail fusion failure. We investigated whether intraoperative local bone strength determination may be useful to the surgeon in predicting intramedullary nail hindfoot fusion performance. In seven human specimens, bone mineral density (BMD) was determined with qCT. A device (DensiProbe) specially devised for nailed tibiotalocalcaneal arthrodesis (TTCA) was inserted at the intended calcaneal screw sites of an intramedullary nail, and the cancellous break-away torque was measured. The constructs were then cyclically loaded to failure in dorsiflexion-plantarfexion. The BMD range was wide (42.8 to 185.9 mg HA/cm(3)). The proximal-screw site peak torque was 0.47 to 1.61 Nm; distal-screw site peak torque was 0.24 to 1.06 Nm. The number of cycles to failure correlated with peak torque both proximally (p = 0.021; r(2) = 0.69) and distally (p = 0.001; r(2) = 0.92). Proximally, peak torque did not correlate with BMD (p = 0.060; r(2) = 0.54); distally, it correlated significantly (p = 0.003; r(2) = 0.86). DensiProbe measurements can be used in the hindfoot to assess bone strength. In this study, specimens that failed early could be identified. However, in clinical practice fusion failure is multifactorial in origin, and failure prediction cannot be based upon peak torque measurements alone. The technique described here may be of use to give an intraoperative decision aid to predict intramedullary nail hindfoot fusion performance.

Minimally invasive trans-sacral approach to L5-S1 interbody fusion: Preliminary results from 1 center and review of the literature.

PubMed

Bradley, W Daniel; Hisey, Michael S; Verma-Kurvari, Sunita; Ohnmeiss, Donna D

2012-01-01

Lumbar interbody fusion has long been used for the treatment of painful degenerative spinal conditions. The anterior approach is not feasible in some patients, and the posterior approach is associated with a risk of neural complications and possibly muscle injury. A trans-sacral technique was developed that allows access to the L5-S1 disc space. The purposes of this study were to investigate the clinical outcome of trans-sacral interbody fusion in a consecutive series of patients from 1 center and to perform a comprehensive review of the literature on this procedure. A literature search using PubMed was performed to identify articles published on trans-sacral axial lumbar interbody fusion (AxiaLIF). Articles reviewed included biomechanical testing, feasibility of the technique, and clinical results. The data from our center were collected retrospectively from charts for the consecutive series, beginning with the first case, of all patients undergoing fusion using the AxiaLIF technique. In most cases, posterior instrumentation was also used. A total of 41 patients with at least 6 months' follow-up were included (mean follow-up, 22.2 months). The primary clinical outcome measures were visual analog scales separately assessing back and leg pain and the Oswestry Disability Index. Radiographic assessment of fusion was also performed. In the group of 28 patients undergoing single-level AxiaLIF combined with posterior fusion, the visual analog scale scores assessing back and leg pain and mean Oswestry Disability Index scores improved significantly (P < .01). In the remaining 13 patients, back pain improved significantly with a trend for improvement in leg pain. Reoperation occurred in 19.5% of patients; in half of these, reoperation was not related to the anterior procedure. A review of the literature found that the AxiaLIF technique was similar to other fusion techniques with respect to biomechanical properties and produced acceptable clinical outcomes, although results varied among studies. The AxiaLIF approach allows access to the L5-S1 interspace without violating the annulus or longitudinal ligaments and with minimal risk to dorsal neural elements. It may be a viable alternative to other approaches to interbody fusion at the L5-S1 level. It is important that the patients be selected carefully and surgeons are familiar with the presacral anatomy and the surgical approach.

Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification.

PubMed

Arvanaghi, Roghayyeh; Daneshvar, Sabalan; Seyedarabi, Hadi; Goshvarpour, Atefeh

2017-11-01

Each of Electrocardiogram (ECG) and Atrial Blood Pressure (ABP) signals contain information of cardiac status. This information can be used for diagnosis and monitoring of diseases. The majority of previously proposed methods rely only on ECG signal to classify heart rhythms. In this paper, ECG and ABP were used to classify five different types of heart rhythms. To this end, two mentioned signals (ECG and ABP) have been fused. These physiological signals have been used from MINIC physioNet database. ECG and ABP signals have been fused together on the basis of the proposed Discrete Wavelet Transformation fusion technique. Then, some frequency features were extracted from the fused signal. To classify the different types of cardiac arrhythmias, these features were given to a multi-layer perceptron neural network. In this study, the best results for the proposed fusion algorithm were obtained. In this case, the accuracy rates of 96.6%, 96.9%, 95.6% and 93.9% were achieved for two, three, four and five classes, respectively. However, the maximum classification rate of 89% was obtained for two classes on the basis of ECG features. It has been found that the higher accuracy rates were acquired by using the proposed fusion technique. The results confirmed the importance of fusing features from different physiological signals to gain more accurate assessments. Copyright © 2017 Elsevier B.V. All rights reserved.

On the path to fusion energy

NASA Astrophysics Data System (ADS)

Tabak, M.

2016-10-01

There is a need to develop alternate energy sources in the coming century because fossil fuels will become depleted and their use may lead to global climate change. Inertial fusion can become such an energy source, but significant progress must be made before its promise is realized. The high-density approach to inertial fusion suggested by Nuckolls et al. leads reaction chambers compatible with civilian power production. Methods to achieve the good control of hydrodynamic stability and implosion symmetry required to achieve these high fuel densities will be discussed. Fast Ignition, a technique that achieves fusion ignition by igniting fusion fuel after it is assembled, will be described along with its gain curves. Fusion costs of energy for conventional hotspot ignition will be compared with those of Fast Ignition and their capital costs compared with advanced fission plants. Finally, techniques that may improve possible Fast Ignition gains by an order of magnitude and reduce driver scales by an order of magnitude below conventional ignition requirements are described.

FusionArc optimization: a hybrid volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) planning strategy.

PubMed

Matuszak, Martha M; Steers, Jennifer M; Long, Troy; McShan, Daniel L; Fraass, Benedick A; Romeijn, H Edwin; Ten Haken, Randall K

2013-07-01

To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT. A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT∕hybrid beams. The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%-43.7% fewer MU∕Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost--32.9%-55.2% compared to single-arc VMAT--the decrease in MU∕Gy compared to IMRT was noticeably smaller at 12.2%-18.5%, when compared to IMRT. A hybrid VMAT∕IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom. This optimization method will allow patients to be simultaneously planned for dosimetric quality and delivery efficiency without switching between delivery techniques. Example phantom and clinical cases suggest that the conversion of only three VMAT segments to modulated beams may result in a good combination of quality and efficiency.

Technique for writing of fiber Bragg gratings over or near preliminary formed macro-structure defects in silica optical fibers

NASA Astrophysics Data System (ADS)

Evtushenko, Alexander S.; Faskhutdinov, Lenar M.; Kafarova, Anastasia M.; Kazakov, Vadim S.; Kuznetzov, Artem A.; Minaeva, Alina Yu.; Sevruk, Nikita L.; Nureev, Ilnur I.; Vasilets, Alexander A.; Andreev, Vladimir A.; Morozov, Oleg G.; Burdin, Vladimir A.; Bourdine, Anton V.

2017-04-01

This work presents method for performing precision macro-structure defects "tapers" and "up-tapers" written in conventional silica telecommunication multimode optical fibers by commercially available field fusion splicer with modified software settings and following writing fiber Bragg gratings over or near them. We developed technique for macrodefect geometry parameters estimation via analysis of photo-image performed after defect writing and displayed on fusion splicer screen. Some research results of defect geometry dependence on fusion current and fusion time values re-set in splicer program are represented that provided ability to choose their "the best" combination. Also experimental statistical researches concerned with "taper" and "up-taper" diameter stability as well as their insertion loss values during their writing under fixed corrected splicer program parameters were performed. We developed technique for FBG writing over or near macro-structure defect. Some results of spectral response measurements produced for short-length samples of multimode optical fiber with fiber Bragg gratings written over and near macro-defects prepared by using proposed technique are presented.

Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT.

PubMed

Mazaheri, Samaneh; Sulaiman, Puteri Suhaiza; Wirza, Rahmita; Dimon, Mohd Zamrin; Khalid, Fatimah; Moosavi Tayebi, Rohollah

2015-01-01

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.

A systematic review of clinical outcomes in surgical treatment of adult isthmic spondylolisthesis.

PubMed

Noorian, Shaya; Sorensen, Karen; Cho, Woojin

2018-05-07

A variety of surgical methods are available for the treatment of adult isthmic spondylolisthesis, but there is no consensus regarding their relative effects on clinical outcomes. To compare the effects of different surgical techniques on clinical outcomes in adult isthmic spondylolisthesis. Systematic Review PATIENT SAMPLE: A total of 1,538 patients from six randomized clinical trials and nine observational studies comparing different surgical treatments in adult isthmic spondylolisthesis. Primary outcome measures of interest included differences in pre- versus post-surgical assessments of pain, functional disability, and overall health as assessed by validated pain rating scales and questionnaires. Secondary outcome measures of interest included intraoperative blood loss, length of hospital stay, surgery duration, reoperation rates, and complication rates. A search of the literature was performed in September, 2017 for relevant comparative studies published in the prior 10-year period in the following databases: PubMed, Embase, Web of Science, and ClinicalTrials.Gov. PRISMA guidelines were followed and studies were included/excluded based on strict predetermined criteria. Quality appraisal was conducted using the Newcastle-Ottawa Scale (NOS) for observational studies and the Cochrane Collaboration's risk of bias assessment tool for randomized clinical trials. The authors received no funding support to conduct this review. A total of 15 studies (6 randomized clinical trials and 9 observational studies) were included for full text review, a majority of which only included cases of low-grade isthmic spondylolisthesis. 1 study examined the effects of adding pedicle screw fixation (PS) to posterolateral fusion (PLF) and 2 studies examined the effects of adding reduction to interbody fusion (IF) + PS on clinical outcomes. 5 studies compared PLF, 4 with and 1 without PS, to IF + PS. Additionally, 3 studies compared circumferential fusion (IF + PS + PLF) to IF + PS and 1 study compared circumferential fusion to PLF + PS. 3 studies compared clinical outcomes among different IF + PS techniques (ALIF + PS vs. PLIF + PS vs TLIF + PS) without PLF. As per the Cochrane Collaboration's risk of bias assessment tool, 4 randomized clinical trials had an overall low risk of bias, 1 randomized clinical trial had an unclear risk of bias, and 1 randomized clinical trial had a high risk of bias. As per the Newcastle-Ottawa scale, 3 observational studies were of overall good quality, 4 observational studies were of fair quality, and 2 observational studies were of poor quality. Available studies provide strong evidence that the addition of reduction to fusion does not result in better clinical outcomes of pain and function in low-grade isthmic spondylolisthesis. Evidence also suggests that there is no significant difference between interbody fusion (IF + PS) and posterior fusion (PLF +/- PS) in outcomes of pain, function, and complication rates at follow-up points up to approximately 3 years in cases of low-grade slips. However, studies with longer follow-up points suggest that interbody fusion (IF + PS) may perform better in these same measures at later follow-up points. Available evidence also suggests no difference between circumferential fusion (IF + PS + PLF) and interbody fusion (IF + PS) in outcomes of pain and function in low-grade slips, but circumferential fusion has been associated with greater intraoperative blood loss, longer surgery duration, and longer hospital stays. In terms of clinical outcomes, insufficient evidence is available to assess the utility of adding PS to PLF, the relative efficacy of different interbody fusion (IF + PS) techniques (ALIF + PS vs. TLIF + PS vs. PLIF + PS), and the relative efficacy of circumferential fusion and posterior fusion (PLF + PS). Copyright © 2018. Published by Elsevier Inc.

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

Tools and Methods for the Registration and Fusion of Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

2010-01-01

Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

Leak testing and repair of fusion devices

NASA Astrophysics Data System (ADS)

Kozman, T. A.

1983-06-01

The leak testing, reporting and vacuum leak repair techniques of the MPTF yin-yang number one magnet system, the world's largest superconducting magnet system, are discussed. Based on this experience, techniques are developed for testing and repairing leaks on the 42 MPTF-B magnets. The leak hunting techniques for the yin-yang magnet systems were applied to two helium circuits (the coil bundle and guard vacuum; both require helium flow for magnet cooldown). Additionally, during MPTF-B operation there are warm water plasma shields and piping that require leak checking.

Knee fusion--a new technique using an old Belgian surgical approach and a new intramedullary nail.

PubMed

Alt, V; Seligson, D

2001-02-01

Knee arthrodesis is a useful procedure in difficult cases such as failed total knee arthroplasty, severe articular trauma, bone tumors, and infected knee joints. The most common techniques for knee fusion include external fixation and intramedullary nailing. Küntscher's nail is driven antegrade from the intertrochanteric region into the knee. We describe a new technique for knee arthrodesis using a new intramedullary nail and an old Belgian surgical approach to the knee joint published by Lambotte in 1913. This approach provides excellent exposure for the implantation of the nail by osteotomizing the patella vertically. The nail is implanted using HeyGroves method, whereby the nail is inserted retrograde into the femur and pulled distally anterograde into the tibia. We now use this technique as our standard procedure for knee fusion.

Evaluation of a speaker identification system with and without fusion using three databases in the presence of noise and handset effects

NASA Astrophysics Data System (ADS)

S. Al-Kaltakchi, Musab T.; Woo, Wai L.; Dlay, Satnam; Chambers, Jonathon A.

2017-12-01

In this study, a speaker identification system is considered consisting of a feature extraction stage which utilizes both power normalized cepstral coefficients (PNCCs) and Mel frequency cepstral coefficients (MFCC). Normalization is applied by employing cepstral mean and variance normalization (CMVN) and feature warping (FW), together with acoustic modeling using a Gaussian mixture model-universal background model (GMM-UBM). The main contributions are comprehensive evaluations of the effect of both additive white Gaussian noise (AWGN) and non-stationary noise (NSN) (with and without a G.712 type handset) upon identification performance. In particular, three NSN types with varying signal to noise ratios (SNRs) were tested corresponding to street traffic, a bus interior, and a crowded talking environment. The performance evaluation also considered the effect of late fusion techniques based on score fusion, namely, mean, maximum, and linear weighted sum fusion. The databases employed were TIMIT, SITW, and NIST 2008; and 120 speakers were selected from each database to yield 3600 speech utterances. As recommendations from the study, mean fusion is found to yield overall best performance in terms of speaker identification accuracy (SIA) with noisy speech, whereas linear weighted sum fusion is overall best for original database recordings.

Retinal vessel enhancement based on the Gaussian function and image fusion

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Obreja, Cristian Dragoş

2017-01-01

The Gaussian function is essential in the construction of the Frangi and COSFIRE (combination of shifted filter responses) filters. The connection of the broken vessels and an accurate extraction of the vascular structure is the main goal of this study. Thus, the outcome of the Frangi and COSFIRE edge detection algorithms are fused using the Dempster-Shafer algorithm with the aim to improve detection and to enhance the retinal vascular structure. For objective results, the average diameters of the retinal vessels provided by Frangi, COSFIRE and Dempster-Shafer fusion algorithms are measured. These experimental values are compared to the ground truth values provided by manually segmented retinal images. We prove the superiority of the fusion algorithm in terms of image quality by using the figure of merit objective metric that correlates the effects of all post-processing techniques.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

Clinical outcome of trans-sacral interbody fusion after partial reduction for high-grade l5-s1 spondylolisthesis.

PubMed

Smith, J A; Deviren, V; Berven, S; Kleinstueck, F; Bradford, D S

2001-10-15

A clinical retrospective study was conducted. To evaluate the clinical and radiographic outcome of reduction followed by trans-sacral interbody fusion for high-grade spondylolisthesis. In situ posterior interbody fusion with fibula allograft has improved the fusion rates for patients with high-grade spondylolisthesis. The use of this technique in conjunction with partial reduction has not been reported. Nine consecutive patients underwent treatment of high-grade (Grade 3 or 4) spondylolisthesis with partial reduction followed by posterior interbody fusion using cortical allograft. The average age at the time of surgery was 27 years (range, 8-51 years), and the average follow-up period was 43 months (range, 24-72 months). Before surgery, eight patients had low back pain, seven patients had radiating leg pain, and five patients had hamstring tightness. The average grade of spondylolisthesis by Meyerding grading was 3.9 (range, 3-5). Charts and radiographs were evaluated, and outcomes were collected by use of the modified SRS outcomes instrument. Radiographic indexes demonstrated significant improvement with partial reduction and fusion. The slip angle, as measured from the inferior endplate of L5, improved from 41.2 degrees (range, 24-82 degrees ) before surgery to 21 degrees (range, 5-40 degrees ) after surgery. All the patients were extremely or somewhat satisfied with surgery. The two patients who underwent this operation without initial instrumentation experienced fractures of their interbody grafts. Both of these patients underwent repair of the pseudarthrosis with placement of trans-sacral pedicle screw instrumentation and subsequent fusion. Partial reduction followed by posterior interbody fusion is an effective technique for the management of high-grade spondylolisthesis in pediatric and adult patient populations, as assessed by radiographic and clinical criteria. Pedicle screw instrumentation with the sacral screws capturing L5 is recommended when this technique is used for the treatment of high-grade spondylolisthesis. According to the clinical and radiographic results from this study, partial reduction and posterior fibula interbody fusion supplemented with pedicle screw instrumentation is an effective technique for select patients with high-grade spondylolisthesis at L5-S1.

Integrated Data Analysis for Fusion: A Bayesian Tutorial for Fusion Diagnosticians

NASA Astrophysics Data System (ADS)

Dinklage, Andreas; Dreier, Heiko; Fischer, Rainer; Gori, Silvio; Preuss, Roland; Toussaint, Udo von

2008-03-01

Integrated Data Analysis (IDA) offers a unified way of combining information relevant to fusion experiments. Thereby, IDA meets with typical issues arising in fusion data analysis. In IDA, all information is consistently formulated as probability density functions quantifying uncertainties in the analysis within the Bayesian probability theory. For a single diagnostic, IDA allows the identification of faulty measurements and improvements in the setup. For a set of diagnostics, IDA gives joint error distributions allowing the comparison and integration of different diagnostics results. Validation of physics models can be performed by model comparison techniques. Typical data analysis applications benefit from IDA capabilities of nonlinear error propagation, the inclusion of systematic effects and the comparison of different physics models. Applications range from outlier detection, background discrimination, model assessment and design of diagnostics. In order to cope with next step fusion device requirements, appropriate techniques are explored for fast analysis applications.

Hybrid Decompression Technique Versus Anterior Cervical Corpectomy and Fusion for Treating Multilevel Cervical Spondylotic Myelopathy: Which One Is Better?

PubMed

Liu, Jia-Ming; Peng, Hong-Wei; Liu, Zhi-Li; Long, Xin-Hua; Yu, Yan-Qing; Huang, Shan-Hu

2015-12-01

The hybrid decompression technique (corpectomy combined with discectomy) and anterior cervical corpectomy with fusion (ACCF) both provide good neurological recovery and disease stabilization for the treatment of multilevel cervical spondylotic myelopathy (CSM). However, no single study has been large enough to determine definitively which one is superior for this condition. A meta-analysis was conducted to compare the clinical efficacy and safety of the hybrid decompression technique versus ACCF for the treatment of multilevel CSM. Electronic databases such as PubMed, MEDLINE, EMBASE, Google Scholar, and the Cochrane Library were selected to search for potentially relevant trials up to April 2015 that compared the outcomes of the hybrid technique with ACCF for the treatment of multilevel CSM. Data extraction and quality assessment were performed according to Cochrane Collaboration guidelines. The outcome assessments were duration of surgery, blood loss, Cobb angle of C2-C7, segment angle, fusion rate, Japanese Orthopedics Association score, Neck Disability Index, and complications. The results were expressed as the odds ratio (OR) for dichotomous outcomes and the mean difference (MD) for continuous outcomes with a 95% confidence interval (CI). Five controlled clinical trials published between 2009 and 2013, involving 356 patients (hybrid, 196; ACCF, 160) with 3- or 4-level CSM were retrieved in this study. Overall, there were significant differences between the 2 treatment groups for blood loss (MD = -38.69, 95% CI = -54.62 to -22.76, P < 0.01), fusion rate (OR = 2.56, 95% CI = 1.11 to 5.93, P = 0.03), and complications (OR = 0.25, 95% CI = 0.15 to 0.43, P < 0.01). However, no significant differences were found for duration of surgery (MD = -4.50, 95% CI = -22.902 to 13.91, P = 0.63), Cobb angle of C2-C7 after surgery (MD = 3.32, 95% CI = -3.72 to 10.37, P = 0.35), segment angle after surgery (MD = 2.87, 95% CI = -2.47 to 8.21, P = 0.29), Japanese Orthopedics Association score (MD = -0.07, 95% CI = -0.36 to 0.22, P = 0.62), or Neck Disability Index (MD = -0.86, 95% CI = -3.26 to 1.54, P = 0.48). Based on this meta-analysis, both the hybrid technique and ACCF can achieve good results for CSM. However, the hybrid technique is associated with significantly less blood loss, complications, and a higher fusion rate than ACCF. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of buried objects by fusing dual-band infrared images

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-11-01

We have conducted experiments to demonstrate the enhanced detectability of buried land mines using sensor fusion techniques. Multiple sensors, including visible imagery, infrared imagery, and ground penetrating radar (GPR), have been used to acquire data on a number of buried mines and mine surrogates. Because the visible wavelength and GPR data are currently incomplete. This paper focuses on the fusion of two-band infrared images. We use feature-level fusion and supervised learning with the probabilistic neural network (PNN) to evaluate detection performance. The novelty of the work lies in the application of advanced target recognition algorithms, the fusion of dual-band infraredmore » images and evaluation of the techniques using two real data sets.« less

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

Measuring situational awareness and resolving inherent high-level fusion obstacles

NASA Astrophysics Data System (ADS)

Sudit, Moises; Stotz, Adam; Holender, Michael; Tagliaferri, William; Canarelli, Kathie

2006-04-01

Information Fusion Engine for Real-time Decision Making (INFERD) is a tool that was developed to supplement current graph matching techniques in Information Fusion models. Based on sensory data and a priori models, INFERD dynamically generates, evolves, and evaluates hypothesis on the current state of the environment. The a priori models developed are hierarchical in nature lending them to a multi-level Information Fusion process whose primary output provides a situational awareness of the environment of interest in the context of the models running. In this paper we look at INFERD's multi-level fusion approach and provide insight on the inherent problems such as fragmentation in the approach and the research being undertaken to mitigate those deficiencies. Due to the large variance of data in disparate environments, the awareness of situations in those environments can be drastically different. To accommodate this, the INFERD framework provides support for plug-and-play fusion modules which can be developed specifically for domains of interest. However, because the models running in INFERD are graph based, some default measurements can be provided and will be discussed in the paper. Among these are a Depth measurement to determine how much danger is presented by the action taking place, a Breadth measurement to gain information regarding the scale of an attack that is currently happening, and finally a Reliability measure to tell the user the credibility of a particular hypothesis. All of these results will be demonstrated in the Cyber domain where recent research has shown to be an area that is welldefined and bounded, so that new models and algorithms can be developed and evaluated.

FT-MIR and NIR spectral data fusion: a synergetic strategy for the geographical traceability of Panax notoginseng.

PubMed

Li, Yun; Zhang, Jin-Yu; Wang, Yuan-Zhong

2018-01-01

Three data fusion strategies (low-llevel, mid-llevel, and high-llevel) combined with a multivariate classification algorithm (random forest, RF) were applied to authenticate the geographical origins of Panax notoginseng collected from five regions of Yunnan province in China. In low-level fusion, the original data from two spectra (Fourier transform mid-IR spectrum and near-IR spectrum) were directly concatenated into a new matrix, which then was applied for the classification. Mid-level fusion was the strategy that inputted variables extracted from the spectral data into an RF classification model. The extracted variables were processed by iterate variable selection of the RF model and principal component analysis. The use of high-level fusion combined the decision making of each spectroscopic technique and resulted in an ensemble decision. The results showed that the mid-level and high-level data fusion take advantage of the information synergy from two spectroscopic techniques and had better classification performance than that of independent decision making. High-level data fusion is the most effective strategy since the classification results are better than those of the other fusion strategies: accuracy rates ranged between 93% and 96% for the low-level data fusion, between 95% and 98% for the mid-level data fusion, and between 98% and 100% for the high-level data fusion. In conclusion, the high-level data fusion strategy for Fourier transform mid-IR and near-IR spectra can be used as a reliable tool for correct geographical identification of P. notoginseng. Graphical abstract The analytical steps of Fourier transform mid-IR and near-IR spectral data fusion for the geographical traceability of Panax notoginseng.

Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

2014-05-01

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

Transforaminal endoscopic treatment of lumbar radiculopathy after instrumented lumbar spine fusion.

PubMed

Telfeian, Albert E; Jasper, Gabriele P; Francisco, Gina M

2015-01-01

Transforaminal endoscopic discectomy and foraminotomy is a well-described minimally invasive technique for surgically treating lumbar radiculopathy caused by a herniated disc and foraminal narrowing. To describe the technique and feasibility of transforaminal foraminoplasty for the treatment of lumbar radiculopathy in patients who have already undergone instrumented spinal fusion. Retrospective study. Hospital and ambulatory surgery center After Institutional Review Board approval, charts from 18 consecutive patients with lumbar radiculopathy and instrumented spinal fusions who underwent endoscopic procedures between 2008 and 2013 were reviewed. The average pain relief one year postoperatively was reported to be 67.0%, good results as defined by MacNab. The average preoperative VAS score was 9.14, indicated in our questionnaire as severe and constant pain. The average one year postoperative VAS score was 3.00, indicated in our questionnaire as mild and intermittent pain. This is a retrospective study and only offers one year follow-up data for patients with instrumented fusions who have undergone endoscopic spine surgery. Transforaminal endoscopic discectomy and foraminotomy could be used as a safe, yet, minimally invasive and innovative technique for the treatment of lumbar radiculopathy in the setting of previous instrumented lumbar fusion. IRB approval: Meridian Health: IRB Study # 201206071J

Sensor data validation and reconstruction. Phase 1: System architecture study

NASA Technical Reports Server (NTRS)

1991-01-01

The sensor validation and data reconstruction task reviewed relevant literature and selected applicable validation and reconstruction techniques for further study; analyzed the selected techniques and emphasized those which could be used for both validation and reconstruction; analyzed Space Shuttle Main Engine (SSME) hot fire test data to determine statistical and physical relationships between various parameters; developed statistical and empirical correlations between parameters to perform validation and reconstruction tasks, using a computer aided engineering (CAE) package; and conceptually designed an expert system based knowledge fusion tool, which allows the user to relate diverse types of information when validating sensor data. The host hardware for the system is intended to be a Sun SPARCstation, but could be any RISC workstation with a UNIX operating system and a windowing/graphics system such as Motif or Dataviews. The information fusion tool is intended to be developed using the NEXPERT Object expert system shell, and the C programming language.

More nerve root injuries occur with minimally invasive lumbar surgery, especially extreme lateral interbody fusion: A review

PubMed Central

Epstein, Nancy E.

2016-01-01

Background: In the lumbar spine, do more nerve root injuries occur utilizing minimally invasive surgery (MIS) techniques versus open lumbar procedures? To answer this question, we compared the frequency of nerve root injuries for multiple open versus MIS operations including diskectomy, laminectomy with/without fusion addressing degenerative disc disease, stenosis, and/or degenerative spondylolisthesis. Methods: Several of Desai et al. large Spine Patient Outcomes Research Trial studies showed the frequency for nerve root injury following an open diskectomy ranged from 0.13% to 0.25%, for open laminectomy/stenosis with/without fusion it was 0%, and for open laminectomy/stenosis/degenerative spondylolisthesis with/without fusion it was 2%. Results: Alternatively, one study compared the incidence of root injuries utilizing MIS transforaminal lumbar interbody fusion (TLIF) versus posterior lumbar interbody fusion (PLIF) techniques; 7.8% of PLIF versus 2% of TLIF patients sustained root injuries. Furthermore, even higher frequencies of radiculitis and nerve root injuries occurred during anterior lumbar interbody fusions (ALIFs) versus extreme lateral interbody fusions (XLIFs). These high frequencies were far from acceptable; 15.8% following ALIF experienced postoperative radiculitis, while 23.8% undergoing XLIF sustained root/plexus deficits. Conclusions: This review indicates that MIS (TLIF/PLIF/ALIF/XLIF) lumbar surgery resulted in a higher incidence of root injuries, radiculitis, or plexopathy versus open lumbar surgical techniques. Furthermore, even a cursory look at the XLIF data demonstrated the greater danger posed to neural tissue by this newest addition to the MIS lumbar surgical armamentariu. The latter should prompt us as spine surgeons to question why the XLIF procedure is still being offered to our patients? PMID:26904372

Axial presacral lumbar interbody fusion and percutaneous posterior fixation for stabilization of lumbosacral isthmic spondylolisthesis.

PubMed

Gerszten, Peter C; Tobler, William; Raley, Thomas J; Miller, Larry E; Block, Jon E; Nasca, Richard J

2012-04-01

Case series. To describe a minimally invasive surgical technique for treatment of lumbosacral spondylolisthesis. Traditional surgical management of lumbosacral spondylolisthesis is technically challenging and associated with significant complications. Minimally invasive surgical techniques offer patients treatment alternatives with lower operative morbidity risk. The combination of percutaneous pedicle screw reduction and an axial presacral approach for lumbosacral discectomy and fusion is an option for the surgical management of low-grade lumbosacral spondylolisthesis. Twenty-six consecutive patients with symptomatic L5-S1 level isthmic spondylolisthesis (grade 1 or grade 2) underwent axial presacral lumbar interbody fusion and percutaneous posterior fixation. Study outcomes included visual analogue scale for axial pain severity, Odom criteria, and radiographic fusion. The procedure was successfully completed in all patients with no intraoperative complications reported. Intraoperative blood loss was minimal (range, 20-150 mL). Median hospital stay was 1 day (range, <1-2 d). Spondylolisthesis grade was improved after axial lumbar interbody fusion (P<0.001) with 50% (13 of 26) of patients showing a reduction of at least 1 grade. Axial pain severity improved from 8.1±1.4 at baseline to 2.8±2.3 after axial lumbar interbody fusion, representing a 66% reduction from baseline (95% confidence interval, 54.3%-77.9%). At 2-year posttreatment, all patients showed solid fusion. Using Odom criteria, 81% of patients were judged as excellent or good (16 excellent, 5 good, 3 fair, and 2 poor). There were no perioperative procedure-related complications including infection or bowel perforation. During postoperative follow-up, 4 patients required reintervention due to recurrent radicular (n=2) or screw-related (n=2) pain. The minimally invasive presacral axial interbody fusion and posterior instrumentation technique is a safe and effective treatment for low-grade isthmic spondylolisthesis.

[Contrast-enhanced ultrasound (CEUS) and image fusion for procedures of liver interventions].

PubMed

Jung, E M; Clevert, D A

2018-06-01

Contrast-enhanced ultrasound (CEUS) is becoming increasingly important for the detection and characterization of malignant liver lesions and allows percutaneous treatment when surgery is not possible. Contrast-enhanced ultrasound image fusion with computed tomography (CT) and magnetic resonance imaging (MRI) opens up further options for the targeted investigation of a modified tumor treatment. Ultrasound image fusion offers the potential for real-time imaging and can be combined with other cross-sectional imaging techniques as well as CEUS. With the implementation of ultrasound contrast agents and image fusion, ultrasound has been improved in the detection and characterization of liver lesions in comparison to other cross-sectional imaging techniques. In addition, this method can also be used for intervention procedures. The success rate of fusion-guided biopsies or CEUS-guided tumor ablation lies between 80 and 100% in the literature. Ultrasound-guided image fusion using CT or MRI data, in combination with CEUS, can facilitate diagnosis and therapy follow-up after liver interventions. In addition to the primary applications of image fusion in the diagnosis and treatment of liver lesions, further useful indications can be integrated into daily work. These include, for example, intraoperative and vascular applications as well applications in other organ systems.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

A novel method to recover DD fusion proton CR-39 data corrupted by fast ablator ions at OMEGA and the National Ignition Facility

NASA Astrophysics Data System (ADS)

Sutcliffe, G. D.; Milanese, L. M.; Orozco, D.; Lahmann, B.; Gatu Johnson, M.; Séguin, F. H.; Sio, H.; Frenje, J. A.; Li, C. K.; Petrasso, R. D.; Park, H.-S.; Rygg, J. R.; Casey, D. T.; Bionta, R.; Turnbull, D. P.; Huntington, C. M.; Ross, J. S.; Zylstra, A. B.; Rosenberg, M. J.; Glebov, V. Yu.

2016-11-01

CR-39 detectors are used routinely in inertial confinement fusion (ICF) experiments as a part of nuclear diagnostics. CR-39 is filtered to stop fast ablator ions which have been accelerated from an ICF implosion due to electric fields caused by laser-plasma interactions. In some experiments, the filtering is insufficient to block these ions and the fusion-product signal tracks are lost in the large background of accelerated ion tracks. A technique for recovering signal in these scenarios has been developed, tested, and implemented successfully. The technique involves removing material from the surface of the CR-39 to a depth beyond the endpoint of the ablator ion tracks. The technique preserves signal magnitude (yield) as well as structure in radiograph images. The technique is effective when signal particle range is at least 10 μm deeper than the necessary bulk material removal.

A novel method to recover DD fusion proton CR-39 data corrupted by fast ablator ions at OMEGA and the National Ignition Facility.

PubMed

Sutcliffe, G D; Milanese, L M; Orozco, D; Lahmann, B; Gatu Johnson, M; Séguin, F H; Sio, H; Frenje, J A; Li, C K; Petrasso, R D; Park, H-S; Rygg, J R; Casey, D T; Bionta, R; Turnbull, D P; Huntington, C M; Ross, J S; Zylstra, A B; Rosenberg, M J; Glebov, V Yu

2016-11-01

CR-39 detectors are used routinely in inertial confinement fusion (ICF) experiments as a part of nuclear diagnostics. CR-39 is filtered to stop fast ablator ions which have been accelerated from an ICF implosion due to electric fields caused by laser-plasma interactions. In some experiments, the filtering is insufficient to block these ions and the fusion-product signal tracks are lost in the large background of accelerated ion tracks. A technique for recovering signal in these scenarios has been developed, tested, and implemented successfully. The technique involves removing material from the surface of the CR-39 to a depth beyond the endpoint of the ablator ion tracks. The technique preserves signal magnitude (yield) as well as structure in radiograph images. The technique is effective when signal particle range is at least 10 μm deeper than the necessary bulk material removal.

Nonperturbative measurement of the local magnetic field using pulsed polarimetry for fusion reactor conditions (invited).

PubMed

Smith, Roger J

2008-10-01

A novel diagnostic technique for the remote and nonperturbative sensing of the local magnetic field in reactor relevant plasmas is presented. Pulsed polarimetry [Patent No. 12/150,169 (pending)] combines optical scattering with the Faraday effect. The polarimetric light detection and ranging (LIDAR)-like diagnostic has the potential to be a local B(pol) diagnostic on ITER and can achieve spatial resolutions of millimeters on high energy density (HED) plasmas using existing lasers. The pulsed polarimetry method is based on nonlocal measurements and subtle effects are introduced that are not present in either cw polarimetry or Thomson scattering LIDAR. Important features include the capability of simultaneously measuring local T(e), n(e), and B(parallel) along the line of sight, a resiliency to refractive effects, a short measurement duration providing near instantaneous data in time, and location for real-time feedback and control of magnetohydrodynamic (MHD) instabilities and the realization of a widely applicable internal magnetic field diagnostic for the magnetic fusion energy program. The technique improves for higher n(e)B(parallel) product and higher n(e) and is well suited for diagnosing the transient plasmas in the HED program. Larger devices such as ITER and DEMO are also better suited to the technique, allowing longer pulse lengths and thereby relaxing key technology constraints making pulsed polarimetry a valuable asset for next step devices. The pulsed polarimetry technique is clarified by way of illustration on the ITER tokamak and plasmas within the magnetized target fusion program within present technological means.

Model-Based Control using Model and Mechanization Fusion Techniques for Image-Aided Navigation

DTIC Science & Technology

2009-03-01

Magnet Motors . Magna Physics Publishing, Hillsboro, OH, 1994. 7. Houwu Bai, Xubo Song, Eric Wan and Andriy Myronenko. “Vision-only Navi- gation and...filter”. Proceedings of the Recent Advances in Space Technologies (RAST). Nov 2003. 6. Hendershot, J.R. and Tje Miller. Design of Brushless Permanent

Examining the efficiency of muffle furnance-induced alkaline hydrolysis in determining the titanium content of environmental samples containing engineered titanium dioxide particles

EPA Science Inventory

A novel muffle furnace (MF)-based potassium hydroxide (KOH) fusion digestion technique was developed and its comparative digestion and dissolution efficacy for different titanium dioxide nanoparticles (TiO2-NPs)/environmental matrices was evaluated. Digestion of different enviro...

Robust model-based 3d/3D fusion using sparse matching for minimally invasive surgery.

PubMed

Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan

2013-01-01

Classical surgery is being disrupted by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm CT and C-arm fluoroscopy are routinely used for intra-operative guidance. However, intra-operative modalities have limited image quality of the soft tissue and a reliable assessment of the cardiac anatomy can only be made by injecting contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a novel sparse matching approach for fusing high quality pre-operative CT and non-contrasted, non-gated intra-operative C-arm CT by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the pre-operative CT and mapped to the intra-operative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments demonstrate that our model-based fusion approach has an average execution time of 2.9 s, while the accuracy lies within expert user confidence intervals.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

[Clinical utility of real-time fluorescent PCR for combined detection of anaplastic lymphoma kinase and c-ros oncogene 1 receptor tyrosine kinase in non-small cell lung cancer].

PubMed

Bai, D Y; Zhang, H P; Zhong, S; Suo, W H; Gao, D H; Ding, Y; Tu, J H

2016-12-23

Objective: To investigate the clinical application value of combined detection of ALK fusion gene and c-ros oncogene 1 receptor tyrosine kinase (ROS1) fusion gene in non-small cell lung cancer (NSCLC) using real-time fluorescent PCR. Methods: A kit for combined detection of ALK fusion gene and ROS1 fusion gene based on fluorescent PCR was used to simultaneously detect the two fusion genes in 302 cases of NSCLC specimens. The results were validated through Sanger sequencing. The consistency of the two detection methods was analyzed. Results: All 302 cases of NSCLC specimens were successfully analyzed through fluorescent PCR (302/302). 12 cases (4.0%) were found to contain ALK fusion gene, including 3 cases with ALK-M1, 3 with ALK-M2, 3 with ALK-M3, 1 with ALK-M4, and 2 with ALK-M6 fusion gene.12 cases (4.0%) were found to contain ROS1 fusion gene, including 1 case with ROS1-M7, 8 cases with ROS1-M8, 1 case with ROS1-M12, 1 case with ROS1-M14, and 1 case with double-positive ROS1-M3 and ROS1-M8 fusion genes. The total detection rate of ALK fusion gene and ROS1 fusion gene was 7.9% (24/302) and 278 cases showed to be negative for ALK fusion gene and ROS1 fusion gene. The successful detection rates for Sanger DNA sequencing were also 100%. The positive, negative and total coincidence rates obtained by real-time fluorescent PCR and by Sanger DNA sequencing were all 100%. Conclusions: The results of Sanger DNA sequencing demonstrate that the real-time fluorescent PCR assay is equally effective in detecting ALK and ROS1 fusion genes in NSCLC tissues. Furthermore, real-time fluorescent PCR assay can be used to detect trace ALK and ROS1 fusion gene simultaneously in tiny samples, and can save time and avoid repeated sampling. It is worthy of recommendation as a rapid and reliable detection technique.

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

Henderson, Ian M.; Collins, Aaron M.; Quintana, Hope A.

In this study, we develop a quantitative dye dequenching technique for the measurement of polymersome fusion, using it to characterize the salt mediated, mechanically-induced fusion of polymersomes with polymer, lipid, and so-called stealth lipid vesicles. While dye dequenching has been used to quantitatively explore liposome fusion in the past, this is the first use of dye dequenching to measure polymersome fusion of which we are aware. In addition to providing quantitative results, dye dequenching is ideal for detecting fusion in instances where DLS results would be ambiguous, such as low yield levels and size ranges outside the capabilities of DLS.more » The dye chosen for this study was a cyanine derivative, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR), which proved to provide excellent data on the extent of polymersome fusion. Using this technique, we have shown the limited fusion capabilities of polymersome/liposome heterofusion, notably DOPC vesicles fusing with polymersomes at half the efficiency of polymersome homofusion and DPPC vesicles showing virtually no fusion. In addition to these key heterofusion experiments, we determined the broad applicability of dye dequenching in measuring kinetic rates of polymersome fusion; and showed that even at elevated temperatures or over multiple weeks' time, no polymersome fusion occurred without agitation. Stealth liposomes formed from DPPC and PEO-functionalized lipid, however, fused with polymersomes and stealth liposomes with relatively high efficiency, lending support to our hypothesis that the response of the PEO corona to salt is a key factor in the fusion process. This last finding suggests that although the conjugation of PEO to lipids increases vesicle biocompatibility and enables their longer circulation times, it also renders the vesicles subject to destabilization under high salt and shear (e.g. in the circulatory system) that may lead to, in this case, fusion.« less

Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver.

PubMed

Lee, Chan-Gun; Dao, Nhu-Ngoc; Jang, Seonmin; Kim, Deokhwan; Kim, Yonghun; Cho, Sungrae

2016-06-11

Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3 × 10(-1) to 5.3 × 10(-7), respectively.

Ghost detection and removal based on super-pixel grouping in exposure fusion

NASA Astrophysics Data System (ADS)

Jiang, Shenyu; Xu, Zhihai; Li, Qi; Chen, Yueting; Feng, Huajun

2014-09-01

A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.

Creep behavior and in-depth microstructural characterization of dissimilar joints

PubMed Central

Kauffmann, F; Klein, T; Klenk, A; Maile, K

2013-01-01

The 700 °C power plants currently under development will utilize Ni-base alloys such as alloy 617 for components to be operated at temperatures >650 °C. Due to economic reasons for components or parts of components which are subjected to temperatures <650 °C, 2% Cr or 9–12% Cr steels is used, depending on the required mechanical properties. This makes the dissimilar joining of Ni-base alloys and Cr steels a necessity in these plants. Experimental investigations show that these joints have to be identified as weak points with regard to damage development under creep and creep-fatigue loading. The present investigation focuses on welds between the alloy 617 and 2% Cr steel. Under creep load the fracture occurs near the fusion line between the 2% Cr steel base metal and alloy 617 weld metal. To explain the reasons for this fracture location, the microstructure of this fusion line was investigated using TEM and FIB techniques after welding and after creep loading. The TEM investigations have shown a small zone in the weld metal near the fusion line exhibiting chromium depletion and clearly reduced amounts of chromium carbides, leading to a weakening of this zone. PMID:27877551

Evaluation of taste solutions by sensor fusion

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

Kojima, Yohichiro; Sato, Eriko; Atobe, Masahiko

In our previous studies, properties of taste solutions were discriminated based on sound velocity and amplitude of ultrasonic waves propagating through the solutions. However, to make this method applicable to beverages which contain many taste substances, further studies are required. In this study, the waveform of an ultrasonic wave with frequency of approximately 5 MHz propagating through a solution was measured and subjected to frequency analysis. Further, taste sensors require various techniques of sensor fusion to effectively obtain chemical and physical parameter of taste solutions. A sensor fusion method of ultrasonic wave sensor and various sensors, such as the surfacemore » plasmon resonance (SPR) sensor, to estimate tastes were proposed and examined in this report. As a result, differences among pure water and two basic taste solutions were clearly observed as differences in their properties. Furthermore, a self-organizing neural network was applied to obtained data which were used to clarify the differences among solutions.« less

Left Ventricular Endocardium Tracking by Fusion of Biomechanical and Deformable Models

PubMed Central

Gu, Jason

2014-01-01

This paper presents a framework for tracking left ventricular (LV) endocardium through 2D echocardiography image sequence. The framework is based on fusion of biomechanical (BM) model of the heart with the parametric deformable model. The BM model constitutive equation consists of passive and active strain energy functions. The deformations of the LV are obtained by solving the constitutive equations using ABAQUS FEM in each frame in the cardiac cycle. The strain energy functions are defined in two user subroutines for active and passive phases. Average fusion technique is used to fuse the BM and deformable model contours. Experimental results are conducted to verify the detected contours and the results are evaluated by comparing themto a created gold standard. The results and the evaluation proved that the framework has the tremendous potential to track and segment the LV through the whole cardiac cycle. PMID:24587814

Preventing Proximal Adjacent Level Kyphosis With Strap Stabilization.

PubMed

Zaghloul, Khaled M; Matoian, Brett J; Denardin, Nicholas B; Patel, Vikas V

2016-07-01

A substantial proportion of patients develop proximal junctional kyphosis following spinal surgery. To combat this postoperative change, several techniques have focused on maintaining the structural integrity of adjacent spinal levels and adapting the proximal end of the fusion construct to accommodate the increased mechanical stressors produced by long spinal fusion. The use of Mersilene tape (Ethicon, Somerville, New Jersey) for spine and orthopedic surgery is well documented, although considerably less is known about its use for preventing proximal junctional kyphosis. This article describes a proposed technique using Mersilene tape to provide a check-rein strap stabilization at the proximal end of fusion constructs. Initial data suggest that use of this technique may prevent formation of proximal junctional kyphosis. [Orthopedics. 2016; 39(4):e794-e799.]. Copyright 2016, SLACK Incorporated.

A synthetic dataset for evaluating soft and hard fusion algorithms

NASA Astrophysics Data System (ADS)

Graham, Jacob L.; Hall, David L.; Rimland, Jeffrey

2011-06-01

There is an emerging demand for the development of data fusion techniques and algorithms that are capable of combining conventional "hard" sensor inputs such as video, radar, and multispectral sensor data with "soft" data including textual situation reports, open-source web information, and "hard/soft" data such as image or video data that includes human-generated annotations. New techniques that assist in sense-making over a wide range of vastly heterogeneous sources are critical to improving tactical situational awareness in counterinsurgency (COIN) and other asymmetric warfare situations. A major challenge in this area is the lack of realistic datasets available for test and evaluation of such algorithms. While "soft" message sets exist, they tend to be of limited use for data fusion applications due to the lack of critical message pedigree and other metadata. They also lack corresponding hard sensor data that presents reasonable "fusion opportunities" to evaluate the ability to make connections and inferences that span the soft and hard data sets. This paper outlines the design methodologies, content, and some potential use cases of a COIN-based synthetic soft and hard dataset created under a United States Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office (ARO). The dataset includes realistic synthetic reports from a variety of sources, corresponding synthetic hard data, and an extensive supporting database that maintains "ground truth" through logical grouping of related data into "vignettes." The supporting database also maintains the pedigree of messages and other critical metadata.

REMOTE LAND MINE(FIELD) DETECTION. An Overview of Techniques (DETECTIE VAN LANDMIJNEN EN MIJNENVELDEN OP AFSTAND. Een Overzicht van de technieken),

DTIC Science & Technology

1994-09-01

titel DETECTIE VAN LANDMIJNEN EN MIJNENVELDEN OP AFSTAND, een overzicht van de technieken auteur (s) Drs. J.S. Groot, Ir. Y.H.L. Janssen datum september...functions based on set theory . The fundamental theory is developed in the sixties. This theory was applicable to binary images (black-and-white images...held at TNO-FEL. Various subjects related to fusion techniques: Dempster Shafer theory , Bayesian inference, Kalman filtering, fuzzy logic. [A15], [B4

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Additive Manufacturing of Single-Crystal Superalloy CMSX-4 Through Scanning Laser Epitaxy: Computational Modeling, Experimental Process Development, and Process Parameter Optimization

NASA Astrophysics Data System (ADS)

Basak, Amrita; Acharya, Ranadip; Das, Suman

2016-08-01

This paper focuses on additive manufacturing (AM) of single-crystal (SX) nickel-based superalloy CMSX-4 through scanning laser epitaxy (SLE). SLE, a powder bed fusion-based AM process was explored for the purpose of producing crack-free, dense deposits of CMSX-4 on top of similar chemistry investment-cast substrates. Optical microscopy and scanning electron microscopy (SEM) investigations revealed the presence of dendritic microstructures that consisted of fine γ' precipitates within the γ matrix in the deposit region. Computational fluid dynamics (CFD)-based process modeling, statistical design of experiments (DoE), and microstructural characterization techniques were combined to produce metallurgically bonded single-crystal deposits of more than 500 μm height in a single pass along the entire length of the substrate. A customized quantitative metallography based image analysis technique was employed for automatic extraction of various deposit quality metrics from the digital cross-sectional micrographs. The processing parameters were varied, and optimal processing windows were identified to obtain good quality deposits. The results reported here represent one of the few successes obtained in producing single-crystal epitaxial deposits through a powder bed fusion-based metal AM process and thus demonstrate the potential of SLE to repair and manufacture single-crystal hot section components of gas turbine systems from nickel-based superalloy powders.

Intensity-hue-saturation-based image fusion using iterative linear regression

NASA Astrophysics Data System (ADS)

Cetin, Mufit; Tepecik, Abdulkadir

2016-10-01

The image fusion process basically produces a high-resolution image by combining the superior features of a low-resolution spatial image and a high-resolution panchromatic image. Despite its common usage due to its fast computing capability and high sharpening ability, the intensity-hue-saturation (IHS) fusion method may cause some color distortions, especially when a large number of gray value differences exist among the images to be combined. This paper proposes a spatially adaptive IHS (SA-IHS) technique to avoid these distortions by automatically adjusting the exact spatial information to be injected into the multispectral image during the fusion process. The SA-IHS method essentially suppresses the effects of those pixels that cause the spectral distortions by assigning weaker weights to them and avoiding a large number of redundancies on the fused image. The experimental database consists of IKONOS images, and the experimental results both visually and statistically prove the enhancement of the proposed algorithm when compared with the several other IHS-like methods such as IHS, generalized IHS, fast IHS, and generalized adaptive IHS.

Membrane fusion-competent virus-like proteoliposomes and proteinaceous supported bilayers made directly from cell plasma membranes.

PubMed

Costello, Deirdre A; Hsia, Chih-Yun; Millet, Jean K; Porri, Teresa; Daniel, Susan

2013-05-28

Virus-like particles are useful materials for studying virus-host interactions in a safe manner. However, the standard production of pseudovirus based on the vesicular stomatitis virus (VSV) backbone is an intricate procedure that requires trained laboratory personnel. In this work, a new strategy for creating virus-like proteoliposomes (VLPLs) and virus-like supported bilayers (VLSBs) is presented. This strategy uses a cell blebbing technique to induce the formation of nanoscale vesicles from the plasma membrane of BHK cells expressing the hemagglutinin (HA) fusion protein of influenza X-31. These vesicles and supported bilayers contain HA and are used to carry out single particle membrane fusion events, monitored using total internal reflection fluorescence microscopy. The results of these studies show that the VLPLs and VLSBs contain HA proteins that are fully competent to carry out membrane fusion, including the formation of a fusion pore and the release of fluorophores loaded into vesicles. This new strategy for creating spherical and planar geometry virus-like membranes has many potential applications. VLPLs could be used to study fusion proteins of virulent viruses in a safe manner, or they could be used as therapeutic delivery particles to transport beneficial proteins coexpressed in the cells to a target cell. VLSBs could facilitate high throughput screening of antiviral drugs or pathogen-host cell interactions.

Facility Monitoring: A Qualitative Theory for Sensor Fusion

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2001-01-01

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

Integration of language and sensor information

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Weijers, Bertus

2003-04-01

The talk describes the development of basic technologies of intelligent systems fusing data from multiple domains and leading to automated computational techniques for understanding data contents. Understanding involves inferring appropriate decisions and recommending proper actions, which in turn requires fusion of data and knowledge about objects, situations, and actions. Data might include sensory data, verbal reports, intelligence intercepts, or public records, whereas knowledge ought to encompass the whole range of objects, situations, people and their behavior, and knowledge of languages. In the past, a fundamental difficulty in combining knowledge with data was the combinatorial complexity of computations, too many combinations of data and knowledge pieces had to be evaluated. Recent progress in understanding of natural intelligent systems, including the human mind, leads to the development of neurophysiologically motivated architectures for solving these challenging problems, in particular the role of emotional neural signals in overcoming combinatorial complexity of old logic-based approaches. Whereas past approaches based on logic tended to identify logic with language and thinking, recent studies in cognitive linguistics have led to appreciation of more complicated nature of linguistic models. Little is known about the details of the brain mechanisms integrating language and thinking. Understanding and fusion of linguistic information with sensory data represent a novel challenging aspect of the development of integrated fusion systems. The presentation will describe a non-combinatorial approach to this problem and outline techniques that can be used for fusing diverse and uncertain knowledge with sensory and linguistic data.

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT

PubMed Central

Sulaiman, Puteri Suhaiza; Wirza, Rahmita; Dimon, Mohd Zamrin; Khalid, Fatimah; Moosavi Tayebi, Rohollah

2015-01-01

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics. PMID:26089965

Cellulose binding domain fusion proteins

DOEpatents

Shoseyov, Oded; Shpiegl, Itai; Goldstein, Marc A.; Doi, Roy H.

1998-01-01

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production thereof. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques.

Preparation of calibration materials for microanalysis of Ti minerals by direct fusion of synthetic and natural materials: experience with LA-ICP-MS analysis of some important minor and trace elements in ilmenite and rutile.

PubMed

Odegård, M; Mansfeld, J; Dundas, S H

2001-08-01

Calibration materials for microanalysis of Ti minerals have been prepared by direct fusion of synthetic and natural materials by resistance heating in high-purity graphite electrodes. Synthetic materials were FeTiO3 and TiO2 reagents doped with minor and trace elements; CRMs for ilmenite, rutile, and a Ti-rich magnetite were used as natural materials. Problems occurred during fusion of Fe2O3-rich materials, because at atmospheric pressure Fe2O3 decomposes into Fe3O4 and O2 at 1462 degrees C. An alternative fusion technique under pressure was tested, but the resulting materials were characterized by extensive segregation and development of separate phases. Fe2O3-rich materials were therefore fused below this temperature, resulting in a form of sintering, without conversion of the materials into amorphous glasses. The fused materials were studied by optical microscopy and EPMA, and tested as calibration materials by inductively coupled plasma mass spectrometry, equipped with laser ablation for sample introduction (LA-ICP-MS). It was demonstrated that calibration curves based on materials of rutile composition, within normal analytical uncertainty, generally coincide with calibration curves based on materials of ilmenite composition. It is, therefore, concluded that LA-ICP-MS analysis of Ti minerals can with advantage be based exclusively on calibration materials prepared for rutile, thereby avoiding the special fusion problems related to oxide mixtures of ilmenite composition. It is documented that sintered materials were in good overall agreement with homogeneous glass materials, an observation that indicates that in other situations also sintered mineral concentrates might be a useful alternative for instrument calibration, e.g. as alternative to pressed powders.

Millimeter-wave imaging of magnetic fusion plasmas: technology innovations advancing physics understanding

NASA Astrophysics Data System (ADS)

Wang, Y.; Tobias, B.; Chang, Y.-T.; Yu, J.-H.; Li, M.; Hu, F.; Chen, M.; Mamidanna, M.; Phan, T.; Pham, A.-V.; Gu, J.; Liu, X.; Zhu, Y.; Domier, C. W.; Shi, L.; Valeo, E.; Kramer, G. J.; Kuwahara, D.; Nagayama, Y.; Mase, A.; Luhmann, N. C., Jr.

2017-07-01

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. Microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These have the potential to greatly advance microwave fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfvén eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today’s most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.

Millimeter-wave imaging of magnetic fusion plasmas: technology innovations advancing physics understanding

DOE PAGES

Wang, Y.; Tobias, B.; Chang, Y. -T.; ...

2017-03-14

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. The microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These also have the potential to greatly advance microwavemore » fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfven eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today's most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.« less

Seismic data fusion anomaly detection

NASA Astrophysics Data System (ADS)

Harrity, Kyle; Blasch, Erik; Alford, Mark; Ezekiel, Soundararajan; Ferris, David

2014-06-01

Detecting anomalies in non-stationary signals has valuable applications in many fields including medicine and meteorology. These include uses such as identifying possible heart conditions from an Electrocardiography (ECG) signals or predicting earthquakes via seismographic data. Over the many choices of anomaly detection algorithms, it is important to compare possible methods. In this paper, we examine and compare two approaches to anomaly detection and see how data fusion methods may improve performance. The first approach involves using an artificial neural network (ANN) to detect anomalies in a wavelet de-noised signal. The other method uses a perspective neural network (PNN) to analyze an arbitrary number of "perspectives" or transformations of the observed signal for anomalies. Possible perspectives may include wavelet de-noising, Fourier transform, peak-filtering, etc.. In order to evaluate these techniques via signal fusion metrics, we must apply signal preprocessing techniques such as de-noising methods to the original signal and then use a neural network to find anomalies in the generated signal. From this secondary result it is possible to use data fusion techniques that can be evaluated via existing data fusion metrics for single and multiple perspectives. The result will show which anomaly detection method, according to the metrics, is better suited overall for anomaly detection applications. The method used in this study could be applied to compare other signal processing algorithms.

Toughness characterization by small specimen test technique for HIPed joints of F82H steel aiming at first wall fabrication in fusion

NASA Astrophysics Data System (ADS)

Kishimoto, H.; Ono, T.; Sakasegawa, H.; Tanigawa, H.; Kohno, Y.; Kohyama, A.

2013-09-01

Reduced activation ferritic/martensitic steels (RAFMs), such as F82H steels, have been developed as candidates of structural materials for fusion. In the design of a fusion reactor, cooling channels are built in the first wall of the blanket. One large issue is to determine how to join rectangular tubes to thin panels to fabricate the first wall. Hot Isostatic Pressing (HIPing) is a solution to solve the issue. Because of the thin HIPed walls of the channels, the specimen size for inspection of HIPed interface is limited. In the present research, Small Specimen Test Techniques (SSTT) are screened for the destructive toughness investigation technique of HIPed F82H joints. 1/3 size Charpy V-notch impact (1/3 CVN) and small punch (SP) tests are employed for the present research. The toughness of the HIPed joints is strongly affected by various surface finishing of specimens treated previous to the HIPing. In the present research, several kinds of HIPed joints were surface finished by different methods and investigated by 1/3 CVN impact test. The HIPed F82H joints had different toughness ranging from 20% to 70% of the toughness of the F82H base metal. The SP test is also available for the investigation of toughness change by the HIPing. The sensitivity of 1/3 CVN impact test against toughness change was better than the SP test, it revealed that the SP test has some limitations.

Lights on: Dye dequenching reveals polymersome fusion with polymer, lipid and stealth lipid vesicles

DOE PAGES

Henderson, Ian M.; Collins, Aaron M.; Quintana, Hope A.; ...

2015-12-13

In this study, we develop a quantitative dye dequenching technique for the measurement of polymersome fusion, using it to characterize the salt mediated, mechanically-induced fusion of polymersomes with polymer, lipid, and so-called stealth lipid vesicles. While dye dequenching has been used to quantitatively explore liposome fusion in the past, this is the first use of dye dequenching to measure polymersome fusion of which we are aware. In addition to providing quantitative results, dye dequenching is ideal for detecting fusion in instances where DLS results would be ambiguous, such as low yield levels and size ranges outside the capabilities of DLS.more » The dye chosen for this study was a cyanine derivative, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR), which proved to provide excellent data on the extent of polymersome fusion. Using this technique, we have shown the limited fusion capabilities of polymersome/liposome heterofusion, notably DOPC vesicles fusing with polymersomes at half the efficiency of polymersome homofusion and DPPC vesicles showing virtually no fusion. In addition to these key heterofusion experiments, we determined the broad applicability of dye dequenching in measuring kinetic rates of polymersome fusion; and showed that even at elevated temperatures or over multiple weeks' time, no polymersome fusion occurred without agitation. Stealth liposomes formed from DPPC and PEO-functionalized lipid, however, fused with polymersomes and stealth liposomes with relatively high efficiency, lending support to our hypothesis that the response of the PEO corona to salt is a key factor in the fusion process. This last finding suggests that although the conjugation of PEO to lipids increases vesicle biocompatibility and enables their longer circulation times, it also renders the vesicles subject to destabilization under high salt and shear (e.g. in the circulatory system) that may lead to, in this case, fusion.« less

Production Of Human Antibodies

NASA Technical Reports Server (NTRS)

Sammons, David W.; Neil, Garry A.

1993-01-01

Process for making human monoclonal antibodies based on combination of techniques. Antibodies made active against specific antigen. Process involves in vivo immunization of human B lymphocyte cells in mice. B cells of interest enriched in vitro before fusion. Method potentially applicable to any antigen. Does not rely on use of Epstein-Barr virus at any step. Human lymphocytes taken from any source.

Posterior spinal osteosynthesis for cervical fracture/dislocation using a flexible multistrand cable system: technical note.

PubMed

Huhn, S L; Wolf, A L; Ecklund, J

1991-12-01

Cervical instability secondary to fracture/dislocation or traumatic subluxation involving the posterior elements may be treated by a variety of fusion techniques. The rigidity of the stainless steel wires used in posterior cervical fusions often leads to difficulty with insertion, adequate tension, and conformation of the graft construct. This report describes a technique of posterior cervical fusion employing a wire system using flexible stainless steel cables. The wire consists of a flexible, 49-strand, stainless steel cable connected on one end to a short, malleable, blunt leader with the opposite end connected to a small islet. The cable may be used in occipitocervical, atlantoaxial, facet-to-spinous process, and interspinous fusion techniques. The cable loop is secured by using a tension/crimper device that sets the desired tension in the cable. In addition to superior biomechanical strength, the flexibility of the cable allows greater ease of insertion and tension adjustment. In terms of direct operative instrumentation in posterior cervical arthrodesis, involving both the upper and lower cervical spine, the cable system appears to be a safe and efficient alternative to monofilament wires.

Dual wavelength imaging allows analysis of membrane fusion of influenza virus inside cells.

PubMed

Sakai, Tatsuya; Ohuchi, Masanobu; Imai, Masaki; Mizuno, Takafumi; Kawasaki, Kazunori; Kuroda, Kazumichi; Yamashina, Shohei

2006-02-01

Influenza virus hemagglutinin (HA) is a determinant of virus infectivity. Therefore, it is important to determine whether HA of a new influenza virus, which can potentially cause pandemics, is functional against human cells. The novel imaging technique reported here allows rapid analysis of HA function by visualizing viral fusion inside cells. This imaging was designed to detect fusion changing the spectrum of the fluorescence-labeled virus. Using this imaging, we detected the fusion between a virus and a very small endosome that could not be detected previously, indicating that the imaging allows highly sensitive detection of viral fusion.

Extension of an iterative closest point algorithm for simultaneous localization and mapping in corridor environments

NASA Astrophysics Data System (ADS)

Yue, Haosong; Chen, Weihai; Wu, Xingming; Wang, Jianhua

2016-03-01

Three-dimensional (3-D) simultaneous localization and mapping (SLAM) is a crucial technique for intelligent robots to navigate autonomously and execute complex tasks. It can also be applied to shape measurement, reverse engineering, and many other scientific or engineering fields. A widespread SLAM algorithm, named KinectFusion, performs well in environments with complex shapes. However, it cannot handle translation uncertainties well in highly structured scenes. This paper improves the KinectFusion algorithm and makes it competent in both structured and unstructured environments. 3-D line features are first extracted according to both color and depth data captured by Kinect sensor. Then the lines in the current data frame are matched with the lines extracted from the entire constructed world model. Finally, we fuse the distance errors of these line-pairs into the standard KinectFusion framework and estimate sensor poses using an iterative closest point-based algorithm. Comparative experiments with the KinectFusion algorithm and one state-of-the-art method in a corridor scene have been done. The experimental results demonstrate that after our improvement, the KinectFusion algorithm can also be applied to structured environments and has higher accuracy. Experiments on two open access datasets further validated our improvements.

Traceability of Boletaceae mushrooms using data fusion of UV-visible and FTIR combined with chemometrics methods.

PubMed

Yao, Sen; Li, Tao; Liu, HongGao; Li, JieQing; Wang, YuanZhong

2018-04-01

Boletaceae mushrooms are wild-grown edible mushrooms that have high nutrition, delicious flavor and large economic value distributing in Yunnan Province, China. Traceability is important for the authentication and quality assessment of Boletaceae mushrooms. In this study, UV-visible and Fourier transform infrared (FTIR) spectroscopies were applied for traceability of 247 Boletaceae mushroom samples in combination with chemometrics. Compared with a single spectroscopy technique, data fusion strategy can obviously improve the classification performance in partial least square discriminant analysis (PLS-DA) and grid-search support vector machine (GS-SVM) models, for both species and geographical origin traceability. In addition, PLS-DA and GS-SVM models can provide 100.00% accuracy for species traceability and have reliable evaluation parameters. For geographical origin traceability, the accuracy of prediction in the PLS-DA model by data fusion was just 64.63%, but the GS-SVM model based on data fusion was 100.00%. The results demonstrated that the data fusion strategy of UV-visible and FTIR combined with GS-SVM could provide a higher synergic effect for traceability of Boletaceae mushrooms and have a good generalization ability for the comprehensive quality control and evaluation of similar foods. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Effect of retransmission and retrodiction on estimation and fusion in long-haul sensor networks

DOE PAGES

Liu, Qiang; Wang, Xin; Rao, Nageswara S. V.; ...

2016-01-01

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as target tracking. In this work, we study the scenario where sensors take measurements of one or more dynamic targets and send state estimates of the targets to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels reduce the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. In addition, the errors in target-sensor data association can alsomore » degrade the estimation performance. To mitigate the effect of imperfect communications on state estimation and fusion, we consider retransmission and retrodiction. The system adopts certain retransmission-based transport protocols so that lost messages can be recovered over time. Besides, retrodiction/smoothing techniques are applied so that the chances of incurring excess delay due to retransmission are greatly reduced. We analyze the extent to which retransmission and retrodiction can improve the performance of delay-sensitive target tracking tasks under variable communication loss and delay conditions. Lastly, simulation results of a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.« less

Cellulose binding domain fusion proteins

DOEpatents

Shoseyov, O.; Yosef, K.; Shpiegl, I.; Goldstein, M.A.; Doi, R.H.

1998-02-17

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques. 16 figs.

Data fusion for delivering advanced traveler information services

DOT National Transportation Integrated Search

2003-05-01

Many transportation professionals have suggested that improved ATIS data fusion techniques and processing will improve the overall quality, timeliness, and usefulness of traveler information. The purpose of this study was four fold. First, conduct a ...

Failure of technetium bone scanning to detect pseudarthroses in spinal fusion for scoliosis

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

Hannon, K.M.; Wetta, W.J.

1977-01-01

A prospective study of 11 patients suggests that present techniques of technetium bone scanning do not assist in recognizing the presence of well-established pseudarthrosis in spinal fusions for scoliosis.

Invited Article: A novel calibration method for the JET real-time far infrared polarimeter and integration of polarimetry-based line-integrated density measurements for machine protection of a fusion plant.

PubMed

Boboc, A; Bieg, B; Felton, R; Dalley, S; Kravtsov, Yu

2015-09-01

In this paper, we present the work in the implementation of a new calibration for the JET real-time polarimeter based on the complex amplitude ratio technique and a new self-validation mechanism of data. This allowed easy integration of the polarimetry measurements into the JET plasma density control (gas feedback control) and as well as machine protection systems (neutral beam injection heating safety interlocks). The new addition was used successfully during 2014 JET Campaign and is envisaged that will operate routinely from 2015 campaign onwards in any plasma condition (including ITER relevant scenarios). This mode of operation elevated the importance of the polarimetry as a diagnostic tool in the view of future fusion experiments.

Invited Article: A novel calibration method for the JET real-time far infrared polarimeter and integration of polarimetry-based line-integrated density measurements for machine protection of a fusion plant

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

Boboc, A., E-mail: Alexandru.Boboc@ccfe.ac.uk; Felton, R.; Dalley, S.

2015-09-15

In this paper, we present the work in the implementation of a new calibration for the JET real-time polarimeter based on the complex amplitude ratio technique and a new self-validation mechanism of data. This allowed easy integration of the polarimetry measurements into the JET plasma density control (gas feedback control) and as well as machine protection systems (neutral beam injection heating safety interlocks). The new addition was used successfully during 2014 JET Campaign and is envisaged that will operate routinely from 2015 campaign onwards in any plasma condition (including ITER relevant scenarios). This mode of operation elevated the importance ofmore » the polarimetry as a diagnostic tool in the view of future fusion experiments.« less

Visual terrain mapping for traversable path planning of mobile robots

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Amrani, Rachida; Tunstel, Edward W.

2004-10-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

Time-resolved wide-field optically sectioned fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dupuis, Guillaume; Benabdallah, Nadia; Chopinaud, Aurélien; Mayet, Céline; Lévêque-Fort, Sandrine

2013-02-01

We present the implementation of a fast wide-field optical sectioning technique called HiLo microscopy on a fluorescence lifetime imaging microscope. HiLo microscopy is based on the fusion of two images, one with structured illumination and another with uniform illumination. Optically sectioned images are then digitally generated thanks to a fusion algorithm. HiLo images are comparable in quality with confocal images but they can be acquired faster over larger fields of view. We obtain 4D imaging by combining HiLo optical sectioning, time-gated detection, and z-displacement. We characterize the performances of this set-up in terms of 3D spatial resolution and time-resolved capabilities in both fixed- and live-cell imaging modes.

Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

PubMed Central

Shaukat, Affan; Blacker, Peter C.; Spiteri, Conrad; Gao, Yang

2016-01-01

In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers deployed to explore extraterrestrial surfaces are required to perceive and model the environment with little or no intervention from the ground station. Up to date, stereopsis represents the state-of-the art method and can achieve short-distance planetary surface modelling. However, future space missions will require scene reconstruction at greater distance, fidelity and feature complexity, potentially using other sensors like Light Detection And Ranging (LIDAR). LIDAR has been extensively exploited for target detection, identification, and depth estimation in terrestrial robotics, but is still under development to become a viable technology for space robotics. This paper will first review current methods for scene reconstruction and terrain modelling using cameras in planetary robotics and LIDARs in terrestrial robotics; then we will propose camera-LIDAR fusion as a feasible technique to overcome the limitations of either of these individual sensors for planetary exploration. A comprehensive analysis will be presented to demonstrate the advantages of camera-LIDAR fusion in terms of range, fidelity, accuracy and computation. PMID:27879625

Phase Aberrations And Beam Cleanup Techniques In Carbon-Dioxide Laser Fusion Systems

NASA Astrophysics Data System (ADS)

Viswanathan, V. K.

1981-12-01

This paper describes the various carbon dioxide laser fusion systems at Los Alamos from the point of view of an optical designer. The types of phase aberrations present in these systems, as well as the beam cleanup techniques that can be used to improve the beam optical quality, are discussed. As this is a review article, some previously published results are also used where relevant.

Multimodality Inferring of Human Cognitive States Based on Integration of Neuro-Fuzzy Network and Information Fusion Techniques

NASA Astrophysics Data System (ADS)

Yang, G.; Lin, Y.; Bhattacharya, P.

2007-12-01

To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human's operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressions or cues, the recent trend to infer the human state is to consider multimodality features of the human operator. In this paper, we present a method for multimodality inferring of human cognitive states by integrating neuro-fuzzy network and information fusion techniques. To demonstrate the effectiveness of this method, we take the driver fatigue detection as an example. The proposed method has, in particular, the following new features. First, human expressions are classified into four categories: (i) casual or contextual feature, (ii) contact feature, (iii) contactless feature, and (iv) performance feature. Second, the fuzzy neural network technique, in particular Takagi-Sugeno-Kang (TSK) model, is employed to cope with uncertain behaviors. Third, the sensor fusion technique, in particular ordered weighted aggregation (OWA), is integrated with the TSK model in such a way that cues are taken as inputs to the TSK model, and then the outputs of the TSK are fused by the OWA which gives outputs corresponding to particular cognitive states under interest (e.g., fatigue). We call this method TSK-OWA. Validation of the TSK-OWA, performed in the Northeastern University vehicle drive simulator, has shown that the proposed method is promising to be a general tool for human cognitive state inferring and a special tool for the driver fatigue detection.

Segmentation of lung nodules in computed tomography images using dynamic programming and multidirection fusion techniques.

PubMed

Wang, Qian; Song, Enmin; Jin, Renchao; Han, Ping; Wang, Xiaotong; Zhou, Yanying; Zeng, Jianchao

2009-06-01

The aim of this study was to develop a novel algorithm for segmenting lung nodules on three-dimensional (3D) computed tomographic images to improve the performance of computer-aided diagnosis (CAD) systems. The database used in this study consists of two data sets obtained from the Lung Imaging Database Consortium. The first data set, containing 23 nodules (22% irregular nodules, 13% nonsolid nodules, 17% nodules attached to other structures), was used for training. The second data set, containing 64 nodules (37% irregular nodules, 40% nonsolid nodules, 62% nodules attached to other structures), was used for testing. Two key techniques were developed in the segmentation algorithm: (1) a 3D extended dynamic programming model, with a newly defined internal cost function based on the information between adjacent slices, allowing parameters to be adapted to each slice, and (2) a multidirection fusion technique, which makes use of the complementary relationships among different directions to improve the final segmentation accuracy. The performance of this approach was evaluated by the overlap criterion, complemented by the true-positive fraction and the false-positive fraction criteria. The mean values of the overlap, true-positive fraction, and false-positive fraction for the first data set achieved using the segmentation scheme were 66%, 75%, and 15%, respectively, and the corresponding values for the second data set were 58%, 71%, and 22%, respectively. The experimental results indicate that this segmentation scheme can achieve better performance for nodule segmentation than two existing algorithms reported in the literature. The proposed 3D extended dynamic programming model is an effective way to segment sequential images of lung nodules. The proposed multidirection fusion technique is capable of reducing segmentation errors especially for no-nodule and near-end slices, thus resulting in better overall performance.

A novel method to recover DD fusion proton CR-39 data corrupted by fast ablator ions at OMEGA and the National Ignition Facility

DOE PAGES

Sutcliffe, G. D.; Milanese, L. M.; Orozco, D.; ...

2016-08-05

CR-39 detectors are used routinely in inertial confinement fusion (ICF) experiments as a part of nuclear diagnostics. CR-39 is filtered to stop fast ablator ions which have been accelerated from an ICF implosion due to electric fields caused by laser-plasma interactions. In some experiments, the filtering is insufficient to block these ions and the fusion-product signal tracks are lost in the large background of accelerated ion tracks. A technique for recovering signal in these scenarios has been developed, tested, and implemented successfully. The technique involves removing material from the surface of the CR-39 to a depth beyond the endpoint ofmore » the ablator ion tracks. The technique preserves signal magnitude (yield) as well as structure in radiograph images. The technique is effective when signal particle range is at least 10 μm deeper than the necessary bulk material removal.« less

A novel method to recover DD fusion proton CR-39 data corrupted by fast ablator ions at OMEGA and the National Ignition Facility

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

Sutcliffe, G. D., E-mail: gdsut@mit.edu; Milanese, L. M.; Orozco, D.

2016-11-15

CR-39 detectors are used routinely in inertial confinement fusion (ICF) experiments as a part of nuclear diagnostics. CR-39 is filtered to stop fast ablator ions which have been accelerated from an ICF implosion due to electric fields caused by laser-plasma interactions. In some experiments, the filtering is insufficient to block these ions and the fusion-product signal tracks are lost in the large background of accelerated ion tracks. A technique for recovering signal in these scenarios has been developed, tested, and implemented successfully. The technique involves removing material from the surface of the CR-39 to a depth beyond the endpoint ofmore » the ablator ion tracks. The technique preserves signal magnitude (yield) as well as structure in radiograph images. The technique is effective when signal particle range is at least 10 μm deeper than the necessary bulk material removal.« less

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.

Simulated Radioscapholunate Fusion Alters Carpal Kinematics While Preserving Dart-Thrower's Motion

PubMed Central

Calfee, Ryan P.; Leventhal, Evan L.; Wilkerson, Jim; Moore, Douglas C.; Akelman, Edward; Crisco, Joseph J.

2014-01-01

Purpose Midcarpal degeneration is well documented after radioscapholunate fusion. This study tested the hypothesis that radioscapholunate fusion alters the kinematic behavior of the remaining lunotriquetral and midcarpal joints, with specific focus on the dart-thrower's motion. Methods Simulated radioscapholunate fusions were performed on 6 cadaveric wrists in an anatomically neutral posture. Two 0.060-in. carbon fiber pins were placed from proximal to distal across the radiolunate and radioscaphoid joints, respectively. The wrists were passively positioned in a custom jig toward a full range of motion along the orthogonal axes as well as oblique motions, with additional intermediate positions along the dart-thrower's path. Using a computed tomography– based markerless bone registration technique, each carpal bone's three-dimensional rotation was defined as a function of wrist flexion/extension from the pinned neutral position. Kinematic data was analyzed against data collected on the same wrist prior to fixation using hierarchical linear regression analysis and paired Student's t-tests. Results After simulated fusion, wrist motion was restricted to an average flexion-extension arc of 48°, reduced from 77°, and radial-ulnar deviation arc of 19°, reduced from 33°. The remaining motion was maximally preserved along the dart-thrower's path from radial-extension toward ulnar-flexion. The simulated fusion significantly increased rotation through the scaphotrapezial joint, scaphocapitate joint, triquetrohamate joint, and lunotriquetral joint. For example, in the pinned wrist, the rotation of the hamate relative to the triquetrum increased 85%. Therefore, during every 10° of total wrist motion, the hamate rotated an average of nearly 8° relative to the triquetrum after pinning versus 4° in the normal state. Conclusions Simulated radioscapholunate fusion altered midcarpal and lunotriquetral kinematics. The increased rotations across these remaining joints provide one potential explanation for midcarpal degeneration after radioscapholunate fusion. Additionally, this fusion model confirms the dart-thrower's hypothesis, as wrist motion after simulated radioscapholunate fusion was primarily preserved from radial-extension toward ulnar-flexion. PMID:18406953

Occipitocervical fusion in skeletal dysplasia: a new surgical technique.

PubMed

Sitoula, Prakash; Mackenzie, William G; Shah, Suken A; Thacker, Mihir; Ditro, Colleen; Holmes, Laurens; Campbell, Jeffrey W; Rogers, Kenneth J

2014-07-01

Retrospective cohort study. This study describes clinical and radiological results of a new cable technique for occipitocervical fusion (OCF) in children with skeletal dysplasia (SD). Anatomical variability and poor bone quality make upper cervical surgery technically challenging in patients with SD. We present a new cable technique for OCF in children with SD when the posterior elements are not of a size or quality for other types of instrumentation. Retrospective review of 24 patients with SD (8 boys, 16 girls) who underwent OCF between 2001 and 2011. In this technique, cables provide compression across a bone graft that is prevented from entering the canal and the graft resists excessive lordosis. Demographic and radiographical data are presented. All patients were followed for initial outcomes of surgery, and 20 patients (83%) were followed for 2 years or more for mid- and long-term outcomes. Mean age at surgery was 6.5 years and mean follow-up was 4.1 ± 2.4 years. This technique was used as a primary procedure in 20 and a revision procedure in 4 patients. Diagnoses included Morquio syndrome (6), spondyloepiphyseal dysplasia (9), spondyloepimetaphyseal dysplasia (5), metatropic dysplasia (3), and Kniest syndrome (1). Ten patients had upper cervical instability and features of cervical myelopathy, and the remaining 14 patients had instability and signal changes on magnetic resonance image. Fusion extended from occiput to C2 in 71% patients, and upper cervical decompression was needed in 92% patients. Postoperatively, all patients were immobilized in a halo vest for mean duration of 12 weeks. Fusion was achieved in all patients. Complications included halo pin-tract infections (7), junctional instability (2), and extension of fusion (4). This new cable technique is a good alternative for OCF in patients with SD who have altered anatomy at the craniocervical junction not amenable to rigid internal fixation. 4.

Local bone graft harvesting and volumes in posterolateral lumbar fusion: a technical report.

PubMed

Carragee, Eugene J; Comer, Garet C; Smith, Micah W

2011-06-01

In lumbar surgery, local bone graft is often harvested and used in posterolateral fusion procedures. The volume of local bone graft available for posterolateral fusion has not been determined in North American patients. Some authors have described this as minimal, but others have suggested the volume was sufficient to be reliably used as a stand-alone bone graft substitute for single-level fusion. To describe the technique used and determine the volume of local bone graft available in a cohort of patients undergoing single-level primary posterolateral fusion by the authors harvesting technique. Technical description and cohort report. Consecutive patients undergoing lumbar posterolateral fusion with or without instrumentation for degenerative processes. Local bone graft volume. Consecutive patients undergoing lumbar posterolateral fusion with or without instrumentation for degenerative processes of were studied. Local bone graft was harvested by a standard method in each patient and the volume measured by a standard procedure. Twenty-five patients were studied, and of these 11 (44%) had a previous decompression. The mean volume of local bone graft harvested was measured to be 25 cc (range, 12-36 cc). Local bone graft was augmented by iliac crest bone in six of 25 patients (24%) if the posterolateral fusion bed was not well packed with local bone alone. There was a trend to greater local bone graft volumes in men and in patients without previous decompression. Large volumes of local bone can be harvested during posterolateral lumbar fusion surgery. Even in patients with previous decompression the volume harvested is similar to that reported harvested from the posterior iliac crest for single-level fusion. Copyright © 2011 Elsevier Inc. All rights reserved.

Novel chromosomal rearrangements and break points at the t(6;9) in salivary adenoid cystic carcinoma: association with MYB-NFIB chimeric fusion, MYB expression, and clinical outcome.

PubMed

Mitani, Yoshitsugu; Rao, Pulivarthi H; Futreal, P Andrew; Roberts, Dianna B; Stephens, Philip J; Zhao, Yi-Jue; Zhang, Li; Mitani, Mutsumi; Weber, Randal S; Lippman, Scott M; Caulin, Carlos; El-Naggar, Adel K

2011-11-15

To investigate the molecular genetic heterogeneity associated with the t(6:9) in adenoid cystic carcinoma (ACC) and correlate the findings with patient clinical outcome. Multimolecular and genetic techniques complemented with massive pair-ended sequencing and single-nucleotide polymorphism array analyses were used on tumor specimens from 30 new and 52 previously analyzed fusion transcript-negative ACCs by reverse transcriptase PCR (RT-PCR). MYB mRNA expression level was determined by quantitative RT-PCR. The results of 102 tumors (30 new and 72 previously reported cases) were correlated with the clinicopathologic factors and patients' survival. The FISH analysis showed 34 of 82 (41.5%) fusion-positive tumors and molecular techniques identified fusion transcripts in 21 of the 82 (25.6%) tumors. Detailed FISH analysis of 11 out the 15 tumors with gene fusion without transcript formation showed translocation of NFIB sequences to proximal or distal sites of the MYB gene. Massive pair-end sequencing of a subset of tumors confirmed the proximal translocation to an NFIB sequence and led to the identification of a new fusion gene (NFIB-AIG1) in one of the tumors. Overall, MYB-NFIB gene fusion rate by FISH was in 52.9% whereas fusion transcript forming incidence was 38.2%. Significant statistical association between the 5' MYB transcript expression and patient survival was found. We conclude that: (i) t(6;9) results in complex genetic and molecular alterations in ACC, (ii) MYB-NFIB gene fusion may not always be associated with chimeric transcript formation, (iii) noncanonical MYB-NFIB gene fusions occur in a subset of tumors, (iv) high MYB expression correlates with worse patient survival.

Novel Chromosomal Rearrangements and breakpoints at the t(6;9) in Salivary Adenoid Cystic Carcinoma: association with MYB-NFIB chimeric fusion, MYB expression, and clinical outcome

PubMed Central

Mitani, Yoshitsugu; Rao, Pulivarthi H.; Futreal, P. Andrew; Roberts, Dianna B.; Stephens, Philip J.; Zhao, Yi-Jue; Zhang, Li; Mitani, Mutsumi; Weber, Randal S.; Lippman, Scott M.; Caulin, Carlos; El-Naggar, Adel K.

2011-01-01

Objective To investigate the molecular-genetic heterogeneity associated with the t(6:9) in adenoid cystic carcinoma (ACC) and correlate the findings with patient clinical outcome. Experimental Design Multi-molecular and genetic techniques complemented with massive pair-ended sequencing and SNP array analyses were used on tumor specimens from 30 new and 52 previously RT-PCR analyzed fusion transcript negative ACCs. MYB mRNA expression level was determined by quantitative RT-PCR. The results of 102 tumors (30 new and 72 previously reported cases) were correlated with the clinicopathologic factors and patients’ survival. Results The FISH analysis showed 34/82 (41.5%) fusion positive tumors and molecular techniques identified fusion transcripts in 21 of the 82 (25.6%) tumors. Detailed FISH analysis of 11 out the 15 tumors with gene fusion without transcript formation showed translocation of NFIB sequences to proximal or distal sites of the MYB gene. Massive pair-end sequencing of a subset of tumors confirmed the proximal translocation to an NFIB sequence and led to the identification of a new fusion gene (NFIB-AIG1) in one of the tumors. Overall, MYB-NFIB gene fusion rate by FISH was in 52.9% while fusion transcript forming incidence was 38.2%. Significant statistical association between the 5′ MYB transcript expression and patient survival was found. Conclusions We conclude that: 1) t(6;9) results in a complex genetic and molecular alterations in ACC, 2) MYB-NFIB gene fusion may not always be associated with chimeric transcript formation, 3) non-canonical MYB, NFIB gene fusions occur in a subset of tumors, 4) high MYB expression correlates with worse patient survival. PMID:21976542

A New Approach to Image Fusion Based on Cokriging

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; LeMoigne, Jacqueline; Mount, David M.; Morisette, Jeffrey T.

2005-01-01

We consider the image fusion problem involving remotely sensed data. We introduce cokriging as a method to perform fusion. We investigate the advantages of fusing Hyperion with ALI. The evaluation is performed by comparing the classification of the fused data with that of input images and by calculating well-chosen quantitative fusion quality metrics. We consider the Invasive Species Forecasting System (ISFS) project as our fusion application. The fusion of ALI with Hyperion data is studies using PCA and wavelet-based fusion. We then propose utilizing a geostatistical based interpolation method called cokriging as a new approach for image fusion.

The application of microwave digestion in decomposing some refractory ore samples with solid fusion agent.

PubMed

Lu, Yan; Li, Gang; Liu, Wei; Yuan, Hongyan; Xiao, Dan

2018-08-15

It is known that most of the refractory ore are the basis of national economy and widely applied in various fields, however, the complexity of the chemical composition and the diversity of the crystallinity in the mineral phases make the sample pre-treatment of refractory ore still remains a challenge. In this work, the complete decomposition of the refractory ore sample can be achieved just by exposing the solid fusion agent and the refractory ore sample in the microwave irradiation environment for a few minutes, and induced by a drop of water. A digestion time of 15 min for 3.0 g solid fusion agent mixture of sodium peroxide/sodium carbonate (Na 2 O 2 /Na 2 CO 3 ) in a corundum crucible via microwave heating is sufficient to decompose 0.1 g refractory ore sample. An excellent microwave digestion solid agent should meet the following conditions, a good decomposition ability, an outstanding ability of absorbing microwave energy and converting it into heat quickly, a higher melting point than the decomposing temperature of the ore sample. In the research, the induction effect of water plays an important role for the microwave digestion. The energy which is released by the reaction of water and the solid fusion agent (Na 2 O 2 ) is the key to decompose refractory ore samples with solid fusion agent, which replenished the total energy required for the microwave digestion and made the microwave digestion completed successfully. This microwave digestion technique has good reproducibility and precision, RSD % for Mo, Fe, Ti, Cr and W in the refractory ore samples were all better than 6, except RSD % for Be of about 8 because of the influence of matrix-effect. Meanwhile, the analysis results of the elements in the refractory ore samples provided by the microwave digestion technique were all in good agreement with the analysis results provided by the traditional fusion method except for Cr in the mixture ore samples. In the study, the non-linear dependence of the electromagnetic and thermal properties of the solid fusion agent on temperature under microwave irradiation and the selective heating of microwave are fully applied in this simple microwave technique. Comparing to the traditional fusion decomposition method, this microwave digestion technique is a simple, economical, fast and energy-saving sample pre-treatment technique. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparison of complications, costs, and length of stay of three different lumbar interbody fusion techniques: an analysis of the Nationwide Inpatient Sample database.

PubMed

Goz, Vadim; Weinreb, Jeffrey H; Schwab, Frank; Lafage, Virginie; Errico, Thomas J

2014-09-01

Lumbar interbody fusion (LIF) techniques have been used for years to treat a number of pathologies of the lower back. These procedures may use an anterior, posterior, or combined surgical approach. Each approach is associated with a unique set of complications, but the exact prevalence of complications associated with each approach remains unclear. To investigate the rates of perioperative complications of anterior lumbar interbody fusion (ALIF), posterior/transforaminal lumbar interbody fusion (P/TLIF), and LIF with a combined anterior-posterior interbody fusion (APF). Retrospective review of national data from a large administrative database. Patients undergoing ALIF, P/TLIF, or APF. Perioperative complications, length of stay (LOS), total costs, and mortality. The Nationwide Inpatient Sample database was queried for patients undergoing ALIF, P/TLIF, or APF between 2001 and 2010 as identified via International Classification of Diseases, ninth revision codes. Univariate analyses were carried out comparing the three cohorts in terms of the outcomes of interest. Multivariate analysis for primary outcomes was carried out adjusting for overall comorbidity burden, race, gender, age, and length of fusion. National estimates of annual total number of procedures were calculated based on the provided discharge weights. Geographic distribution of the three cohorts was also investigated. An estimated total of 923,038 LIFs were performed between 2001 and 2010 in the United States. Posterior/transforaminal lumbar interbody fusions accounted for 79% to 86% of total LIFs between 2001 and 2010, ALIFs for 10% to 15%, and APF decreased from 10% in 2002 to less than 1% in 2010. On average, P/TLIF patients were oldest (54.55 years), followed by combined approach (47.23 years) and ALIF (46.94 years) patients (p<.0001). Anterior lumbar interbody fusion, P/TLIF, and combined surgical costs were $75,872, $65,894, and $92,249, respectively (p<.0001). Patients in the P/TLIF cohort had the greatest number of comorbidities, having the highest prevalence for 10 of 17 comorbidities investigated. Anterior-posterior interbody fusion group was associated with the greatest number of complications, having the highest incidence of 12 of the 16 complications investigated. These data help to define the perioperative risks for several LIF approaches. Comparison of outcomes showed that a combined approach is more expensive and associated with greater LOS, whereas ALIF is associated with the highest postoperative mortality. These trends should be taken into consideration during surgical planning to improve clinical outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Computed tomography angiography-fluoroscopy image fusion allows visceral vessel cannulation without angiography during fenestrated endovascular aneurysm repair.

PubMed

Schwein, Adeline; Chinnadurai, Ponraj; Behler, Greg; Lumsden, Alan B; Bismuth, Jean; Bechara, Carlos F

2018-07-01

Fenestrated endovascular aneurysm repair (FEVAR) is an evolving technique to treat juxtarenal abdominal aortic aneurysms (AAAs). Catheterization of visceral and renal vessels after the deployment of the fenestrated main body device is often challenging, usually requiring additional fluoroscopy and multiple digital subtraction angiograms. The aim of this study was to assess the clinical utility and accuracy of a computed tomography angiography (CTA)-fluoroscopy image fusion technique in guiding visceral vessel cannulation during FEVAR. Between August 2014 and September 2016, all consecutive patients who underwent FEVAR at our institution using image fusion guidance were included. Preoperative CTA images were fused with intraoperative fluoroscopy after coregistering with non-contrast-enhanced cone beam computed tomography (syngo 3D3D image fusion; Siemens Healthcare, Forchheim, Germany). The ostia of the visceral vessels were electronically marked on CTA images (syngo iGuide Toolbox) and overlaid on live fluoroscopy to guide vessel cannulation after fenestrated device deployment. Clinical utility of image fusion was evaluated by assessing the number of dedicated angiograms required for each visceral or renal vessel cannulation and the use of optimized C-arm angulation. Accuracy of image fusion was evaluated from video recordings by three raters using a binary qualitative assessment scale. A total of 26 patients (17 men; mean age, 73.8 years) underwent FEVAR during the study period for juxtarenal AAA (17), pararenal AAA (6), and thoracoabdominal aortic aneurysm (3). Video recordings of fluoroscopy from 19 cases were available for review and assessment. A total of 46 vessels were cannulated; 38 of 46 (83%) of these vessels were cannulated without angiography but based only on image fusion guidance: 9 of 11 superior mesenteric artery cannulations and 29 of 35 renal artery cannulations. Binary qualitative assessment showed that 90% (36/40) of the virtual ostia overlaid on live fluoroscopy were accurate. Optimized C-arm angulations were achieved in 35% of vessel cannulations (0/9 for superior mesenteric artery cannulation, 12/25 for renal arteries). Preoperative CTA-fluoroscopy image fusion guidance during FEVAR is a valuable and accurate tool that allows visceral and renal vessel cannulation without the need of dedicated angiograms, thus avoiding additional injection of contrast material and radiation exposure. Further refinements, such as accounting for device-induced aortic deformation and automating the image fusion workflow, will bolster this technology toward optimal routine clinical use. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Costs and effects in lumbar spinal fusion. A follow-up study in 136 consecutive patients with chronic low back pain

PubMed Central

Christensen, Finn Bjarke; Christiansen, Terkel; Bünger, Cody

2006-01-01

Although cost-effectiveness is becoming the foremost evaluative criterion within health service management of spine surgery, scientific knowledge about cost-patterns and cost-effectiveness is limited. The aims of this study were (1) to establish an activity-based method for costing at the patient-level, (2) to investigate the correlation between costs and effects, (3) to investigate the influence of selected patient characteristics on cost-effectiveness and, (4) to investigate the incremental cost-effectiveness ratio of (a) posterior instrumentation and (b) intervertebral anterior support in lumbar spinal fusion. We hypothesized a positive correlation between costs and effects, that determinants of effects would also determine cost-effectiveness, and that posterolateral instrumentation and anterior intervertebral support are cost-effective adjuncts in posterolateral lumbar fusion. A cohort of 136 consecutive patients with chronic low back pain, who were surgically treated from January 2001 through January 2003, was followed until 2 years postoperatively. Operations took place at University Hospital of Aarhus and all patients had either (1) non-instrumented posterolateral lumbar spinal fusion, (2) instrumented posterolateral lumbar spinal fusion, or (3) instrumented posterolateral lumbar spinal fusion + anterior intervertebral support. Analysis of costs was performed at the patient-level, from an administrator’s perspective, by means of Activity-Based-Costing. Clinical effects were measured by means of the Dallas Pain Questionnaire and the Low Back Pain Rating Scale at baseline and 2 years postoperatively. Regression models were used to reveal determinants for costs and effects. Costs and effects were analyzed as a net-benefit measure to reveal determinants for cost-effectiveness, and finally, adjusted analysis (for non-random allocation of patients) was performed in order to reveal the incremental cost-effectiveness ratios of (a) posterior instrumentation and (b) anterior support. The costs of non-instrumented posterolateral spinal fusion were estimated at DKK 88,285(95% CI 81,369;95,546), instrumented posterolateral spinal fusion at DKK 94,396(95% CI 89,865;99,574) and instrumented posterolateral lumbar spinal fusion + anterior intervertebral support at DKK 120,759(95% CI 111,981;133,738). The net-benefit of the regimens was significantly affected by smoking and functional disability in psychosocial life areas. Multi-level fusion and surgical technique significantly affected the net-benefit as well. Surprisingly, no correlation was found between treatment costs and treatment effects. Incremental analysis suggested that the probability of posterior instrumentation being cost-effective was limited, whereas the probability of anterior intervertebral support being cost-effective escalates as willingness-to-pay per effect unit increases. This study reveals useful and hitherto unknown information both about cost-patterns at the patient-level and determinants of cost-effectiveness. The overall conclusion of the present investigation is a recommendation to focus further on determinants of cost-effectiveness. For example, patient characteristics that are modifiable at a relatively low expense may have greater influence on cost-effectiveness than the surgical technique itself—at least from an administrator’s perspective. PMID:16871387

Complications with axial presacral lumbar interbody fusion: A 5-year postmarketing surveillance experience

PubMed Central

Gundanna, Mukund I.; Miller, Larry E.; Block, Jon E.

2011-01-01

Background Open and minimally invasive lumbar fusion procedures have inherent procedural risks, with posterior and transforaminal approaches resulting in significant soft-tissue injury and the anterior approach endangering organs and major blood vessels. An alternative lumbar fusion technique uses a small paracoccygeal incision and a presacral approach to the L5-S1 intervertebral space, which avoids critical structures and may result in a favorable safety profile versus open and other minimally invasive fusion techniques. The purpose of this study was to evaluate complications associated with axial interbody lumbar fusion procedures using the Axial Lumbar Interbody Fusion (AxiaLIF) System (TranS1, Wilmington, North Carolina) in the postmarketing period. Methods Between March 2005 and March 2010, 9,152 patients underwent interbody fusion with the AxiaLIF System through an axial presacral approach. A single-level L5-S1 fusion was performed in 8,034 patients (88%), and a 2-level (L4-S1) fusion was used in 1,118 (12%). A predefined database was designed to record device- or procedure-related complaints via spontaneous reporting. The complications that were recorded included bowel injury, superficial wound and systemic infections, transient intraoperative hypotension, migration, subsidence, presacral hematoma, sacral fracture, vascular injury, nerve injury, and ureter injury. Results Complications were reported in 120 of 9,152 patients (1.3%). The most commonly reported complications were bowel injury (n = 59, 0.6%) and transient intraoperative hypotension (n = 20, 0.2%). The overall complication rate was similar between single-level (n = 102, 1.3%) and 2-level (n = 18, 1.6%) fusion procedures, with no significant differences noted for any single complication. Conclusions The 5-year postmarketing surveillance experience with the AxiaLIF System suggests that axial interbody lumbar fusion through the presacral approach is associated with a low incidence of complications. The overall complication rates observed in our evaluation compare favorably with those reported in trials of open and minimally invasive lumbar fusion surgery. PMID:25802673

Multi-modality image fusion based on enhanced fuzzy radial basis function neural networks.

PubMed

Chao, Zhen; Kim, Dohyeon; Kim, Hee-Joung

2018-04-01

In clinical applications, single modality images do not provide sufficient diagnostic information. Therefore, it is necessary to combine the advantages or complementarities of different modalities of images. Recently, neural network technique was applied to medical image fusion by many researchers, but there are still many deficiencies. In this study, we propose a novel fusion method to combine multi-modality medical images based on the enhanced fuzzy radial basis function neural network (Fuzzy-RBFNN), which includes five layers: input, fuzzy partition, front combination, inference, and output. Moreover, we propose a hybrid of the gravitational search algorithm (GSA) and error back propagation algorithm (EBPA) to train the network to update the parameters of the network. Two different patterns of images are used as inputs of the neural network, and the output is the fused image. A comparison with the conventional fusion methods and another neural network method through subjective observation and objective evaluation indexes reveals that the proposed method effectively synthesized the information of input images and achieved better results. Meanwhile, we also trained the network by using the EBPA and GSA, individually. The results reveal that the EBPGSA not only outperformed both EBPA and GSA, but also trained the neural network more accurately by analyzing the same evaluation indexes. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Cleaved thioredoxin fusion protein enables the crystallization of poorly soluble ERα in complex with synthetic ligands

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

Cura, Vincent; Gangloff, Monique; Eiler, Sylvia

2008-01-01

A new crystallization strategy: the presence of cleaved thioredoxin fusion is critical for crystallization of the estrogen nuclear receptor ligand binding domain in complex with synthetic ligands. This novel technique should be regarded as an interesting alternative for crystallization of difficult proteins. The ligand-binding domain (LBD) of human oestrogen receptor α was produced in Escherichia coli as a cleavable thioredoxin (Trx) fusion in order to improve solubility. Crystallization trials with either cleaved and purified LBD or with the purified fusion protein both failed to produce crystals. In another attempt, Trx was not removed from the LBD after endoproteolytic cleavage andmore » its presence promoted nucleation and subsequent crystal growth, which allowed the structure determination of two different LBD–ligand–coactivator peptide complexes at 2.3 Å resolution. This technique is likely to be applicable to other low-solubility proteins.« less

Measurements of fusion neutron yields by neutron activation technique: Uncertainty due to the uncertainty on activation cross-sections

NASA Astrophysics Data System (ADS)

Stankunas, Gediminas; Batistoni, Paola; Sjöstrand, Henrik; Conroy, Sean; JET Contributors

2015-07-01

The neutron activation technique is routinely used in fusion experiments to measure the neutron yields. This paper investigates the uncertainty on these measurements as due to the uncertainties on dosimetry and activation reactions. For this purpose, activation cross-sections were taken from the International Reactor Dosimetry and Fusion File (IRDFF-v1.05) in 640 groups ENDF-6 format for several reactions of interest for both 2.5 and 14 MeV neutrons. Activation coefficients (reaction rates) have been calculated using the neutron flux spectra at JET vacuum vessel, both for DD and DT plasmas, calculated by MCNP in the required 640-energy group format. The related uncertainties for the JET neutron spectra are evaluated as well using the covariance data available in the library. These uncertainties are in general small, but not negligible when high accuracy is required in the determination of the fusion neutron yields.

Applying a nonlinear, pitch-catch, ultrasonic technique for the detection of kissing bonds in friction stir welds.

PubMed

Delrue, Steven; Tabatabaeipour, Morteza; Hettler, Jan; Van Den Abeele, Koen

2016-05-01

Friction stir welding (FSW) is a promising technology for the joining of aluminum alloys and other metallic admixtures that are hard to weld by conventional fusion welding. Although FSW generally provides better fatigue properties than traditional fusion welding methods, fatigue properties are still significantly lower than for the base material. Apart from voids, kissing bonds for instance, in the form of closed cracks propagating along the interface of the stirred and heat affected zone, are inherent features of the weld and can be considered as one of the main causes of a reduced fatigue life of FSW in comparison to the base material. The main problem with kissing bond defects in FSW, is that they currently are very difficult to detect using existing NDT methods. Besides, in most cases, the defects are not directly accessible from the exposed surface. Therefore, new techniques capable of detecting small kissing bond flaws need to be introduced. In the present paper, a novel and practical approach is introduced based on a nonlinear, single-sided, ultrasonic technique. The proposed inspection technique uses two single element transducers, with the first transducer transmitting an ultrasonic signal that focuses the ultrasonic waves at the bottom side of the sample where cracks are most likely to occur. The large amount of energy at the focus activates the kissing bond, resulting in the generation of nonlinear features in the wave propagation. These nonlinear features are then captured by the second transducer operating in pitch-catch mode, and are analyzed, using pulse inversion, to reveal the presence of a defect. The performance of the proposed nonlinear, pitch-catch technique, is first illustrated using a numerical study of an aluminum sample containing simple, vertically oriented, incipient cracks. Later, the proposed technique is also applied experimentally on a real-life friction stir welded butt joint containing a kissing bond flaw. Copyright © 2016 Elsevier B.V. All rights reserved.

Biomechanical advantages of robot-assisted pedicle screw fixation in posterior lumbar interbody fusion compared with freehand technique in a prospective randomized controlled trial-perspective for patient-specific finite element analysis.

PubMed

Kim, Ho-Joong; Kang, Kyoung-Tak; Park, Sung-Cheol; Kwon, Oh-Hyo; Son, Juhyun; Chang, Bong-Soon; Lee, Choon-Ki; Yeom, Jin S; Lenke, Lawrence G

2017-05-01

There have been conflicting results on the surgical outcome of lumbar fusion surgery using two different techniques: robot-assisted pedicle screw fixation and conventional freehand technique. In addition, there have been no studies about the biomechanical issues between both techniques. This study aimed to investigate the biomechanical properties in terms of stress at adjacent segments using robot-assisted pedicle screw insertion technique (robot-assisted, minimally invasive posterior lumbar interbody fusion, Rom-PLIF) and freehand technique (conventional, freehand, open approach, posterior lumbar interbody fusion, Cop-PLIF) for instrumented lumbar fusion surgery. This is an additional post-hoc analysis for patient-specific finite element (FE) model. The sample is composed of patients with degenerative lumbar disease. Intradiscal pressure and facet contact force are the outcome measures. Patients were randomly assigned to undergo an instrumented PLIF procedure using a Rom-PLIF (37 patients) or a Cop-PLIF (41), respectively. Five patients in each group were selected using a simple random sampling method after operation, and 10 preoperative and postoperative lumbar spines were modeled from preoperative high-resolution computed tomography of 10 patients using the same method for a validated lumbar spine model. Under four pure moments of 7.5 Nm, the changes in intradiscal pressure and facet joint contact force at the proximal adjacent segment following fusion surgery were analyzed and compared with preoperative states. The representativeness of random samples was verified. Both groups showed significant increases in postoperative intradiscal pressure at the proximal adjacent segment under four moments, compared with the preoperative state. The Cop-PLIF models demonstrated significantly higher percent increments of intradiscal pressure at proximal adjacent segments under extension, lateral bending, and torsion moments than the Rom-PLIF models (p=.032, p=.008, and p=.016, respectively). Furthermore, the percent increment of facet contact force was significantly higher in the Cop-PLIF models under extension and torsion moments than in the Rom-PLIF models (p=.016 under both extension and torsion moments). The present study showed the clinical application of subject-specific FE analysis in the spine. Even though there was biomechanical superiority of the robot-assisted insertions in terms of alleviation of stress increments at adjacent segments after fusion, cautious interpretation is needed because of the small sample size. Copyright © 2016 Elsevier Inc. All rights reserved.

Impact of Starting Point and Bicortical Purchase of C1 Lateral Mass Screws on Atlantoaxial Fusion: Meta-Analysis and Review of the Literature.

PubMed

Elliott, Robert E; Tanweer, Omar; Smith, Michael L; Frempong-Boadu, Anthony

2015-08-01

Structured review of literature and application of meta-analysis statistical techniques. Review published series describing clinical and radiographic outcomes of patients treated with C1 lateral mass screws (C1LMS), specifically analyzing the impact of starting point and bicortical purchase on successful atlantoaxial arthrodesis. Biomechanical studies suggest posterior arch screws and C1LMS with bicortical purchase are stronger than screws placed within the center of the lateral mass or those with unicortical purchase. Online databases were searched for English-language articles between 1994 and 2012 describing posterior atlantal instrumentation with C1LMS. Thirty-four studies describing 1247 patients having posterior atlantoaxial fusion with C1LMS met inclusion criteria. All studies provided class III evidence. Arthrodesis was quite successful regardless of technique (99.0% overall). Meta-analysis and multivariate regression analyses showed that neither posterior arch starting point nor bicortical screw purchase translated into a higher rate of successful arthrodesis. There were no complications from bicortical screw purchase. The Goel-Harms technique is a very safe and successful technique for achieving atlantoaxial fusion, regardless of minor variations in C1LMS technique. Although biomechanical studies suggest markedly increased rigidity of bicortical and posterior arch C1LMS, the significance of these findings may be minimal in the clinical setting of atlantoaxial fixation and fusion with modern techniques. The decision to use either technique must be made after careful review of the preoperative multiplanar computed tomography imaging, assessment of the unique anatomy of each patient, and the demands of the clinical scenario such as bone quality.

Methods of detection using a cellulose binding domain fusion product

DOEpatents

Shoseyov, O.; Shpiegl, I.; Goldstein, M.A.; Doi, R.H.

1999-01-05

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques. 34 figs.

Kits and methods of detection using cellulose binding domain fusion proteins

DOEpatents

Shoseyov, O.; Yosef, K.

1998-04-14

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques. 16 figs.

Kits and methods of detection using cellulose binding domain fusion proteins

DOEpatents

Shoseyov, Oded

1998-01-01

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production thereof. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques.

Methods of detection using a cellulose binding domain fusion product

DOEpatents

Shoseyov, Oded; Shpiegl, Itai; Goldstein, Marc A.; Doi, Roy H.

1999-01-01

A cellulose binding domain (CBD) having a high affinity for crystalline cellulose and chitin is disclosed, along with methods for the molecular cloning and recombinant production thereof. Fusion products comprising the CBD and a second protein are likewise described. A wide range of applications are contemplated for both the CBD and the fusion products, including drug delivery, affinity separations, and diagnostic techniques.

Why You Should Believe Cold Fusion is Real

NASA Astrophysics Data System (ADS)

Storms, Edmund K.

2005-03-01

Nuclear reactions are now claimed to be initiated in certain solid materials at an energy too low to overcome the Coulomb barrier. These reactions include fusion, accelerated radioactive decay, and transmutation involving heavy elements. Evidence is based on hundreds of measurements of anomalous energy using a variety of calorimeters at levels far in excess of error, measurement of nuclear products using many normally accepted techniques, observations of many patterns of behavior common to all studies, measurement of anomalous energetic emissions using accepted techniques, and an understanding of most variables that have hindered reproducibility in the past. This evidence can be found at www.LENR-CANR.orgwww.LENR-CANR.org. Except for an accepted theory, the claims have met all requirements normally required before a new idea is accepted by conventional science, yet rejection continues. How long can the US afford to reject a clean and potentially cheap source of energy, especially when other nations are attempting to develop this energy and the need for such an energy source is so great?

Bayesian Knowledge Fusion in Prognostics and Health Management—A Case Study

NASA Astrophysics Data System (ADS)

Rabiei, Masoud; Modarres, Mohammad; Mohammad-Djafari, Ali

2011-03-01

In the past few years, a research effort has been in progress at University of Maryland to develop a Bayesian framework based on Physics of Failure (PoF) for risk assessment and fleet management of aging airframes. Despite significant achievements in modelling of crack growth behavior using fracture mechanics, it is still of great interest to find practical techniques for monitoring the crack growth instances using nondestructive inspection and to integrate such inspection results with the fracture mechanics models to improve the predictions. The ultimate goal of this effort is to develop an integrated probabilistic framework for utilizing all of the available information to come up with enhanced (less uncertain) predictions for structural health of the aircraft in future missions. Such information includes material level fatigue models and test data, health monitoring measurements and inspection field data. In this paper, a case study of using Bayesian fusion technique for integrating information from multiple sources in a structural health management problem is presented.

Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

DTIC Science & Technology

2012-09-01

Photogrammetry and Remote Sensing, 62, 43–63. Stein, D., Beaven, S., Hoff, L., Winter, E., Schaum, A., & Stocker, A. (2002). Anomaly detection from...TECHNIQUES USING THE FUSION OF LIDAR AND SPECTRAL DATA by Justin E. Mesina September 2012 Thesis Advisor: Richard C . Olsen Second...from shadow anomalies . The fused results however, were not as accurate in differentiating trees from grasses as using only spectral results. Overall the

Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors

PubMed Central

Zakaria, Ammar; Shakaff, Ali Yeon Md.; Adom, Abdul Hamid; Ahmad, Mohd Noor; Masnan, Maz Jamilah; Aziz, Abdul Hallis Abdul; Fikri, Nazifah Ahmad; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2010-01-01

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together. PMID:22163381

Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors.

PubMed

Zakaria, Ammar; Shakaff, Ali Yeon Md; Adom, Abdul Hamid; Ahmad, Mohd Noor; Masnan, Maz Jamilah; Aziz, Abdul Hallis Abdul; Fikri, Nazifah Ahmad; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2010-01-01

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.

Production and characterization of pure cryogenic inertial fusion targets

NASA Astrophysics Data System (ADS)

Boyd, B. A.; Kamerman, G. W.

An experimental cryogenic inertial fusion target generator and two optical techniques for automated target inspection are described. The generator produces 100 microns diameter solid hydrogen spheres at a rate compatible with fueling requirements of conceptual inertial fusion power plants. A jet of liquified hydrogen is disrupted into droplets by an ultrasonically excited nozzle. The droplets solidify into microspheres while falling through a chamber maintained below the hydrogen triple point pressure. Stable operation of the generator has been demonstrated for up to three hours. The optical inspection techniques are computer aided photomicrography and coarse diffraction pattern analysis (CDPA). The photomicrography system uses a conventional microscope coupled to a computer by a solid state camera and digital image memory. The computer enhances the stored image and performs feature extraction to determine pellet parameters. The CDPA technique uses Fourier transform optics and a special detector array to perform optical processing of a target image.

Structural materials by powder HIP for fusion reactors

NASA Astrophysics Data System (ADS)

Dellis, C.; Le Marois, G.; van Osch, E. V.

1998-10-01

Tokamak blankets have complex shapes and geometries with double curvature and embedded cooling channels. Usual manufacturing techniques such as forging, bending and welding generate very complex fabrication routes. Hot Isostatic Pressing (HIP) is a versatile and flexible fabrication technique that has a broad range of commercial applications. Powder HIP appears to be one of the most suitable techniques for the manufacturing of such complex shape components as fusion reactor modules. During the HIP cycle, consolidation of the powder is made and porosity in the material disappears. This involves a variation of 30% in volume of the component. These deformations are not isotropic due to temperature gradients in the part and the stiffness of the canister. This paper discusses the following points: (i) Availability of manufacturing process by powder HIP of 316LN stainless steel (ITER modules) and F82H martensitic steel (ITER Test Module and DEMO blanket) with properties equivalent to the forged one.(ii) Availability of powerful modelling techniques to simulate the densification of powder during the HIP cycle, and to control the deformation of components during consolidation by improving the canister design.(iii) Material data base needed for simulation of the HIP process, and the optimisation of canister geometry.(iv) Irradiation behaviour on powder HIP materials from preliminary results.

A comparison of line enhancement techniques: applications to guide-wire detection and respiratory motion tracking

NASA Astrophysics Data System (ADS)

Bismuth, Vincent; Vancamberg, Laurence; Gorges, Sébastien

2009-02-01

During interventional radiology procedures, guide-wires are usually inserted into the patients vascular tree for diagnosis or healing purpose. These procedures are monitored with an Xray interventional system providing images of the interventional devices navigating through the patient's body. The automatic detection of such tools by image processing means has gained maturity over the past years and enables applications ranging from image enhancement to multimodal image fusion. Sophisticated detection methods are emerging, which rely on a variety of device enhancement techniques. In this article we reviewed and classified these techniques into three families. We chose a state of the art approach in each of them and built a rigorous framework to compare their detection capability and their computational complexity. Through simulations and the intensive use of ROC curves we demonstrated that the Hessian based methods are the most robust to strong curvature of the devices and that the family of rotated filters technique is the most suited for detecting low CNR and low curvature devices. The steerable filter approach demonstrated less interesting detection capabilities and appears to be the most expensive one to compute. Finally we demonstrated the interest of automatic guide-wire detection on a clinical topic: the compensation of respiratory motion in multimodal image fusion.

Fusion primer and nested integrated PCR (FPNI-PCR): a new high-efficiency strategy for rapid chromosome walking or flanking sequence cloning

PubMed Central

2011-01-01

Background The advent of genomics-based technologies has revolutionized many fields of biological enquiry. However, chromosome walking or flanking sequence cloning is still a necessary and important procedure to determining gene structure. Such methods are used to identify T-DNA insertion sites and so are especially relevant for organisms where large T-DNA insertion libraries have been created, such as rice and Arabidopsis. The currently available methods for flanking sequence cloning, including the popular TAIL-PCR technique, are relatively laborious and slow. Results Here, we report a simple and effective fusion primer and nested integrated PCR method (FPNI-PCR) for the identification and cloning of unknown genomic regions flanked known sequences. In brief, a set of universal primers was designed that consisted of various 15-16 base arbitrary degenerate oligonucleotides. These arbitrary degenerate primers were fused to the 3' end of an adaptor oligonucleotide which provided a known sequence without degenerate nucleotides, thereby forming the fusion primers (FPs). These fusion primers are employed in the first step of an integrated nested PCR strategy which defines the overall FPNI-PCR protocol. In order to demonstrate the efficacy of this novel strategy, we have successfully used it to isolate multiple genomic sequences namely, 21 orthologs of genes in various species of Rosaceace, 4 MYB genes of Rosa rugosa, 3 promoters of transcription factors of Petunia hybrida, and 4 flanking sequences of T-DNA insertion sites in transgenic tobacco lines and 6 specific genes from sequenced genome of rice and Arabidopsis. Conclusions The successful amplification of target products through FPNI-PCR verified that this novel strategy is an effective, low cost and simple procedure. Furthermore, FPNI-PCR represents a more sensitive, rapid and accurate technique than the established TAIL-PCR and hiTAIL-PCR procedures. PMID:22093809

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

NASA Astrophysics Data System (ADS)

Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

2014-12-01

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

Multi-model data fusion to improve an early warning system for hypo-/hyperglycemic events.

PubMed

Botwey, Ransford Henry; Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G

2014-01-01

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Primary Renal Hybrid Low-grade Fibromyxoid Sarcoma-Sclerosing Epithelioid Fibrosarcoma: An Unusual Pediatric Case With EWSR1-CREB3L1 Fusion.

PubMed

Mok, Yingting; Pang, Yin Huei; Sanjeev, Jain Sudhanshi; Kuick, Chik Hong; Chang, Kenneth Tou-En

2018-01-01

Low-grade fibromyxoid sarcoma (LGFMS) and sclerosing epithelioid fibrosarcoma (SEF) are rare tumors with distinct sets of morphological features, both characterized by MUC4 immunoreactivity. Tumors exhibiting features of both entities are considered hybrid LGFMS-SEF lesions. While the majority of LGFMS cases are characterized by FUS-CREB3L2 gene fusions, most cases of pure SEF show EWSR1 gene rearrangements. In the largest study of hybrid LGFMS-SEF tumors to date, all cases exhibited FUS rearrangements, a similar genetic profile to LGFMS. We herein describe the clinicopathological features and genetic findings of a case of primary renal hybrid LGFMS-SEF occurring in a 10-year-old child, with disseminated metastases. Fusion gene detection using a next-generation sequencing-based anchored multiplex PCR technique (Archer FusionPlex Sarcoma Panel) was performed on both the primary renal tumor that showed the morphology of a LGFMS, and a cervical metastasis that showed the morphology of SEF. An EWSR1-CREB3L1 gene fusion occurring between exon 11 of EWSR1 and exon 6 of CREB3L1 was present in both the LGFMS and SEF components. This unusual case provides evidence that a subset of hybrid LGFMS-SEF harbor EWSR1-CREB3L1 gene fusions. In this case, these features were associated with an aggressive clinical course, with disease-associated mortality occurring within 12 months of diagnosis.

Nonintrusive multibiometrics on a mobile device: a comparison of fusion techniques

NASA Astrophysics Data System (ADS)

Allano, Lorene; Morris, Andrew C.; Sellahewa, Harin; Garcia-Salicetti, Sonia; Koreman, Jacques; Jassim, Sabah; Ly-Van, Bao; Wu, Dalei; Dorizzi, Bernadette

2006-04-01

In this article we test a number of score fusion methods for the purpose of multimodal biometric authentication. These tests were made for the SecurePhone project, whose aim is to develop a prototype mobile communication system enabling biometrically authenticated users to deal legally binding m-contracts during a mobile phone call on a PDA. The three biometrics of voice, face and signature were selected because they are all traditional non-intrusive and easy to use means of authentication which can readily be captured on a PDA. By combining multiple biometrics of relatively low security it may be possible to obtain a combined level of security which is at least as high as that provided by a PIN or handwritten signature, traditionally used for user authentication. As the relative success of different fusion methods depends on the database used and tests made, the database we used was recorded on a suitable PDA (the Qtek2020) and the test protocol was designed to reflect the intended application scenario, which is expected to use short text prompts. Not all of the fusion methods tested are original. They were selected for their suitability for implementation within the constraints imposed by the application. All of the methods tested are based on fusion of the match scores output by each modality. Though computationally simple, the methods tested have shown very promising results. All of the 4 fusion methods tested obtain a significant performance increase.

Interocular suppression

NASA Astrophysics Data System (ADS)

Tuna, Ana Rita; Almeida Neves Carrega, Filipa; Nunes, Amélia Fernandes

2017-08-01

The objective of this work is to quantify the suppressive imbalance, based on the manipulation of ocular luminance, between a group of subjects with normal binocular vision and a group of subjects with amblyopia. The result reveals that there are statistically significant differences in interocular dominance between two groups, evidencing a greater suppressive imbalance in amblyopic subjects. The technique used, proved to be a simple, easy to apply and economic method, for quantified ocular dominance. It is presented as a technique with the potential to accompany subjects with a marked dominance in one of the eyes that makes fusion difficult.

Comparison of 3 different postimplant dosimetry methods following permanent {sup 125}I prostate seed brachytherapy

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

Marcu, Loredana G., E-mail: loredana@marcunet.com; Faculty of Science, University of Oradea; School of Chemistry and Physics, University of Adelaide, South Australia

2013-10-01

Postimplant dosimetry (PID) after Iodine-125 ({sup 125}I) implant of the prostate should offer a reliable qualitative assessment. So far, there is no consensus regarding the optimum PID method, though the latest literature is in favor of magnetic resonance imaging (MRI). This study aims to simultaneously compare 3 PID techniques: (1) MRI-computed tomography (CT) fusion; (2) ultrasound (US)-CT fusion; and (3) manual target delineation on CT. The study comprised 10 patients with prostate cancer. CT/MR scans with urinary catheters in place for PID were done either on day 0 or day 1 postimplantation. The main parameter evaluated and compared among methodsmore » was target D90. The results show that CT-based D90s are lower than US-CT D90s (median difference,−6.85%), whereas MR-CT PID gives higher D90 than US-CT PID (median difference, 4.25%). Manual contouring on CT images tends to overestimate the prostate volume compared with transrectal ultrasound (TRUS) (median difference, 23.33%), whereas on US images the target is overestimated compared with MR-based contouring (median difference, 13.25%). Although there are certain differences among the results given by various PID techniques, the differences are statistically insignificant for this small group of patients. Any dosimetric comparison between 2 PID techniques should also account for the limitations of each technique, to allow for an accurate quantification of data. Given that PID after permanent radioactive seed implant is mandatory for quality assurance, any imaging method–based PID (MR-CT, US-CT, and CT) available in a radiotherapy department can be indicative of the quality of the procedure.« less

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

PubMed

Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

2016-12-01

Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

Spatial Statistical Data Fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Nguyen, Hai

2010-01-01

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).

The cost-effectiveness of interbody fusions versus posterolateral fusions in 137 patients with lumbar spondylolisthesis.

PubMed

Bydon, Mohamad; Macki, Mohamed; Abt, Nicholas B; Witham, Timothy F; Wolinsky, Jean-Paul; Gokaslan, Ziya L; Bydon, Ali; Sciubba, Daniel M

2015-03-01

Reimbursements for interbody fusions have declined recently because of their questionable cost-effectiveness. A Markov model was adopted to compare the cost-effectiveness of posterior lumbar interbody fusion (PLIF) or transforaminal lumbar interbody fusion (/TLIF) versus noninterbody fusion and posterolateral fusion (PLF) in patients with lumbar spondylolisthesis. Decision model analysis based on retrospective data from a single institutional series. One hundred thirty-seven patients underwent first-time instrumented lumbar fusions for degenerative or isthmic spondylolisthesis. Quality of life adjustments and expenditures were assigned to each short-term complication (durotomy, surgical site infection, and medical complication) and long-term outcome (bowel/bladder dysfunction and paraplegia, neurologic deficit, and chronic back pain). Patients were divided into a PLF cohort and a PLF plus PLIF/TLIF cohort. Anterior techniques and multilevel interbody fusions were excluded. Each short-term complication and long-term outcome was assigned a numerical quality-adjusted life-year (QALY), based on time trade-off values in the Beaver Dam Health Outcomes Study. The cost data for short-term complications were calculated from charges accrued by the institution's finance sector, and the cost data for long-term outcomes were estimated from the literature. The difference in cost of PLF plus PLIF/TLIF from the cost of PLF alone divided by the difference in QALY equals the cost-effectiveness ratio (CER). We do not report any study funding sources or any study-specific appraisal of potential conflict of interest-associated biases in this article. Of 137 first-time lumbar fusions for spondylolisthesis, 83 patients underwent PLF and 54 underwent PLIF/TLIF. The average time to reoperation was 3.5 years. The mean QALY over 3.5 years was 2.81 in the PLF cohort versus 2.66 in the PLIFo/TLIF cohort (p=.110). The mean 3.5-year costs of $54,827.05 after index interbody fusion were statistically higher than that of the $48,822.76 after PLF (p=.042). The CER of interbody fusion to PLF after the first operation was -$46,699.40 per QALY; however, of the 27 patients requiring reoperation, the incident (reoperation) rate ratio was 7.89 times higher after PLF (2.91, 26.67). The CER after the first reoperation was -$24,429.04 per QALY (relative to PLF). Two patients in the PLF cohort required a second reoperation, whereas none required a second reoperation in the PLIF/TLIF cohort. Taken collectively, the total CER for the interbody fusion is $9,883.97 per QALY. The reoperation rate was statistically higher for PLF, whereas the negative CER for the initial operation and first reoperation favors PLF. However, when second reoperations were included, the CER for the interbody fusion became $9,883.97 per QALY, suggesting moderate long-term cost savings and better functional outcomes with the interbody fusion. Copyright © 2015 Elsevier Inc. All rights reserved.

MR and CT image fusion for postimplant analysis in permanent prostate seed implants.

PubMed

Polo, Alfredo; Cattani, Federica; Vavassori, Andrea; Origgi, Daniela; Villa, Gaetano; Marsiglia, Hugo; Bellomi, Massimo; Tosi, Giampiero; De Cobelli, Ottavio; Orecchia, Roberto

2004-12-01

To compare the outcome of two different image-based postimplant dosimetry methods in permanent seed implantation. Between October 1999 and October 2002, 150 patients with low-risk prostate carcinoma were treated with (125)I and (103)Pd in our institution. A CT-MRI image fusion protocol was used in 21 consecutive patients treated with exclusive brachytherapy. The accuracy and reproducibility of the method was calculated, and then the CT-based dosimetry was compared with the CT-MRI-based dosimetry using the dose-volume histogram (DVH) related parameters recommended by the American Brachytherapy Society and the American Association of Physicists in Medicine. Our method for CT-MRI image fusion was accurate and reproducible (median shift <1 mm). Differences in prostate volume were found, depending on the image modality used. Quality assurance DVH-related parameters strongly depended on the image modality (CT vs. CT-MRI): V(100) = 82% vs. 88%, p < 0.05. D(90) = 96% vs. 115%, p < 0.05. Those results depend on the institutional implant technique and reflect the importance of lowering inter- and intraobserver discrepancies when outlining prostate and organs at risk for postimplant dosimetry. Computed tomography-MRI fused images allow accurate determination of prostate size, significantly improving the dosimetric evaluation based on DVH analysis. This provides a consistent method to judge a prostate seed implant's quality.

Rapid Method for Sodium Hydroxide/Sodium Peroxide Fusion ...

EPA Pesticide Factsheets

Technical Fact Sheet Analysis Purpose: Qualitative analysis Technique: Alpha spectrometry Method Developed for: Plutonium-238 and plutonium-239 in water and air filters Method Selected for: SAM lists this method as a pre-treatment technique supporting analysis of refractory radioisotopic forms of plutonium in drinking water and air filters using the following qualitative techniques: • Rapid methods for acid or fusion digestion • Rapid Radiochemical Method for Plutonium-238 and Plutonium 239/240 in Building Materials for Environmental Remediation Following Radiological Incidents. Summary of subject analytical method which will be posted to the SAM website to allow access to the method.

Product development using process monitoring and NDE data fusion

NASA Astrophysics Data System (ADS)

Peterson, Todd; Bossi, Richard H.

1998-03-01

Composite process/product development relies on both process monitoring information and nondestructive evaluation measurements for determining application suitability. In the past these activities have been performed and analyzed independently. Our present approach is to present the process monitoring and NDE data together in a data fusion workstation. This methodology leads to final product acceptance based on a combined process monitoring and NDE criteria. The data fusion work station combines process parameter and NDE data in a single workspace enabling all the data to be used in the acceptance/rejection decision process. An example application is the induction welding process, a unique joining method for assembling primary composite structure, that offers significant cost and weight advantages over traditional fasted structure. The determination of the required time, temperature and pressure conditions used in the process to achieve a complete weld is being aided by the use of ultrasonic inspection techniques. Full waveform ultrasonic inspection data is employed to evaluate the quality of spar cap to skin fit, an essential element of the welding process, and is processed to find a parameter that can be used for weld acceptance. Certification of the completed weld incorporates the data fusion methodology.

Combining multiple ChIP-seq peak detection systems using combinatorial fusion.

PubMed

Schweikert, Christina; Brown, Stuart; Tang, Zuojian; Smith, Phillip R; Hsu, D Frank

2012-01-01

Due to the recent rapid development in ChIP-seq technologies, which uses high-throughput next-generation DNA sequencing to identify the targets of Chromatin Immunoprecipitation, there is an increasing amount of sequencing data being generated that provides us with greater opportunity to analyze genome-wide protein-DNA interactions. In particular, we are interested in evaluating and enhancing computational and statistical techniques for locating protein binding sites. Many peak detection systems have been developed; in this study, we utilize the following six: CisGenome, MACS, PeakSeq, QuEST, SISSRs, and TRLocator. We define two methods to merge and rescore the regions of two peak detection systems and analyze the performance based on average precision and coverage of transcription start sites. The results indicate that ChIP-seq peak detection can be improved by fusion using score or rank combination. Our method of combination and fusion analysis would provide a means for generic assessment of available technologies and systems and assist researchers in choosing an appropriate system (or fusion method) for analyzing ChIP-seq data. This analysis offers an alternate approach for increasing true positive rates, while decreasing false positive rates and hence improving the ChIP-seq peak identification process.

Sensor fusion approaches for EMI and GPR-based subsurface threat identification

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Despite advances in both electromagnetic induction (EMI) and ground penetrating radar (GPR) sensing and related signal processing, neither sensor alone provides a perfect tool for detecting the myriad of possible buried objects that threaten the lives of Soldiers and civilians. However, while neither GPR nor EMI sensing alone can provide optimal detection across all target types, the two approaches are highly complementary. As a result, many landmine systems seek to make use of both sensing modalities simultaneously and fuse the results from both sensors to improve detection performance for targets with widely varying metal content and GPR responses. Despite this, little work has focused on large-scale comparisons of different approaches to sensor fusion and machine learning for combining data from these highly orthogonal phenomenologies. In this work we explore a wide array of pattern recognition techniques for algorithm development and sensor fusion. Results with the ARA Nemesis landmine detection system suggest that nonlinear and non-parametric classification algorithms provide significant performance benefits for single-sensor algorithm development, and that fusion of multiple algorithms can be performed satisfactorily using basic parametric approaches, such as logistic discriminant classification, for the targets under consideration in our data sets.

Nonlinear Burn Control and Operating Point Optimization in ITER

NASA Astrophysics Data System (ADS)

Boyer, Mark; Schuster, Eugenio

2013-10-01

Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).

A Faster, High Resolution, mtPA-GFP-based Mitochondrial Fusion Assay Acquiring Kinetic Data of Multiple Cells in Parallel Using Confocal Microscopy

PubMed Central

Lovy, Alenka; Molina, Anthony J.A.; Cerqueira, Fernanda M.; Trudeau, Kyle; Shirihai, Orian S.

2012-01-01

Mitochondrial fusion plays an essential role in mitochondrial calcium homeostasis, bioenergetics, autophagy and quality control. Fusion is quantified in living cells by photo-conversion of matrix targeted photoactivatable GFP (mtPAGFP) in a subset of mitochondria. The rate at which the photoconverted molecules equilibrate across the entire mitochondrial population is used as a measure of fusion activity. Thus far measurements were performed using a single cell time lapse approach, quantifying the equilibration in one cell over an hour. Here, we scale up and automate a previously published live cell method based on using mtPAGFP and a low concentration of TMRE (15 nm). This method involves photoactivating a small portion of the mitochondrial network, collecting highly resolved stacks of confocal sections every 15 min for 1 hour, and quantifying the change in signal intensity. Depending on several factors such as ease of finding PAGFP expressing cells, and the signal of the photoactivated regions, it is possible to collect around 10 cells within the 15 min intervals. This provides a significant improvement in the time efficiency of this assay while maintaining the highly resolved subcellular quantification as well as the kinetic parameters necessary to capture the detail of mitochondrial behavior in its native cytoarchitectural environment. Mitochondrial dynamics play a role in many cellular processes including respiration, calcium regulation, and apoptosis1,2,3,13. The structure of the mitochondrial network affects the function of mitochondria, and the way they interact with the rest of the cell. Undergoing constant division and fusion, mitochondrial networks attain various shapes ranging from highly fused networks, to being more fragmented. Interestingly, Alzheimer's disease, Parkinson's disease, Charcot Marie Tooth 2A, and dominant optic atrophy have been correlated with altered mitochondrial morphology, namely fragmented networks4,10,13. Often times, upon fragmentation, mitochondria become depolarized, and upon accumulation this leads to impaired cell function18. Mitochondrial fission has been shown to signal a cell to progress toward apoptosis. It can also provide a mechanism by which to separate depolarized and inactive mitochondria to keep the bulk of the network robust14. Fusion of mitochondria, on the other hand, leads to sharing of matrix proteins, solutes, mtDNA and the electrochemical gradient, and also seems to prevent progression to apoptosis9. How fission and fusion of mitochondria affects cell homeostasis and ultimately the functioning of the organism needs further understanding, and therefore the continuous development and optimization of how to gather information on these phenomena is necessary. Existing mitochondrial fusion assays have revealed various insights into mitochondrial physiology, each having its own advantages. The hybrid PEG fusion assay7, mixes two populations of differently labeled cells (mtRFP and mtYFP), and analyzes the amount of mixing and colocalization of fluorophores in fused, multinucleated, cells. Although this method has yielded valuable information, not all cell types can fuse, and the conditions under which fusion is stimulated involves the use of toxic drugs that likely affect the normal fusion process. More recently, a cell free technique has been devised, using isolated mitochondria to observe fusion events based on a luciferase assay1,5. Two human cell lines are targeted with either the amino or a carboxy terminal part of Renilla luciferase along with a leucine zipper to ensure dimerization upon mixing. Mitochondria are isolated from each cell line, and fused. The fusion reaction can occur without the cytosol under physiological conditions in the presence of energy, appropriate temperature and inner mitochondrial membrane potential. Interestingly, the cytosol was found to modulate the extent of fusion, demonstrating that cell signaling regulates the fusion process 4,5. This assay will be very useful for high throughput screening to identify components of the fusion machinery and also pharmacological compounds that may affect mitochondrial dynamics. However, more detailed whole cell mitochondrial assays will be needed to complement this in vitro assay to observe these events within a cellular environment. A technique for monitoring whole-cell mitochondrial dynamics has been in use for some time and is based on a mitochondrially-targeted photoactivatable GFP (mtPAGFP)6,11. Upon expression of the mtPAGFP, a small portion of the mitochondrial network is photoactivated (10-20%), and the spread of the signal to the rest of the mitochondrial network is recorded every 15 minutes for 1 hour using time lapse confocal imaging. Each fusion event leads to a dilution of signal intensity, enabling quantification of the fusion rate. Although fusion and fission are continuously occurring in cells, this technique only monitors fusion as fission does not lead to a dilution of the PAGFP signal6. Co-labeling with low levels of TMRE (7-15 nM in INS1 cells) allows quantification of the membrane potential of mitochondria. When mitochondria are hyperpolarized they uptake more TMRE, and when they depolarize they lose the TMRE dye. Mitochondria that depolarize no longer have a sufficient membrane potential and tend not to fuse as efficiently if at all. Therefore, active fusing mitochondria can be tracked with these low levels of TMRE9,15. Accumulation of depolarized mitochondria that lack a TMRE signal may be a sign of phototoxicity or cell death. Higher concentrations of TMRE render mitochondria very sensitive to laser light, and therefore great care must be taken to avoid overlabeling with TMRE. If the effect of depolarization of mitochondria is the topic of interest, a technique using slightly higher levels of TMRE and more intense laser light can be used to depolarize mitochondria in a controlled fashion (Mitra and Lippincott-Schwartz, 2010). To ensure that toxicity due to TMRE is not an issue, we suggest exposing loaded cells (3-15 nM TMRE) to the imaging parameters that will be used in the assay (perhaps 7 stacks of 6 optical sections in a row), and assessing cell health after 2 hours. If the mitochondria appear too fragmented and cells are dying, other mitochondrial markers, such as dsRED or Mitotracker red could be used instead of TMRE. The mtPAGFP method has revealed details about mitochondrial network behavior that could not be visualized using other methods. For example, we now know that mitochondrial fusion can be full or transient, where matrix content can mix without changing the overall network morphology. Additionally, we know that the probability of fusion is independent of contact duration and organelle dimension, is influenced by organelle motility, membrane potential and history of previous fusion activity8,15,16,17. In this manuscript, we describe a methodology for scaling up the previously published protocol using mtPAGFP and 15nM TMRE8 in order to examine multiple cells at a time and improve the time efficiency of data collection without sacrificing the subcellular resolution. This has been made possible by the use of an automated microscope stage, and programmable image acquisition software. Zen software from Zeiss allows the user to mark and track several designated cells expressing mtPAGFP. Each of these cells can be photoactivated in a particular region of interest, and stacks of confocal slices can be monitored for mtPAGFP signal as well as TMRE at specified intervals. Other confocal systems could be used to perform this protocol provided there is an automated stage that is programmable, an incubator with CO2, and a means by which to photoactivate the PAGFP; either a multiphoton laser, or a 405 nm diode laser. PMID:22847388

A faster, high resolution, mtPA-GFP-based mitochondrial fusion assay acquiring kinetic data of multiple cells in parallel using confocal microscopy.

PubMed

Lovy, Alenka; Molina, Anthony J A; Cerqueira, Fernanda M; Trudeau, Kyle; Shirihai, Orian S

2012-07-20

Mitochondrial fusion plays an essential role in mitochondrial calcium homeostasis, bioenergetics, autophagy and quality control. Fusion is quantified in living cells by photo-conversion of matrix targeted photoactivatable GFP (mtPAGFP) in a subset of mitochondria. The rate at which the photoconverted molecules equilibrate across the entire mitochondrial population is used as a measure of fusion activity. Thus far measurements were performed using a single cell time lapse approach, quantifying the equilibration in one cell over an hour. Here, we scale up and automate a previously published live cell method based on using mtPAGFP and a low concentration of TMRE (15 nm). This method involves photoactivating a small portion of the mitochondrial network, collecting highly resolved stacks of confocal sections every 15 min for 1 hour, and quantifying the change in signal intensity. Depending on several factors such as ease of finding PAGFP expressing cells, and the signal of the photoactivated regions, it is possible to collect around 10 cells within the 15 min intervals. This provides a significant improvement in the time efficiency of this assay while maintaining the highly resolved subcellular quantification as well as the kinetic parameters necessary to capture the detail of mitochondrial behavior in its native cytoarchitectural environment. Mitochondrial dynamics play a role in many cellular processes including respiration, calcium regulation, and apoptosis. The structure of the mitochondrial network affects the function of mitochondria, and the way they interact with the rest of the cell. Undergoing constant division and fusion, mitochondrial networks attain various shapes ranging from highly fused networks, to being more fragmented. Interestingly, Alzheimer's disease, Parkinson's disease, Charcot Marie Tooth 2A, and dominant optic atrophy have been correlated with altered mitochondrial morphology, namely fragmented networks. Often times, upon fragmentation, mitochondria become depolarized, and upon accumulation this leads to impaired cell function. Mitochondrial fission has been shown to signal a cell to progress toward apoptosis. It can also provide a mechanism by which to separate depolarized and inactive mitochondria to keep the bulk of the network robust. Fusion of mitochondria, on the other hand, leads to sharing of matrix proteins, solutes, mtDNA and the electrochemical gradient, and also seems to prevent progression to apoptosis. How fission and fusion of mitochondria affects cell homeostasis and ultimately the functioning of the organism needs further understanding, and therefore the continuous development and optimization of how to gather information on these phenomena is necessary. Existing mitochondrial fusion assays have revealed various insights into mitochondrial physiology, each having its own advantages. The hybrid PEG fusion assay, mixes two populations of differently labeled cells (mtRFP and mtYFP), and analyzes the amount of mixing and colocalization of fluorophores in fused, multinucleated, cells. Although this method has yielded valuable information, not all cell types can fuse, and the conditions under which fusion is stimulated involves the use of toxic drugs that likely affect the normal fusion process. More recently, a cell free technique has been devised, using isolated mitochondria to observe fusion events based on a luciferase assay. Two human cell lines are targeted with either the amino or a carboxy terminal part of Renilla luciferase along with a leucine zipper to ensure dimerization upon mixing. Mitochondria are isolated from each cell line, and fused. The fusion reaction can occur without the cytosol under physiological conditions in the presence of energy, appropriate temperature and inner mitochondrial membrane potential. Interestingly, the cytosol was found to modulate the extent of fusion, demonstrating that cell signaling regulates the fusion process. This assay will be very useful for high throughput screening to identify components of the fusion machinery and also pharmacological compounds that may affect mitochondrial dynamics. However, more detailed whole cell mitochondrial assays will be needed to complement this in vitro assay to observe these events within a cellular environment. A technique for monitoring whole-cell mitochondrial dynamics has been in use for some time and is based on a mitochondrially-targeted photoactivatable GFP (mtPAGFP). Upon expression of the mtPAGFP, a small portion of the mitochondrial network is photoactivated (10-20%), and the spread of the signal to the rest of the mitochondrial network is recorded every 15 minutes for 1 hour using time lapse confocal imaging. Each fusion event leads to a dilution of signal intensity, enabling quantification of the fusion rate. Although fusion and fission are continuously occurring in cells, this technique only monitors fusion as fission does not lead to a dilution of the PAGFP signal. Co-labeling with low levels of TMRE (7-15 nM in INS1 cells) allows quantification of the membrane potential of mitochondria. When mitochondria are hyperpolarized they uptake more TMRE, and when they depolarize they lose the TMRE dye. Mitochondria that depolarize no longer have a sufficient membrane potential and tend not to fuse as efficiently if at all. Therefore, active fusing mitochondria can be tracked with these low levels of TMRE. Accumulation of depolarized mitochondria that lack a TMRE signal may be a sign of phototoxicity or cell death. Higher concentrations of TMRE render mitochondria very sensitive to laser light, and therefore great care must be taken to avoid overlabeling with TMRE. If the effect of depolarization of mitochondria is the topic of interest, a technique using slightly higher levels of TMRE and more intense laser light can be used to depolarize mitochondria in a controlled fashion (Mitra and Lippincott-Schwartz, 2010). To ensure that toxicity due to TMRE is not an issue, we suggest exposing loaded cells (3-15 nM TMRE) to the imaging parameters that will be used in the assay (perhaps 7 stacks of 6 optical sections in a row), and assessing cell health after 2 hours. If the mitochondria appear too fragmented and cells are dying, other mitochondrial markers, such as dsRED or Mitotracker red could be used instead of TMRE. The mtPAGFP method has revealed details about mitochondrial network behavior that could not be visualized using other methods. For example, we now know that mitochondrial fusion can be full or transient, where matrix content can mix without changing the overall network morphology. Additionally, we know that the probability of fusion is independent of contact duration and organelle dimension, is influenced by organelle motility, membrane potential and history of previous fusion activity. In this manuscript, we describe a methodology for scaling up the previously published protocol using mtPAGFP and 15 nM TMRE in order to examine multiple cells at a time and improve the time efficiency of data collection without sacrificing the subcellular resolution. This has been made possible by the use of an automated microscope stage, and programmable image acquisition software. Zen software from Zeiss allows the user to mark and track several designated cells expressing mtPAGFP. Each of these cells can be photoactivated in a particular region of interest, and stacks of confocal slices can be monitored for mtPAGFP signal as well as TMRE at specified intervals. Other confocal systems could be used to perform this protocol provided there is an automated stage that is programmable, an incubator with CO2, and a means by which to photoactivate the PAGFP; either a multiphoton laser, or a 405 nm diode laser.

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

Wang, Y.; Tobias, B.; Chang, Y. -T.

Electron cyclotron emission (ECE) imaging is a passive radiometric technique that measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) is an active radar imaging technique that measures electron density fluctuations. The microwave imaging diagnostic instruments employing these techniques have made important contributions to fusion science and have been adopted at major fusion facilities worldwide including DIII-D, EAST, ASDEX Upgrade, HL-2A, KSTAR, LHD, and J-TEXT. In this paper, we describe the development status of three major technological advancements: custom mm-wave integrated circuits (ICs), digital beamforming (DBF), and synthetic diagnostic modeling (SDM). These also have the potential to greatly advance microwavemore » fusion plasma imaging, enabling compact and low-noise transceiver systems with real-time, fast tracking ability to address critical fusion physics issues, including ELM suppression and disruptions in the ITER baseline scenario, naturally ELM-free states such as QH-mode, and energetic particle confinement (i.e. Alfven eigenmode stability) in high-performance regimes that include steady-state and advanced tokamak scenarios. Furthermore, these systems are fully compatible with today's most challenging non-inductive heating and current drive systems and capable of operating in harsh environments, making them the ideal approach for diagnosing long-pulse and steady-state tokamaks.« less

Comparison of intramedullary nailing and external fixation knee arthrodesis for the infected knee replacement.

PubMed

Mabry, Tad M; Jacofsky, David J; Haidukewych, George J; Hanssen, Arlen D

2007-11-01

We analyzed knee arthrodesis for the infected total knee replacement (TKR) using two different fixation techniques. Patients undergoing knee arthrodesis for infected TKR were identified and rates of successful fusion and recurrence of infection were compared using Cox proportional hazard models. Eighty-five consecutive patients who underwent knee arthrodesis were followed until union, nonunion, amputation, or death. External fixation achieved successful fusion in 41 of 61 patients and was associated with a 4.9% rate of deep infection. Fusion was successful in 23 of 24 patients with intramedullary (IM) nailing and was associated with an 8.3% rate of deep infection. We observed similar fusion and infection rates with the two techniques. Thirty-four patients (40%) had complications. Knee arthrodesis remains a reasonable salvage alternative for the difficult infected TKR. Complication rates are high irrespective of the technique, and one must consider the risks of both nonunion and infection when choosing the fixation method in this setting. IM nailing appears to have a higher rate of successful union but a higher risk of recurrent infection when compared with external fixation knee arthrodesis. Level III, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.

Fusion of monocular cues to detect man-made structures in aerial imagery

NASA Technical Reports Server (NTRS)

Shufelt, Jefferey; Mckeown, David M.

1991-01-01

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

Cryogenic Cathode Cooling Techniques for Improved SABRE Extraction Ion Diode Li Beam Generation

NASA Astrophysics Data System (ADS)

Hanson, D. L.; Johnston, R. R.; Cuneo, M. E.; Menge, P. R.; Fowler, W. E.; Armijo, J.; Nielsen, D. S.; Petmecky, D.

1997-11-01

We are developing techniques for cryogenic cooling of the SABRE extraction ion diode cathode that, combined with source cleaning, should improve the purity and brightness of Li beams for ICF light ion fusion. By liquid helium (LHe) cathode cooling, we have been able to maintain A-K gap base pressures in the range of 5 - 7x10-8 Torr for about 45 minutes. These base pressures extend the monolayer formation time for the worst beam contaminants (H2 and water vapor) to 10 - 100 sec or longer, which should allow the accelerator to be fired without significant Li source recontamination. This technique is compatible with He glow discharge cleaning, laser cleaning, and in situ Li deposition. We are also developing techniques for Ti-gettering of H2 and for cryogenic cooling of cathode electrodes to delay cathode plasma expansion.

Modulating the Neutron Flux from a Mirror Neutron Source

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

Ryutov, D D

2011-09-01

A 14-MeV neutron source based on a Gas-Dynamic Trap will provide a high flux of 14 MeV neutrons for fusion materials and sub-component testing. In addition to its main goal, the source has potential applications in condensed matter physics and biophysics. In this report, the author considers adding one more capability to the GDT-based neutron source, the modulation of the neutron flux with a desired frequency. The modulation may be an enabling tool for the assessment of the role of non-steady-state effects in fusion devices as well as for high-precision, low-signal basic science experiments favoring the use of the synchronousmore » detection technique. A conclusion is drawn that modulation frequency of up to 1 kHz and modulation amplitude of a few percent is achievable. Limitations on the amplitude of modulations at higher frequencies are discussed.« less

volBrain: An Online MRI Brain Volumetry System

PubMed Central

Manjón, José V.; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results. PMID:27512372

volBrain: An Online MRI Brain Volumetry System.

PubMed

Manjón, José V; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results.

A Review of Depth and Normal Fusion Algorithms

PubMed Central

Štolc, Svorad; Pock, Thomas

2018-01-01

Geometric surface information such as depth maps and surface normals can be acquired by various methods such as stereo light fields, shape from shading and photometric stereo techniques. We compare several algorithms which deal with the combination of depth with surface normal information in order to reconstruct a refined depth map. The reasons for performance differences are examined from the perspective of alternative formulations of surface normals for depth reconstruction. We review and analyze methods in a systematic way. Based on our findings, we introduce a new generalized fusion method, which is formulated as a least squares problem and outperforms previous methods in the depth error domain by introducing a novel normal weighting that performs closer to the geodesic distance measure. Furthermore, a novel method is introduced based on Total Generalized Variation (TGV) which further outperforms previous approaches in terms of the geodesic normal distance error and maintains comparable quality in the depth error domain. PMID:29389903

Porous biodegradable lumbar interbody fusion cage design and fabrication using integrated global-local topology optimization with laser sintering.

PubMed

Kang, Heesuk; Hollister, Scott J; La Marca, Frank; Park, Paul; Lin, Chia-Ying

2013-10-01

Biodegradable cages have received increasing attention for their use in spinal procedures involving interbody fusion to resolve complications associated with the use of nondegradable cages, such as stress shielding and long-term foreign body reaction. However, the relatively weak initial material strength compared to permanent materials and subsequent reduction due to degradation may be problematic. To design a porous biodegradable interbody fusion cage for a preclinical large animal study that can withstand physiological loads while possessing sufficient interconnected porosity for bony bridging and fusion, we developed a multiscale topology optimization technique. Topology optimization at the macroscopic scale provides optimal structural layout that ensures mechanical strength, while optimally designed microstructures, which replace the macroscopic material layout, ensure maximum permeability. Optimally designed cages were fabricated using solid, freeform fabrication of poly(ε-caprolactone) mixed with hydroxyapatite. Compression tests revealed that the yield strength of optimized fusion cages was two times that of typical human lumbar spine loads. Computational analysis further confirmed the mechanical integrity within the human lumbar spine, although the pore structure locally underwent higher stress than yield stress. This optimization technique may be utilized to balance the complex requirements of load-bearing, stress shielding, and interconnected porosity when using biodegradable materials for fusion cages.

Assessment of NDE Methods to Detect Lack of Fusion in HDPE Butt Fusion Joints

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

Crawford, Susan L.; Doctor, Steven R.; Cinson, Anthony D.

2011-07-31

Studies at the Pacific Northwest National Laboratory (PNNL) in Richland, Washington, were conducted to evaluate nondestructive examinations (NDE) coupled with mechanical testing of butt fusion joints in high-density polyethylene (HDPE) pipe for assessing lack of fusion. The work provided information to the United States Nuclear Regulatory Commission (NRC) on the effectiveness of volumetric inspection techniques of HDPE butt fusion joints in Section III, Division 1, Class 3, buried piping systems in nuclear power plants. This paper describes results from assessments using ultrasonic and microwave nondestructive techniques and mechanical testing with the high-speed tensile impact test and the side-bend test formore » determining joint integrity. A series of butt joints were fabricated in 3408, 12-inch (30.5-cm) IPS DR-11 HDPE material by varying the fusion parameters to create good joints and joints containing a range of lack-of-fusion conditions. Six of these butt joints were volumetrically examined with time-of-flight diffraction (TOFD), phased-array (PA) ultrasound, and the Evisive microwave system. The outer diameter (OD) weld beads were removed for microwave evaluation and the pipes ultrasonically re-evaluated. In two of the six pipes, both the outer and inner diameter (ID) weld beads were removed and the pipe joints re-evaluated. Some of the pipes were sectioned and the joints destructively evaluated with the high-speed tensile test and the side-bend test. The fusion parameters, nondestructive and destructive evaluation results have been correlated to validate the effectiveness of what each NDE technology detects and what each does not detect. There was no single NDE method that detected all of the lack-of-fusion flaws but a combination of NDE methods did detect most of the flaws.« less

The Fusion Gain Analysis of the Inductively Driven Liner Compression Based Fusion

NASA Astrophysics Data System (ADS)

Shimazu, Akihisa; Slough, John

2016-10-01

An analytical analysis of the fusion gain expected in the inductively driven liner compression (IDLC) based fusion is conducted to identify the fusion gain scaling at various operating conditions. The fusion based on the IDLC is a magneto-inertial fusion concept, where a Field-Reversed Configuration (FRC) plasmoid is compressed via the inductively-driven metal liner to drive the FRC to fusion conditions. In the past, an approximate scaling law for the expected fusion gain for the IDLC based fusion was obtained under the key assumptions of (1) D-T fuel at 5-40 keV, (2) adiabatic scaling laws for the FRC dynamics, (3) FRC energy dominated by the pressure balance with the edge magnetic field at the peak compression, and (4) the liner dwell time being liner final diameter divided by the peak liner velocity. In this study, various assumptions made in the previous derivation is relaxed to study the change in the fusion gain scaling from the previous result of G ml1 / 2 El11 / 8 , where ml is the liner mass and El is the peak liner kinetic energy. The implication from the modified fusion gain scaling on the performance of the IDLC fusion reactor system is also explored.

News video story segmentation method using fusion of audio-visual features

NASA Astrophysics Data System (ADS)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

Improving CAR Navigation with a Vision-Based System

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, K.; Lee, I.

2015-08-01

The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.

Improving Car Navigation with a Vision-Based System

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, K.; Lee, I.

2015-08-01

The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.

Practical Considerations for Optic Nerve Estimation in Telemedicine

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

Karnowski, Thomas Paul; Aykac, Deniz; Chaum, Edward

The projected increase in diabetes in the United States and worldwide has created a need for broad-based, inexpensive screening for diabetic retinopathy (DR), an eye disease which can lead to vision impairment. A telemedicine network with retina cameras and automated quality control, physiological feature location, and lesion / anomaly detection is a low-cost way of achieving broad-based screening. In this work we report on the effect of quality estimation on an optic nerve (ON) detection method with a confidence metric. We report on an improvement of the fusion technique using a data set from an ophthalmologists practice then show themore » results of the method as a function of image quality on a set of images from an on-line telemedicine network collected in Spring 2009 and another broad-based screening program. We show that the fusion method, combined with quality estimation processing, can improve detection performance and also provide a method for utilizing a physician-in-the-loop for images that may exceed the capabilities of automated processing.« less

Robust human machine interface based on head movements applied to assistive robotics.

PubMed

Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano

2013-01-01

This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair.

Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics

PubMed Central

Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano

2013-01-01

This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair. PMID:24453877

Desensitized Optimal Filtering and Sensor Fusion Toolkit

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.

2015-01-01

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

Sampling the kinetic pathways of a micelle fusion and fission transition.

PubMed

Pool, René; Bolhuis, Peter G

2007-06-28

The mechanism and kinetics of micellar breakup and fusion in a dilute solution of a model surfactant are investigated by path sampling techniques. Analysis of the path ensemble gives insight in the mechanism of the transition. For larger, less stable micelles the fission/fusion occurs via a clear neck formation, while for smaller micelles the mechanism is more direct. In addition, path analysis yields an appropriate order parameter to evaluate the fusion and fission rate constants using stochastic transition interface sampling. For the small, stable micelle (50 surfactants) the computed fission rate constant is a factor of 10 lower than the fusion rate constant. The procedure opens the way for accurate calculation of free energy and kinetics for, e.g., membrane fusion, and wormlike micelle endcap formation.

Trypsin pre-treatment corrects SRID over-estimation of immunologically active, pre-fusion HA caused by mixed immunoprecipitin rings.

PubMed

Wen, Yingxia; Palladino, Giuseppe; Xie, Yuhong; Ferrari, Annette; Ma, Xiuwen; Han, Liqun; Dormitzer, Philip R; Settembre, Ethan C

2016-06-17

Influenza vaccines are the primary intervention to prevent the substantial health burden of seasonal and pandemic influenza. Subunit and split influenza vaccines are formulated, released for clinical use, and tested for stability based on their content of immunologically active (capable of eliciting functional antibodies) hemagglutinin (HA). Single-radial immunodiffusion (SRID), the standard in vitro potency assay in the field, is believed to specifically detect immunologically active HA. We confirmed that, with conformationally homogeneous HA preparations, SRID specifically detected native, pre-fusion HA, which elicited influenza neutralizing and hemagglutination inhibiting (HI) antibodies in mice, and it did not detect low-pH stressed, post-fusion HA, which was selectively removed from the SRID gel during a blotting step and was significantly less immunologically active. This selective detection was due to the SRID format, not a conformational specificity of the sheep antiserum used in the SRID, as the same antiserum detected non-stressed and low-pH stressed HA similarly when used in an ELISA format. However, when low-pH stressed HA was mixed with non-stressed HA, SRID detected both forms in mixed immunoprecipitin rings, leading to over-quantification of pre-fusion HA. We previously reported that trypsin digestion of antigen samples selectively degrade stressed HA, so that an otherwise conformationally insensitive biophysical quantification technique, reversed-phase high pressure liquid chromatography (RP-HPLC), can specifically quantify trypsin-resistant, immunologically active, pre-fusion HA. Here, we report that trypsin digestion can also improve the specificity of SRID so that it can quantify immunologically active, pre-fusion HA when it is mixed with less immunologically active, post-fusion HA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fusion of Protegrin-1 and Plectasin to MAP30 Shows Significant Inhibition Activity against Dengue Virus Replication

PubMed Central

Rothan, Hussin A.; Bahrani, Hirbod; Mohamed, Zulqarnain; Abd Rahman, Noorsaadah; Yusof, Rohana

2014-01-01

Dengue virus (DENV) broadly disseminates in tropical and sub-tropical countries and there are no vaccine or anti-dengue drugs available. DENV outbreaks cause serious economic burden due to infection complications that requires special medical care and hospitalization. This study presents a new strategy for inexpensive production of anti-DENV peptide-fusion protein to prevent and/or treat DENV infection. Antiviral cationic peptides protegrin-1 (PG1) and plectasin (PLSN) were fused with MAP30 protein to produce recombinant antiviral peptide-fusion protein (PG1-MAP30-PLSN) as inclusion bodies in E. coli. High yield production of PG1-MAP30-PLSN protein was achieved by solubilization of inclusion bodies in alkaline buffer followed by the application of appropriate refolding techniques. Antiviral PG1-MAP30-PLSN protein considerably inhibited DENV protease (NS2B-NS3pro) with half-maximal inhibitory concentration (IC50) 0.5±0.1 μM. The real-time proliferation assay (RTCA) and the end-point proliferation assay (MTT assay) showed that the maximal-nontoxic dose of the peptide-fusion protein against Vero cells is approximately 0.67±0.2 μM. The cell-based assays showed considerable inhibition of the peptide-fusion protein against binding and proliferating stages of DENV2 into the target cells. The peptide-fusion protein protected DENV2-challeged mice with 100% of survival at the dose of 50 mg/kg. In conclusion, producing recombinant antiviral peptide-fusion protein by combining short antiviral peptide with a central protein owning similar activity could be useful to minimize the overall cost of short peptide production and take advantage of its synergistic antiviral activities. PMID:24722532

Development and Characterization of Somatic Hybrids of Ulva reticulata Forsskål (×) Monostroma oxyspermum (Kutz.)Doty

PubMed Central

Gupta, Vishal; Kumari, Puja; Reddy, CRK

2015-01-01

Ulvophycean species with diverse trait characteristics provide an opportunity to create novel allelic recombinant variants. The present study reports the development of seaweed variants with improved agronomic traits through protoplast fusion between Monostroma oxyspermum (Kutz.) Doty and Ulva reticulata Forsskål. A total of 12 putative hybrids were screened based on the variations in morphology and total DNA content over the fusion partners. DNA-fingerprinting by inter simple sequence repeat (ISSR) and amplified fragment length polymorphism (AFLP) analysis confirmed genomic introgression in the hybrids. The DNA fingerprint revealed sharing of parental alleles in regenerated hybrids and a few alleles that were unique to hybrids. The epigenetic variations in hybrids estimated in terms of DNA methylation polymorphism also revealed sharing of methylation loci with both the fusion partners. The functional trait analysis for growth showed a hybrid with heterotic trait (DGR% = 36.7 ± 1.55%) over the fusion partners U. reticulata (33.2 ± 2.6%) and M. oxyspermum (17.8 ± 1.77%), while others were superior to the mid-parental value (25.2 ± 2.2%) (p < 0.05). The fatty acid (FA) analysis of hybrids showed notable variations over fusion partners. Most hybrids showed increased polyunsaturated FAs (PUFAs) compared to saturated FAs (SFAs) and mainly includes the nutritionally important linoleic acid, α-linolenic acid, oleic acid, stearidonic acid, and docosahexaenoic acid. The other differences observed include superior cellulose content and antioxidative potential in hybrids over fusion partners. The hybrid varieties with superior traits developed in this study unequivocally demonstrate the significance of protoplast fusion technique in developing improved varients of macroalgae. PMID:25688248

Assembly of Customized TAL Effectors Through Advanced ULtiMATE System.

PubMed

Yang, Junjiao; Guo, Shengjie; Yuan, Pengfei; Wei, Wensheng

2016-01-01

Transcription activator-like effectors (TALEs) have been widely applied in gene targeting. Here we describe an advanced ULtiMATE (USER-based Ligation-Mediated Assembly of TAL Effector) system that utilizes USER fusion technique and archive of 512 tetramer templates to achieve highly efficient construction of TALEs, which takes only half a day to accomplish the assembly of any given TALE construct. This system is also suitable for large-scale assembly of TALENs and any other TALE-based constructions.

Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.

A Multi-Disciplinary University Research Initiative in Hard and Soft Information Fusion: Overview, Research Strategies and Initial Results

DTIC Science & Technology

2010-07-01

Multisource Information Fusion ( CMIF ) along with a team including the Pennsylvania State University (PSU), Iona College (Iona), and Tennessee State...License. 14. ABSTRACT The University at Buffalo (UB) Center for Multisource Information Fusion ( CMIF ) along with a team including the Pennsylvania...of CMIF current research on methods for Test and Evaluation ([7], [8]) involving for example large- factor-space experimental design techniques ([9

The evolution of spinal instrumentation for the management of occipital cervical and cervicothoracic junctional injuries.

PubMed

Smucker, Joseph D; Sasso, Rick C

2006-05-15

Independent computer-based literature review of articles pertaining to instrumentation and fusion of junctional injuries of the cervical spine. To review and discuss the evolution of instrumentation techniques and systems used in the treatment of cervical spine junctional injuries. Instrumentation of junctional injuries of the cervical spine has been limited historically by failure to achieve rigid internal fixation in multiple planes. The evolution of these techniques has required increased insight into the morphology and unique biomechanics of the structures to be instrumented. Computer-based literature search of Ovid and PubMed databases. Extensive literature search yielded insights into the evolution of systems initially based on onlay bone graft combined with wiring techniques. Such techniques have come to include systems incorporating rigid, longitudinal struts that accommodate multiplanar screws placed in the lateral masses, pedicles, transarticular regions, and occipital bone. Despite a rapid evolution of techniques and instrumentation technologies, it remains incumbent on the physician to provide the patient with a surgical procedure that balances the likelihood of a favorable outcome with the risk inherent in the implementation of the procedure.

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

Technique tip: use of anterior cruciate ligament jig for hindfoot fusion by calcanio-talo-tibial nail.

PubMed

Haque, Syed; Sarkar, Jay

2012-08-01

The use of intramedullary nail fixation for tibio-talo-calcaneal fusion is gaining popularity. There is chance of failure of procedure following faulty operative technique specially alignment. The article describes a useful application of tibial tunnel jig in inserting the calcanio-talo-tibial guide wire. There is precision of few millimeters in the exit point of guide wire on talus. The authors believe that this helps in better positioning of nail and hence better alignment and better operative outcome.

Joint interpretation of geophysical data using Image Fusion techniques

NASA Astrophysics Data System (ADS)

Karamitrou, A.; Tsokas, G.; Petrou, M.

2013-12-01

Joint interpretation of geophysical data produced from different methods is a challenging area of research in a wide range of applications. In this work we apply several image fusion approaches to combine maps of electrical resistivity, electromagnetic conductivity, vertical gradient of the magnetic field, magnetic susceptibility, and ground penetrating radar reflections, in order to detect archaeological relics. We utilize data gathered from Arkansas University, with the support of the U.S. Department of Defense, through the Strategic Environmental Research and Development Program (SERDP-CS1263). The area of investigation is the Army City, situated in Riley Country of Kansas, USA. The depth of the relics is estimated about 30 cm from the surface, yet the surface indications of its existence are limited. We initially register the images from the different methods to correct from random offsets due to the use of hand-held devices during the measurement procedure. Next, we apply four different image fusion approaches to create combined images, using fusion with mean values, wavelet decomposition, curvelet transform, and curvelet transform enhancing the images along specific angles. We create seven combinations of pairs between the available geophysical datasets. The combinations are such that for every pair at least one high-resolution method (resistivity or magnetic gradiometry) is included. Our results indicate that in almost every case the method of mean values produces satisfactory fused images that corporate the majority of the features of the initial images. However, the contrast of the final image is reduced, and in some cases the averaging process nearly eliminated features that are fade in the original images. Wavelet based fusion outputs also good results, providing additional control in selecting the feature wavelength. Curvelet based fusion is proved the most effective method in most of the cases. The ability of curvelet domain to unfold the image in terms of space, wavenumber, and orientation, provides important advantages compared with the rest of the methods by allowing the incorporation of a-priori information about the orientation of the potential targets.

Accuracy and feasibility of three different methods for software-based image fusion in whole-body PET and CT.

PubMed

Putzer, Daniel; Henninger, Benjamin; Kovacs, Peter; Uprimny, Christian; Kendler, Dorota; Jaschke, Werner; Bale, Reto J

2016-06-01

Even as PET/CT provides valuable diagnostic information in a great number of clinical indications, availability of hybrid PET/CT scanners is mainly limited to clinical centers. A software-based image fusion would facilitate combined image reading of CT and PET data sets if hardware image fusion is not available. To analyze the relevance of retrospective image fusion of separately acquired PET and CT data sets, we studied the accuracy, practicability and reproducibility of three different image registration techniques. We evaluated whole-body 18F-FDG-PET and CT data sets of 71 oncologic patients. Images were fused retrospectively using Stealth Station System, Treon (Medtronic Inc., Louisville, CO, USA) equipped with Cranial4 Software. External markers fixed to a vacuum mattress were used as reference for exact repositioning. Registration was repeated using internal anatomic landmarks and Automerge software, assessing accuracy for all three methods, measuring distances of liver representation in CT and PET with reference to a common coordinate system. On first measurement of image fusions with external markers, 53 were successful, 16 feasible and 2 not successful. Using anatomic landmarks, 42 were successful, 26 feasible and 3 not successful. Using Automerge Software only 13 were successful. The mean distance between center points in PET and CT was 7.69±4.96 mm on first, and 7.65±4.2 mm on second measurement. Results with external markers correlate very well and inaccuracies are significantly lower (P<0.001) than results using anatomical landmarks (10.38±6.13 mm and 10.83±6.23 mm). Analysis revealed a significantly faster alignment using external markers (P<0.001). External fiducials in combination with immobilization devices and breathing protocols allow for highly accurate image fusion cost-effectively and significantly less time, posing an attractive alternative for PET/CT interpretation when a hybrid scanner is not available.

Comparison between free-hand and O-arm-based navigated posterior lumbar interbody fusion in elderly cohorts with three-level lumbar degenerative disease.

PubMed

Wang, Yucheng; Chen, Kangwu; Chen, Hao; Zhang, Kai; Lu, Jian; Mao, Haiqing; Yang, Huilin

2018-06-06

This retrospective cohort study aims to evaluate the effects of introducing the O-arm-based navigation technique into the traditional posterior lumbar interbody fusion (PLIF) procedure treating elderly patients with three-level lumbar degenerative diseases. Forty-one consecutive elderly patients were enrolled according to the criteria. There were 21 patients in the free-hand group and 20 patients in the O-arm group. Both two groups underwent the PLIF with or without the O-arm-based navigation technique. The demographic features, clinical data and outcomes, and radiological information were collected for further analysis. The average follow-up time was 18.3 (range, 12-28) months in the free-hand group and 16.7 (range, 12-24) months in the O-arm group. Comparison between two groups revealed no significant difference regarding demographic features. The operation time took in the navigation group was significantly less than that in the free-hand group (222.55 ± 38.00 mins versus 255.19 ± 40.26 mins, P < 0.05). Both VAS and ODI were improved post-operatively in two groups while comparison between groups showed no difference. The accuracy rate of pedicle screw positioning was 88.7% in the free-hand group to 96.9% in the O-arm group (P < 0.05). The O-arm-based navigation is an efficacious auxiliary technique which could significantly improve the accuracy of pedicle screw insertion, especially in cases of patients with complex anatomic degenerative diseases, without sacrificing the feasibility and reliable outcome of traditional PLIF.

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

The SIGN nail for knee fusion: technique and clinical results.

PubMed

Anderson, Duane Ray; Anderson, Lucas Aaron; Haller, Justin M; Feyissa, Abebe Chala

2016-02-05

Evaluate the efficacy of using the SIGN nail for instrumented knee fusion. Six consecutive patients (seven knees, three males) with an average age of 30.5 years (range, 18-50 years) underwent a knee arthrodesis with SIGN nail (mean follow-up 10.7 months; range, 8-14 months). Diagnoses included tuberculosis (two knees), congenital knee dislocation in two knees (one patient), bacterial septic arthritis (one knee), malunited spontaneous fusion (one knee), and severe gout with 90° flexion contracture (one knee). The nail was inserted through an anteromedial entry point on the femur and full weightbearing was permitted immediately. All knees had clinical and radiographic evidence of fusion at final follow-up and none required further surgery. Four of six patients ambulated without assistive device, and all patients reported improved overall physical function. There were no post-operative complications. The technique described utilizing the SIGN nail is both safe and effective for knee arthrodesis and useful for austere environments with limited fluoroscopy and implant options.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

Localization Using Visual Odometry and a Single Downward-Pointing Camera

NASA Technical Reports Server (NTRS)

Swank, Aaron J.

2012-01-01

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods

PubMed Central

Li, Zhongwei; Liu, Xingjian; Wen, Shifeng; He, Piyao; Zhong, Kai; Wei, Qingsong; Shi, Yusheng; Liu, Sheng

2018-01-01

Lack of monitoring of the in situ process signatures is one of the challenges that has been restricting the improvement of Powder-Bed-Fusion Additive Manufacturing (PBF AM). Among various process signatures, the monitoring of the geometric signatures is of high importance. This paper presents the use of vision sensing methods as a non-destructive in situ 3D measurement technique to monitor two main categories of geometric signatures: 3D surface topography and 3D contour data of the fusion area. To increase the efficiency and accuracy, an enhanced phase measuring profilometry (EPMP) is proposed to monitor the 3D surface topography of the powder bed and the fusion area reliably and rapidly. A slice model assisted contour detection method is developed to extract the contours of fusion area. The performance of the techniques is demonstrated with some selected measurements. Experimental results indicate that the proposed method can reveal irregularities caused by various defects and inspect the contour accuracy and surface quality. It holds the potential to be a powerful in situ 3D monitoring tool for manufacturing process optimization, close-loop control, and data visualization. PMID:29649171

Microstructure Characterization of Fiber Laser Welds of S690QL High-Strength Steels

NASA Astrophysics Data System (ADS)

Li, Baoming; Xu, Peiquan; Lu, Fenggui; Gong, Hongying; Cui, Haichao; Liu, Chuangen

2018-02-01

The use of fiber laser welding to join S690QL steels has attracted interest in the field of construction and assembly. Herein, 13-mm-thick S690QL welded joints were obtained without filler materials using the fiber laser. The as-welded microstructures and the impact energies of the joints were characterized and measured using electron microscopy in conjunction with high-resolution transmission electron images, X-ray diffraction, and impact tests. The results indicated that a single-sided welding technique could be used to join S690QL steels up to a thickness of 12 mm (fail to fuse the joint in the root) when the laser power is equal to 12 kW (scan speed 1 m/min). Double-side welding technique allows better weld penetration and better control of heat distribution. Observation of the samples showed that the fusion zone exhibited bainitic and martensitic microstructures with increased amounts of martensites (Ms) compared with the base materials. Also, the grains in the fusion zone increased in coarseness as the heat input was increased. The fusion zone exhibited increased hardness (397 HV0.2) while exhibiting a simultaneous decrease in the impact toughness. The maximum impact energy value of 26 J was obtained from the single-side-welded sample, which is greater than those obtained from the double-side-welded samples (maximum of 18 J). Many more dislocations and plastic deformations were found in the fusion zone than the heat-affected zone in the joint, which hardened the joints and lowered the impact toughness. The microstructures characterized by FTEM-energy-dispersive X-ray spectrometer also exhibited laths of M, as well as stacking faults and dislocations featuring high-density, interfacial structure ledges that occur between the high-angle grain boundaries and the M and bainite.

Toward an optimisation technique for dynamically monitored environment

NASA Astrophysics Data System (ADS)

Shurrab, Orabi M.

2016-10-01

The data fusion community has introduced multiple procedures of situational assessments; this is to facilitate timely responses to emerging situations. More directly, the process refinement of the Joint Directors of Laboratories (JDL) is a meta-process to assess and improve the data fusion task during real-time operation. In other wording, it is an optimisation technique to verify the overall data fusion performance, and enhance it toward the top goals of the decision-making resources. This paper discusses the theoretical concept of prioritisation. Where the analysts team is required to keep an up to date with the dynamically changing environment, concerning different domains such as air, sea, land, space and cyberspace. Furthermore, it demonstrates an illustration example of how various tracking activities are ranked, simultaneously into a predetermined order. Specifically, it presents a modelling scheme for a case study based scenario, where the real-time system is reporting different classes of prioritised events. Followed by a performance metrics for evaluating the prioritisation process of situational awareness (SWA) domain. The proposed performance metrics has been designed and evaluated using an analytical approach. The modelling scheme represents the situational awareness system outputs mathematically, in the form of a list of activities. Such methods allowed the evaluation process to conduct a rigorous analysis of the prioritisation process, despite any constrained related to a domain-specific configuration. After conducted three levels of assessments over three separates scenario, The Prioritisation Capability Score (PCS) has provided an appropriate scoring scheme for different ranking instances, Indeed, from the data fusion perspectives, the proposed metric has assessed real-time system performance adequately, and it is capable of conducting a verification process, to direct the operator's attention to any issue, concerning the prioritisation capability of situational awareness domain.

The research and realization of digital management platform for ultra-precision optical elements within life-cycle

NASA Astrophysics Data System (ADS)

Wang, Juan; Wang, Jian; Li, Lijuan; Zhou, Kun

2014-08-01

In order to solve the information fusion, process integration, collaborative design and manufacturing for ultra-precision optical elements within life-cycle management, this paper presents a digital management platform which is based on product data and business processes by adopting the modern manufacturing technique, information technique and modern management technique. The architecture and system integration of the digital management platform are discussed in this paper. The digital management platform can realize information sharing and interaction for information-flow, control-flow and value-stream from user's needs to offline in life-cycle, and it can also enhance process control, collaborative research and service ability of ultra-precision optical elements.

Feasibility study of single photon emission coupled tomography imaging technique based on prompt gamma ray during antiproton therapy using boron particle

NASA Astrophysics Data System (ADS)

Shin, Han-Back; Jung, Joo-Young; Kim, Moo-Sub; Kim, Sunmi; Choi, Yong; Yoon, Do-Kun; Suh, Tae Suk

2018-06-01

In this study, we proposed an absorbed-dose monitoring technique using prompt gamma rays emitted from the reaction between an antiproton and a boron particle, and demonstrated the greater physical effect of the antiproton boron fusion therapy in comparison with proton beam using Monte Carlo simulation. The physical effect of the treatment, which was 3.5 times greater, was confirmed from the antiproton beam irradiation compared to the proton beam irradiation. Moreover, the prompt gamma ray image is acquired successfully during antiproton irradiation to boron regions. The results show the application feasibility of absorbed dose monitoring technique proposed in our study.

Minimally invasive versus open sacroiliac joint fusion: are they similarly safe and effective?

PubMed

Ledonio, Charles G T; Polly, David W; Swiontkowski, Marc F

2014-06-01

The sacroiliac joint has been implicated as a source of chronic low back pain in 15% to 30% of patients. When nonsurgical approaches fail, sacroiliac joint fusion may be recommended. Advances in intraoperative image guidance have assisted minimally invasive surgical (MIS) techniques using ingrowth-coated fusion rods; however, how these techniques perform relative to open anterior fusion of the sacroiliac joint using plates and screws is not known. We compared estimated blood loss (EBL), surgical time, length of hospital stay (LOS), and Oswestry Disability Index (ODI) between patients undergoing MIS and open sacroiliac joint fusion. We retrospectively studied 63 patients (open: 36; MIS: 27) who underwent sacroiliac joint fusion with minimum 1-year followup at our institution from 2006 to 2011. Of those, 10 in the open group had incomplete records. All patients had sacroiliac joint dysfunction confirmed by image-guided intraarticular anesthetic sacroiliac joint injection and had failed nonoperative treatment. Patients were matched via propensity score, adjusting for age, sex, BMI, history of spine fusion, and preoperative ODI scores, leaving 22 in each group. Nine patients were not matched. We reviewed patient medical records to obtain EBL, length of surgery, LOS, and pre- and postoperative ODI scores. Mean followup was 13 months (range, 11-33 months) in the open group and 15 months (range, 12-26 months) in the MIS group. Patients in the open group had a higher mean EBL (681 mL versus 41 mL, p < 0.001). Mean surgical time and LOS were shorter in the MIS group than in the open group (68 minutes versus 128 minutes and 3.3 days versus 2 days, p < 0.001 for both). With the numbers available, mean postoperative ODI scores were not different between groups (47% versus 54%, p = 0.272). EBL, surgery time, and LOS favored the MIS sacroiliac fusion group. With the numbers available, ODI scores were similar between groups, though the study size was relatively small and it is possible that the study was underpowered on this end point. Because the implants used for these procedures make assessment of fusion challenging with available imaging techniques, we do not know how many patients' sacroiliac joints successfully fused, so longer followup and critical evaluation of outcomes scores over time are called for. Level III, therapeutic study. See Instructions for Authors for a complete description of levels of evidence.

A Summary of the NASA Fusion Propulsion Workshop 2000

NASA Technical Reports Server (NTRS)

Thio, Y. C. Francis; Turchi, Peter J.; Santarius, John F.; Schafer, Charles (Technical Monitor)

2001-01-01

A NASA Fusion Propulsion Workshop was held on Nov. 8 and 9, 2000 at Marshall Space Flight Center (MSFC) in Huntsville, Alabama. A total of 43 papers were presented at the Workshop orally or by posters, covering a broad spectrum of issues related to applying fusion to propulsion. The status of fusion research was reported at the Workshop showing the outstanding scientific research that has been accomplished worldwide in the fusion energy research program. The international fusion research community has demonstrated the scientific principles of fusion creating plasmas with conditions for fusion burn with a gain of order unity: 0.25 in Princeton TFTR, 0.65 in the Joint European Torus, and a Q-equivalent of 1.25 in Japan's JT-60. This research has developed an impressive range of physics and technological capabilities that may be applied effectively to the research of possibly new propulsion-oriented fusion schemes. The pertinent physics capabilities include the plasma computational tools, the experimental plasma facilities, the diagnostics techniques, and the theoretical understanding. The enabling technologies include the various plasma heating, acceleration, and the pulsed power technologies.

Homeland security application of the Army Soft Target Exploitation and Fusion (STEF) system

NASA Astrophysics Data System (ADS)

Antony, Richard T.; Karakowski, Joseph A.

2010-04-01

A fusion system that accommodates both text-based extracted information along with more conventional sensor-derived input has been developed and demonstrated in a terrorist attack scenario as part of the Empire Challenge (EC) 09 Exercise. Although the fusion system was developed to support Army military analysts, the system, based on a set of foundational fusion principles, has direct applicability to department of homeland security (DHS) & defense, law enforcement, and other applications. Several novel fusion technologies and applications were demonstrated in EC09. One such technology is location normalization that accommodates both fuzzy semantic expressions such as behind Library A, across the street from the market place, as well as traditional spatial representations. Additionally, the fusion system provides a range of fusion products not supported by traditional fusion algorithms. Many of these additional capabilities have direct applicability to DHS. A formal test of the fusion system was performed during the EC09 exercise. The system demonstrated that it was able to (1) automatically form tracks, (2) help analysts visualize behavior of individuals over time, (3) link key individuals based on both explicit message-based information as well as discovered (fusion-derived) implicit relationships, and (4) suggest possible individuals of interest based on their association with High Value Individuals (HVI) and user-defined key locations.

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications.

PubMed

Mendes, José Jair Alves; Vieira, Mário Elias Marinho; Pires, Marcelo Bissi; Stevan, Sergio Luiz

2016-09-23

The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

Continuous internal channels formed in aluminum fusion welds

NASA Technical Reports Server (NTRS)

Gault, J.; Sabo, W.

1967-01-01

Process produces continuous internal channel systems on a repeatable basis in 2014-T6 aluminum. Standard machining forms the initial channel, which is filled with tungsten carbide powder. TIG machine fusion welding completes formation of the channel. Chem-mill techniques enlarge it to the desired size.

Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang

2015-01-01

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

Bringing functions together with fusion enzymes--from nature's inventions to biotechnological applications.

PubMed

Elleuche, Skander

2015-02-01

It is a mammoth task to develop a modular protein toolbox enabling the production of posttranslational organized multifunctional enzymes that catalyze reactions in complex pathways. However, nature has always guided scientists to mimic evolutionary inventions in the laboratory and, nowadays, versatile methods have been established to experimentally connect enzymatic activities with multiple advantages. Among the oldest known natural examples is the linkage of two or more juxtaposed proteins catalyzing consecutive, non-consecutive, or opposing reactions by a native peptide bond. There are multiple reasons for the artificial construction of such fusion enzymes including improved catalytic activities, enabled substrate channelling by proximity of biocatalysts, higher stabilities, and cheaper production processes. To produce fused proteins, it is either possible to genetically fuse coding open reading frames or to connect proteins in a posttranslational process. Molecular biology techniques that have been established for the production of end-to-end or insertional fusions include overlap extension polymerase chain reaction, cloning, and recombination approaches. Depending on their flexibility and applicability, these methods offer various advantages to produce fusion genes in high throughput, different orientations, and including linker sequences to maximize the flexibility and performance of fusion partners. In this review, practical techniques to fuse genes are highlighted, enzymatic parameters to choose adequate enzymes for fusion approaches are summarized, and examples with biotechnological relevance are presented including a focus on plant biomass-degrading glycosyl hydrolases.

Efficient Kriging via Fast Matrix-Vector Products

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Raykar, Vikas C.; Duraiswami, Ramani; Mount, David M.

2008-01-01

Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrixvector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.

The emissivities of liquid metals at their fusion temperatures.

NASA Technical Reports Server (NTRS)

Bonnell, D. W.; Treverton, J. A.; Valerga, A. J.; Margrave , J. L.

1972-01-01

The emissivities for several transition metals and various other metals and compounds in the liquid state at their fusion temperatures have been determined in this laboratory. The technique used involves electromagnetic levitation-induction heating of the materials in an inert atmosphere. The brightness temperature of the liquid phase of the material is measured as the material is heated through fusion. Given a reliable value of the fusion temperature, which is available for most pure substances, one may readily calculate an emissivity for the liquid phase at the fusion temperature. Even in cases where melting points are poorly known, the brightness temperatures are unique parameters, independent of the temperature scale and measured for a chemically defined system at a fixed point.

Hybrid Surgery Combined with Dynamic Stabilization System and Fusion for the Multilevel Degenerative Disease of the Lumbosacral Spine.

PubMed

Lee, Soo Eon; Jahng, Tae-Ahn; Kim, Hyun Jib

2015-01-01

As motion-preserving technique has been developed, the concept of hybrid surgery involves simultaneous application of two different kinds of devices, dynamic stabilization system and fusion technique. In the present study, the application of hybrid surgery for lumbosacral degenerative disease involving two-segments and its long-term outcome were investigated. Fifteen patients with hybrid surgery (Hybrid group) and 10 patients with two-segment fusion (Fusion group) were retrospectively compared. Preoperative grade for disc degeneration was not different between the two groups, and the most common operated segment had the most degenerated disc grade in both groups; L4-5 and L5-S1 in the Hybrid group, and L3-4 and L4-5 in Fusion group. Over 48 months of follow-up, lumbar lordosis and range of motion (ROM) at the T12-S1 global segment were preserved in the Hybrid group, and the segmental ROM at the dynamic stabilized segment maintained at final follow-up. The Fusion group had a significantly decreased global ROM and a decreased segmental ROM with larger angles compared to the Hybrid group. Defining a 2-mm decrease in posterior disc height (PDH) as radiologic adjacent segment pathology (ASP), these changes were observed in 6 and 7 patients in the Hybrid and Fusion group, respectively. However, the last PDH at the above adjacent segment had statistically higher value in Hybrid group. Pain score for back and legs was much reduced in both groups. Functional outcome measured by Oswestry disability index (ODI), however, had better improvement in Hybrid group. Hybrid surgery, combined dynamic stabilization system and fusion, can be effective surgical treatment for multilevel degenerative lumbosacral spinal disease, maintaining lumbar motion and delaying disc degeneration.

Hybrid Surgery Combined with Dynamic Stabilization System and Fusion for the Multilevel Degenerative Disease of the Lumbosacral Spine

PubMed Central

Lee, Soo Eon; Kim, Hyun Jib

2015-01-01

Background As motion-preserving technique has been developed, the concept of hybrid surgery involves simultaneous application of two different kinds of devices, dynamic stabilization system and fusion technique. In the present study, the application of hybrid surgery for lumbosacral degenerative disease involving two-segments and its long-term outcome were investigated. Methods Fifteen patients with hybrid surgery (Hybrid group) and 10 patients with two-segment fusion (Fusion group) were retrospectively compared. Results Preoperative grade for disc degeneration was not different between the two groups, and the most common operated segment had the most degenerated disc grade in both groups; L4-5 and L5-S1 in the Hybrid group, and L3-4 and L4-5 in Fusion group. Over 48 months of follow-up, lumbar lordosis and range of motion (ROM) at the T12-S1 global segment were preserved in the Hybrid group, and the segmental ROM at the dynamic stabilized segment maintained at final follow-up. The Fusion group had a significantly decreased global ROM and a decreased segmental ROM with larger angles compared to the Hybrid group. Defining a 2-mm decrease in posterior disc height (PDH) as radiologic adjacent segment pathology (ASP), these changes were observed in 6 and 7 patients in the Hybrid and Fusion group, respectively. However, the last PDH at the above adjacent segment had statistically higher value in Hybrid group. Pain score for back and legs was much reduced in both groups. Functional outcome measured by Oswestry disability index (ODI), however, had better improvement in Hybrid group. Conclusion Hybrid surgery, combined dynamic stabilization system and fusion, can be effective surgical treatment for multilevel degenerative lumbosacral spinal disease, maintaining lumbar motion and delaying disc degeneration. PMID:26484008

Appearance-based human gesture recognition using multimodal features for human computer interaction

NASA Astrophysics Data System (ADS)

Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

2011-03-01

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

Spin distribution of evaporation residues formed in complete and incomplete fusion in 16O+154Sm system

NASA Astrophysics Data System (ADS)

Singh, D.; Linda, Sneha B.; Giri, Pankaj K.; Mahato, Amritraj; Tripathi, R.; Kumar, Harish; Afzal Ansari, M.; Sathik, N. P. M.; Ali, Rahbar; Kumar, Rakesh; Muralithar, S.; Singh, R. P.

2017-11-01

Spin distributions for several evaporation residues populated in the 16O+154Sm system have been measured at projectile energy ≈ 6.2 MeV/A by using the charged particle-γ-coincidence technique. The measured spin distributions of the evaporation residues populated through incomplete fusion associated with 'fast' α and 2α-emission channels are found to be entirely different from fusion-evaporation channels. It is observed that the mean input angular momentum for the evaporation residues formed in incomplete fusion channel is relatively higher than that observed for evaporation residues in complete fusion channels. The feeding intensity profile of evaporation residues populated through complete fusion and incomplete fusion have also been studied. The incomplete fusion channels are found to have narrow range feeding only for high spin states, while complete fusion channels are strongly fed over a broad spin range and widely populated. Comparison of present results with earlier data suggests that the mean input angular momentum values are relatively smaller for spherical target than that of deformed target using the same projectile and incident energy highlighting the role of target deformation in incomplete fusion dynamics.

An Outcome and Cost Analysis Comparing Single-Level Minimally Invasive Transforaminal Lumbar Interbody Fusion Using Intraoperative Fluoroscopy versus Computed Tomography-Guided Navigation.

PubMed

Khanna, Ryan; McDevitt, Joseph L; Abecassis, Zachary A; Smith, Zachary A; Koski, Tyler R; Fessler, Richard G; Dahdaleh, Nader S

2016-10-01

Minimally invasive transforaminal lumbar interbody fusion (TLIF) has undergone significant evolution since its conception as a fusion technique to treat lumbar spondylosis. Minimally invasive TLIF is commonly performed using intraoperative two-dimensional fluoroscopic x-rays. However, intraoperative computed tomography (CT)-based navigation during minimally invasive TLIF is gaining popularity for improvements in visualizing anatomy and reducing intraoperative radiation to surgeons and operating room staff. This is the first study to compare clinical outcomes and cost between these 2 imaging techniques during minimally invasive TILF. For comparison, 28 patients who underwent single-level minimally invasive TLIF using fluoroscopy were matched to 28 patients undergoing single-level minimally invasive TLIF using CT navigation based on race, sex, age, smoking status, payer type, and medical comorbidities (Charlson Comorbidity Index). The minimum follow-up time was 6 months. The 2 groups were compared in regard to clinical outcomes and hospital reimbursement from the payer perspective. Average surgery time, anesthesia time, and hospital length of stay were similar for both groups, but average estimated blood loss was lower in the fluoroscopy group compared with the CT navigation group (154 mL vs. 262 mL; P = 0.016). Oswestry Disability Index, back visual analog scale, and leg visual analog scale scores similarly improved in both groups (P > 0.05) at 6-month follow-up. Cost analysis showed that average hospital payments were similar in the fluoroscopy versus the CT navigation groups ($32,347 vs. $32,656; P = 0.925) as well as payments for the operating room (P = 0.868). Single minimally invasive TLIF performed with fluoroscopy versus CT navigation showed similar clinical outcomes and cost at 6 months. Copyright © 2016 Elsevier Inc. All rights reserved.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

An in situ accelerator-based diagnostic for plasma-material interactions science on magnetic fusion devices.

PubMed

Hartwig, Zachary S; Barnard, Harold S; Lanza, Richard C; Sorbom, Brandon N; Stahle, Peter W; Whyte, Dennis G

2013-12-01

This paper presents a novel particle accelerator-based diagnostic that nondestructively measures the evolution of material surface compositions inside magnetic fusion devices. The diagnostic's purpose is to contribute to an integrated understanding of plasma-material interactions in magnetic fusion, which is severely hindered by a dearth of in situ material surface diagnosis. The diagnostic aims to remotely generate isotopic concentration maps on a plasma shot-to-shot timescale that cover a large fraction of the plasma-facing surface inside of a magnetic fusion device without the need for vacuum breaks or physical access to the material surfaces. Our instrument uses a compact (~1 m), high-current (~1 milliamp) radio-frequency quadrupole accelerator to inject 0.9 MeV deuterons into the Alcator C-Mod tokamak at MIT. We control the tokamak magnetic fields--in between plasma shots--to steer the deuterons to material surfaces where the deuterons cause high-Q nuclear reactions with low-Z isotopes ~5 μm into the material. The induced neutrons and gamma rays are measured with scintillation detectors; energy spectra analysis provides quantitative reconstruction of surface compositions. An overview of the diagnostic technique, known as accelerator-based in situ materials surveillance (AIMS), and the first AIMS diagnostic on the Alcator C-Mod tokamak is given. Experimental validation is shown to demonstrate that an optimized deuteron beam is injected into the tokamak, that low-Z isotopes such as deuterium and boron can be quantified on the material surfaces, and that magnetic steering provides access to different measurement locations. The first AIMS analysis, which measures the relative change in deuterium at a single surface location at the end of the Alcator C-Mod FY2012 plasma campaign, is also presented.

Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles

PubMed Central

de Ponte Müller, Fabian

2017-01-01

Future driver assistance systems will rely on accurate, reliable and continuous knowledge on the position of other road participants, including pedestrians, bicycles and other vehicles. The usual approach to tackle this requirement is to use on-board ranging sensors inside the vehicle. Radar, laser scanners or vision-based systems are able to detect objects in their line-of-sight. In contrast to these non-cooperative ranging sensors, cooperative approaches follow a strategy in which other road participants actively support the estimation of the relative position. The limitations of on-board ranging sensors regarding their detection range and angle of view and the facility of blockage can be approached by using a cooperative approach based on vehicle-to-vehicle communication. The fusion of both, cooperative and non-cooperative strategies, seems to offer the largest benefits regarding accuracy, availability and robustness. This survey offers the reader a comprehensive review on different techniques for vehicle relative positioning. The reader will learn the important performance indicators when it comes to relative positioning of vehicles, the different technologies that are both commercially available and currently under research, their expected performance and their intrinsic limitations. Moreover, the latest research in the area of vision-based systems for vehicle detection, as well as the latest work on GNSS-based vehicle localization and vehicular communication for relative positioning of vehicles, are reviewed. The survey also includes the research work on the fusion of cooperative and non-cooperative approaches to increase the reliability and the availability. PMID:28146129

Fusion of Modis and Palsar Principal Component Images Through Curvelet Transform for Land Cover Classification

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Kumar, Harish

Earth observation satellites provide data that covers different portions of the electromagnetic spectrum at different spatial and spectral resolutions. The increasing availability of information products generated from satellite images are extending the ability to understand the patterns and dynamics of the earth resource systems at all scales of inquiry. In which one of the most important application is the generation of land cover classification from satellite images for understanding the actual status of various land cover classes. The prospect for the use of satel-lite images in land cover classification is an extremely promising one. The quality of satellite images available for land-use mapping is improving rapidly by development of advanced sensor technology. Particularly noteworthy in this regard is the improved spatial and spectral reso-lution of the images captured by new satellite sensors like MODIS, ASTER, Landsat 7, and SPOT 5. For the full exploitation of increasingly sophisticated multisource data, fusion tech-niques are being developed. Fused images may enhance the interpretation capabilities. The images used for fusion have different temporal, and spatial resolution. Therefore, the fused image provides a more complete view of the observed objects. It is one of the main aim of image fusion to integrate different data in order to obtain more information that can be de-rived from each of the single sensor data alone. A good example of this is the fusion of images acquired by different sensors having a different spatial resolution and of different spectral res-olution. Researchers are applying the fusion technique since from three decades and propose various useful methods and techniques. The importance of high-quality synthesis of spectral information is well suited and implemented for land cover classification. More recently, an underlying multiresolution analysis employing the discrete wavelet transform has been used in image fusion. It was found that multisensor image fusion is a tradeoff between the spectral information from a low resolution multi-spectral images and the spatial information from a high resolution multi-spectral images. With the wavelet transform based fusion method, it is easy to control this tradeoff. A new transform, the curvelet transform was used in recent years by Starck. A ridgelet transform is applied to square blocks of detail frames of undecimated wavelet decomposition, consequently the curvelet transform is obtained. Since the ridgelet transform possesses basis functions matching directional straight lines therefore, the curvelet transform is capable of representing piecewise linear contours on multiple scales through few significant coefficients. This property leads to a better separation between geometric details and background noise, which may be easily reduced by thresholding curvelet coefficients before they are used for fusion. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 m to 14.4 m and also it is freely available. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. In this paper, the band 1 of spatial resolution 250 m and bandwidth 620-670 nm, and band 2, of spatial resolution of 250m and bandwidth 842-876 nm is considered as these bands has special features to identify the agriculture and other land covers. In January 2006, the Advanced Land Observing Satellite (ALOS) was successfully launched by the Japan Aerospace Exploration Agency (JAXA). The Phased Arraytype L-band SAR (PALSAR) sensor onboard the satellite acquires SAR imagery at a wavelength of 23.5 cm (frequency 1.27 GHz) with capabilities of multimode and multipolarization observation. PALSAR can operate in several modes: the fine-beam single (FBS) polarization mode (HH), fine-beam dual (FBD) polariza-tion mode (HH/HV or VV/VH), polarimetric (PLR) mode (HH/HV/VH/VV), and ScanSAR (WB) mode (HH/VV) [15]. These makes PALSAR imagery very attractive for spatially and temporally consistent monitoring system. The Overview of Principal Component Analysis is that the most of the information within all the bands can be compressed into a much smaller number of bands with little loss of information. It allows us to extract the low-dimensional subspaces that capture the main linear correlation among the high-dimensional image data. This facilitates viewing the explained variance or signal in the available imagery, allowing both gross and more subtle features in the imagery to be seen. In this paper we have explored the fusion technique for enhancing the land cover classification of low resolution satellite data espe-cially freely available satellite data. For this purpose, we have considered to fuse the PALSAR principal component data with MODIS principal component data. Initially, the MODIS band 1 and band 2 is considered, its principal component is computed. Similarly the PALSAR HH, HV and VV polarized data are considered, and there principal component is also computed. con-sequently, the PALSAR principal component image is fused with MODIS principal component image. The aim of this paper is to analyze the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of PALSAR data to MODIS data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied for the resultant fused image. It is qualitatively and visually observed that the overall classification accuracy of MODIS image after fusion is enhanced. This type of fusion technique may be quite helpful in near future to use freely available satellite data to develop monitoring system for different land cover classes on the earth.

confFuse: High-Confidence Fusion Gene Detection across Tumor Entities.

PubMed

Huang, Zhiqin; Jones, David T W; Wu, Yonghe; Lichter, Peter; Zapatka, Marc

2017-01-01

Background: Fusion genes play an important role in the tumorigenesis of many cancers. Next-generation sequencing (NGS) technologies have been successfully applied in fusion gene detection for the last several years, and a number of NGS-based tools have been developed for identifying fusion genes during this period. Most fusion gene detection tools based on RNA-seq data report a large number of candidates (mostly false positives), making it hard to prioritize candidates for experimental validation and further analysis. Selection of reliable fusion genes for downstream analysis becomes very important in cancer research. We therefore developed confFuse, a scoring algorithm to reliably select high-confidence fusion genes which are likely to be biologically relevant. Results: confFuse takes multiple parameters into account in order to assign each fusion candidate a confidence score, of which score ≥8 indicates high-confidence fusion gene predictions. These parameters were manually curated based on our experience and on certain structural motifs of fusion genes. Compared with alternative tools, based on 96 published RNA-seq samples from different tumor entities, our method can significantly reduce the number of fusion candidates (301 high-confidence from 8,083 total predicted fusion genes) and keep high detection accuracy (recovery rate 85.7%). Validation of 18 novel, high-confidence fusions detected in three breast tumor samples resulted in a 100% validation rate. Conclusions: confFuse is a novel downstream filtering method that allows selection of highly reliable fusion gene candidates for further downstream analysis and experimental validations. confFuse is available at https://github.com/Zhiqin-HUANG/confFuse.

General fusion approaches for the age determination of latent fingerprint traces: results for 2D and 3D binary pixel feature fusion

NASA Astrophysics Data System (ADS)

Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja

2012-03-01

Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. Solving this issue could provide criminal investigators with the specific time a fingerprint trace was left on a surface, and therefore would enable them to link potential suspects to the time a crime took place as well as to reconstruct the sequence of events or eliminate irrelevant fingerprints to ensure privacy constraints. Transferring imaging techniques from different application areas, such as 3D image acquisition, surface measurement and chemical analysis to the domain of lifting latent biometric fingerprint traces is an upcoming trend in forensics. Such non-destructive sensor devices might help to solve the challenge of determining the age of a latent fingerprint trace, since it provides the opportunity to create time series and process them using pattern recognition techniques and statistical methods on digitized 2D, 3D and chemical data, rather than classical, contact-based capturing techniques, which alter the fingerprint trace and therefore make continuous scans impossible. In prior work, we have suggested to use a feature called binary pixel, which is a novel approach in the working field of fingerprint age determination. The feature uses a Chromatic White Light (CWL) image sensor to continuously scan a fingerprint trace over time and retrieves a characteristic logarithmic aging tendency for 2D-intensity as well as 3D-topographic images from the sensor. In this paper, we propose to combine such two characteristic aging features with other 2D and 3D features from the domains of surface measurement, microscopy, photography and spectroscopy, to achieve an increase in accuracy and reliability of a potential future age determination scheme. Discussing the feasibility of such variety of sensor devices and possible aging features, we propose a general fusion approach, which might combine promising features to a joint age determination scheme in future. We furthermore demonstrate the feasibility of the introduced approach by exemplary fusing the binary pixel features based on 2D-intensity and 3D-topographic images of the mentioned CWL sensor. We conclude that a formula based age determination approach requires very precise image data, which cannot be achieved at the moment, whereas a machine learning based classification approach seems to be feasible, if an adequate amount of features can be provided.

Supervised classification of aerial imagery and multi-source data fusion for flood assessment

NASA Astrophysics Data System (ADS)

Sava, E.; Harding, L.; Cervone, G.

2015-12-01

Floods are among the most devastating natural hazards and the ability to produce an accurate and timely flood assessment before, during, and after an event is critical for their mitigation and response. Remote sensing technologies have become the de-facto approach for observing the Earth and its environment. However, satellite remote sensing data are not always available. For these reasons, it is crucial to develop new techniques in order to produce flood assessments during and after an event. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. This research presents a fusion technique using satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and tweets. A new computational methodology is proposed based on machine learning algorithms to automatically identify water pixels in CAP imagery. Specifically, wavelet transformations are paired with multiple classifiers, run in parallel, to build models discriminating water and non-water regions. The learned classification models are first tested against a set of control cases, and then used to automatically classify each image separately. A measure of uncertainty is computed for each pixel in an image proportional to the number of models classifying the pixel as water. Geo-tagged tweets are continuously harvested and stored on a MongoDB and queried in real time. They are fused with CAP classified data, and with satellite remote sensing derived flood extent results to produce comprehensive flood assessment maps. The final maps are then compared with FEMA generated flood extents to assess their accuracy. The proposed methodology is applied on two test cases, relative to the 2013 floods in Boulder CO, and the 2015 floods in Texas.

Fusion of a FBG-based health monitoring system for wind turbines with a fiber-optic lightning detection system

NASA Astrophysics Data System (ADS)

Krämer, Sebastian G. M.; Wiesent, Benjamin; Müller, Mathias S.; Puente León, Fernando; Méndez Hernández, Yarú

2008-04-01

Wind turbine blades are made of composite materials and reach a length of more than 42 meters. Developments for modern offshore turbines are working on about 60 meters long blades. Hence, with the increasing height of the turbines and the remote locations of the structures, health monitoring systems are becoming more and more important. Therefore, fiber-optic sensor systems are well-suited, as they are lightweight, immune against electromagnetic interference (EMI), and as they can be multiplexed. Based on two separately existing concepts for strain measurements and lightning detection on wind turbines, a fused system is presented. The strain measurement system is based on a reflective fiber-Bragg-grating (FBG) network embedded in the composite structure of the blade. For lightning detection, transmissive &fiber-optic magnetic field sensors based on the Faraday effect are used to register the lightning parameters and estimate the impact point. Hence, an existing lightning detection system will be augmented, due to the fusion, by the capability to measure strain, temperature and vibration. Load, strain, temperature and impact detection information can be incorporated into the turbine's monitoring or SCADA system and remote controlled by operators. Data analysis techniques allow dynamic maintenance scheduling to become a reality, what is of special interest for the cost-effective maintenance of large offshore or badly attainable onshore wind parks. To prove the feasibility of this sensor fusion on one optical fiber, interferences between both sensor systems are investigated and evaluated.

A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations

PubMed Central

Salinas, Carlota; Fernández, Roemi; Montes, Héctor; Armada, Manuel

2015-01-01

Image registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and RGB cameras is an instance that problem. Typically, the fusion of these sensors is based on the extrinsic parameter computation of the coordinate transformation between the two cameras. This leads to a loss of colour information because of the low resolution of the ToF camera, and sophisticated algorithms are required to minimize this issue. This work proposes a method for sensor registration with non-common features and that avoids the loss of colour information. The depth information is used as a virtual feature for estimating a depth-dependent homography lookup table (Hlut). The homographies are computed within sets of ground control points of 104 images. Since the distance from the control points to the ToF camera are known, the working distance of each element on the Hlut is estimated. Finally, two series of experimental tests have been carried out in order to validate the capabilities of the proposed method. PMID:26404315

Human Detection from a Mobile Robot Using Fusion of Laser and Vision Information

PubMed Central

Fotiadis, Efstathios P.; Garzón, Mario; Barrientos, Antonio

2013-01-01

This paper presents a human detection system that can be employed on board a mobile platform for use in autonomous surveillance of large outdoor infrastructures. The prediction is based on the fusion of two detection modules, one for the laser and another for the vision data. In the laser module, a novel feature set that better encapsulates variations due to noise, distance and human pose is proposed. This enhances the generalization of the system, while at the same time, increasing the outdoor performance in comparison with current methods. The vision module uses the combination of the histogram of oriented gradients descriptor and the linear support vector machine classifier. Current approaches use a fixed-size projection to define regions of interest on the image data using the range information from the laser range finder. When applied to small size unmanned ground vehicles, these techniques suffer from misalignment, due to platform vibrations and terrain irregularities. This is effectively addressed in this work by using a novel adaptive projection technique, which is based on a probabilistic formulation of the classifier performance. Finally, a probability calibration step is introduced in order to optimally fuse the information from both modules. Experiments in real world environments demonstrate the robustness of the proposed method. PMID:24008280

Human detection from a mobile robot using fusion of laser and vision information.

PubMed

Fotiadis, Efstathios P; Garzón, Mario; Barrientos, Antonio

2013-09-04

This paper presents a human detection system that can be employed on board a mobile platform for use in autonomous surveillance of large outdoor infrastructures. The prediction is based on the fusion of two detection modules, one for the laser and another for the vision data. In the laser module, a novel feature set that better encapsulates variations due to noise, distance and human pose is proposed. This enhances the generalization of the system, while at the same time, increasing the outdoor performance in comparison with current methods. The vision module uses the combination of the histogram of oriented gradients descriptor and the linear support vector machine classifier. Current approaches use a fixed-size projection to define regions of interest on the image data using the range information from the laser range finder. When applied to small size unmanned ground vehicles, these techniques suffer from misalignment, due to platform vibrations and terrain irregularities. This is effectively addressed in this work by using a novel adaptive projection technique, which is based on a probabilistic formulation of the classifier performance. Finally, a probability calibration step is introduced in order to optimally fuse the information from both modules. Experiments in real world environments demonstrate the robustness of the proposed method.

Dust remobilization in fusion plasmas under steady state conditions

NASA Astrophysics Data System (ADS)

Tolias, P.; Ratynskaia, S.; De Angeli, M.; De Temmerman, G.; Ripamonti, D.; Riva, G.; Bykov, I.; Shalpegin, A.; Vignitchouk, L.; Brochard, F.; Bystrov, K.; Bardin, S.; Litnovsky, A.

2016-02-01

The first combined experimental and theoretical studies of dust remobilization by plasma forces are reported. The main theoretical aspects of remobilization in fusion devices under steady state conditions are analyzed. In particular, the dominant role of adhesive forces is highlighted and generic remobilization conditions—direct lift-up, sliding, rolling—are formulated. A novel experimental technique is proposed, based on controlled adhesion of dust grains on tungsten samples combined with detailed mapping of the dust deposition profile prior and post plasma exposure. Proof-of-principle experiments in the TEXTOR tokamak and the EXTRAP-T2R reversed-field pinch are presented. The versatile environment of the linear device Pilot-PSI allowed for experiments with different magnetic field topologies and varying plasma conditions that were complemented with camera observations.

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

Mou, J.I.; King, C.

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess themore » status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.« less

Hospital competitive intensity and perioperative outcomes following lumbar spinal fusion.

PubMed

Durand, Wesley M; Johnson, Joseph R; Li, Neill Y; Yang, JaeWon; Eltorai, Adam E M; DePasse, J Mason; Daniels, Alan H

2018-04-01

Interhospital competition has been shown to influence the adoption of surgical techniques and approaches, clinical patient outcomes, and health care resource use for select surgical procedures. However, little is known regarding these dynamics as they relate to spine surgery. This investigation sought to examine the relationship between interhospital competitive intensity and perioperative outcomes following lumbar spinal fusion. This study used the Nationwide Inpatient Sample dataset, years 2003, 2006, and 2009. Patients were included based on the presence of the International Classification of Disease, Ninth Edition, Clinical Modification (ICD-9-CM) codes corresponding to lumbar spinal fusion, as well as on the presence of data on the Herfindahl-Hirschman Index (HHI). The outcome measures are perioperative complications, defined using an ICD-9-CM coding algorithm. The HHI, a validated measure of competition within a market, was used to assess hospital market competitiveness. The HHI was calculated based on the hospital cachement area. Multiple regression was performed to adjust for confounding variables including patient age, gender, primary payer, severity of illness score, primary versus revision fusion, anterior versus posterior approach, national region, hospital bed size, location or teaching status, ownership, and year. Perioperative clinical outcomes were assessed based on ICD-9-CM codes with modifications. In total, 417,520 weighted patients (87,999 unweighted records) were analyzed. The mean cachement area HHI was 0.31 (range 0.099-0.724). The average patient age was 55.4 years (standard error=0.194), and the majority of patients were female (55.8%, n=232,727). The majority of procedures were primary spinal fusions (92.7%, n=386,998) and fusions with a posterior-only technique (81.5%, n=340,271). Most procedures occurred in the South (42.5%, n=177,509) or the Midwest (27.0%, n=112,758) regions. In the multiple regression analysis, increased hospital competitive intensity was associated with an increased total complication rate (odds ratio [OR] 1.52, p<.0001), device-related complications (OR 1.46, p=.0294), genitourinary complications (OR 2.15, p=.0091), infection (OR 3.48, p<.0001), neurologic complications (OR 1.69, p=.0422), total charges (+29%, p=.0034), and inpatient hospital length of stay (LOS) (+16%, p=.0012). The likelihood of complications at state-owned hospitals (OR 2.81, p=.0001) was more highly associated with HHI than at private, non-profit hospitals (OR 1.39, p=.0050). The occurrence of complications at urban teaching hospitals (OR 2.14, p<.0001) was generally more associated with HHI than at urban non-teaching hospitals (OR 1.19, p=.2457). Increased interhospital competitive intensity is associated with increased odds of complications, increased total charges, and prolonged LOS following lumbar spine fusion. These differences are generally highest among state-owned and urban teaching hospitals. Differences in outcome related to hospital competition may be due to suboptimal resource allocation. Identifying differences in perioperative outcomes associated with hospital market competition is important in the contemporary environment of health care reimbursement reform and hospital consolidation. Perioperative outcome disparities between highly competitive and minimally competitive areas should be monitored and further studied. Copyright © 2017 Elsevier Inc. All rights reserved.

The role and application of ion beam analysis for studies of plasma-facing components in controlled fusion devices

NASA Astrophysics Data System (ADS)

Rubel, Marek; Petersson, Per; Alves, Eduardo; Brezinsek, Sebastijan; Coad, Joseph Paul; Heinola, Kalle; Mayer, Matej; Widdowson, Anna

2016-03-01

First wall materials in controlled fusion devices undergo serious modification by several physical and chemical processes arising from plasma-wall interactions. Detailed information is required for the assessment of material lifetime and accumulation of hydrogen isotopes in wall materials. The intention of this work is to give a concise overview of key issues in the characterization of plasma-facing materials and components in tokamaks, especially in JET with an ITER-Like Wall. IBA techniques play a particularly prominent role here because of their isotope selectivity in the low-Z range (1-10), high sensitivity and combination of several methods in a single run. The role of 3He-based NRA, RBS (standard and micro-size beam) and HIERDA in fuel retention and material migration studies is presented. The use of tracer techniques with rare isotopes (e.g. 15N) or marker layers on wall diagnostic components is described. Special instrumentation, development of equipment to enhance research capabilities and issues in handling of contaminated materials are addressed.

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy

PubMed Central

Lim, Daryl; Ford, Tim N.; Chu, Kengyeh K.; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish. PMID:21280920

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy.

PubMed

Lim, Daryl; Ford, Tim N; Chu, Kengyeh K; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish.

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy

NASA Astrophysics Data System (ADS)

Lim, Daryl; Ford, Tim N.; Chu, Kengyeh K.; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish.

In situ strain and temperature measurement and modelling during arc welding

DOE PAGES

Chen, Jian; Yu, Xinghua; Miller, Roger G.; ...

2014-12-26

In this study, experiments and numerical models were applied to investigate the thermal and mechanical behaviours of materials adjacent to the weld pool during arc welding. In the experiment, a new high temperature strain measurement technique based on digital image correlation (DIC) was developed and applied to measure the in situ strain evolution. In contrast to the conventional DIC method that is vulnerable to the high temperature and intense arc light involved in fusion welding processes, the new technique utilised a special surface preparation method to produce high temperature sustaining speckle patterns required by the DIC algorithm as well asmore » a unique optical illumination and filtering system to suppress the influence of the intense arc light. These efforts made it possible for the first time to measure in situ the strain field 1 mm away from the fusion line. The temperature evolution in the weld and the adjacent regions was simultaneously monitored by an infrared camera. Finally and additionally, a thermal–mechanical finite element model was applied to substantiate the experimental measurement.« less

Observer for a thick layer of solid deuterium-tritium using backlit optical shadowgraphy and interferometry.

PubMed

Choux, Alexandre; Busvelle, Eric; Gauthier, Jean Paul; Pascal, Ghislain

2007-11-20

Our work is in the context of the French "laser mégajoule" project, about fusion by inertial confinement. The project leads to the problem of characterizing the inner surface, of the approximately spherical target, by optical shadowgraphy techniques. Our work is entirely based on the basic idea that optical shadowgraphy produces "caustics" of systems of optical rays, which contain a great deal of 3D information about the surface to be characterized. We develop a method of 3D reconstruction based upon this idea plus a "small perturbations" technique. Although computations are made in the special "spherical" case, the method is in fact general and may be extended to several other situations.

Development of Long-Pulse Heating and Current Drive Actuators and Operational Techniques Compatible with a High-Z Divertor and First Wall

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

Wang, Guiding

Accurate measurement of the edge electron density profile is essential to optimizing antenna coupling and assessment of impurity contamination in studying long-pulse plasma heating and current drive in fusion devices. Measurement of the edge density profile has been demonstrated on the US fusion devices such as C-Mod, DIII-D, and TFTR amongst many devices, and has been used for RF loading and impurity modeling calculations for many years. University of Science and Technology of China (USTC) has recently installed a density profile reflectometer system on the EAST fusion device at the Institute of Plasma Physics, Chinese Academy of Sciences in Chinamore » based on the University of California Los Angeles (UCLA)-designed reflectometer system on the DIII-D fusion device at General Atomics Company in San Diego, California. UCLA has been working with USTC to optimize the existing microwave antenna, waveguide system, microwave electronics, and data analysis to produce reliable edge density profiles. During the past budget year, progress has been made in all three major areas: effort to achieve reliable system operations under various EAST operational conditions, effort to optimize system performance, and effort to provide quality density profiles into EAST’s database routinely.« less

Enhancement of low light level images using color-plus-mono dual camera.

PubMed

Jung, Yong Ju

2017-05-15

In digital photography, the improvement of imaging quality in low light shooting is one of the users' needs. Unfortunately, conventional smartphone cameras that use a single, small image sensor cannot provide satisfactory quality in low light level images. A color-plus-mono dual camera that consists of two horizontally separate image sensors, which simultaneously captures both a color and mono image pair of the same scene, could be useful for improving the quality of low light level images. However, an incorrect image fusion between the color and mono image pair could also have negative effects, such as the introduction of severe visual artifacts in the fused images. This paper proposes a selective image fusion technique that applies an adaptive guided filter-based denoising and selective detail transfer to only those pixels deemed reliable with respect to binocular image fusion. We employ a dissimilarity measure and binocular just-noticeable-difference (BJND) analysis to identify unreliable pixels that are likely to cause visual artifacts during image fusion via joint color image denoising and detail transfer from the mono image. By constructing an experimental system of color-plus-mono camera, we demonstrate that the BJND-aware denoising and selective detail transfer is helpful in improving the image quality during low light shooting.

A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

On the enhancement of p-11B fusion reaction rate in laser-driven plasma by α → p collisional energy transfer

NASA Astrophysics Data System (ADS)

Belloni, Fabio; Margarone, Daniele; Picciotto, Antonino; Schillaci, Francesco; Giuffrida, Lorenzo

2018-02-01

The possibility of triggering an avalanche reaction in laser-driven p-11B fusion by the effect of collisional energy transfer from α particles to protons has recently been debated, especially in connection to the high yield of α particles (4 × 108 per laser shot) achieved on engineered targets at the Prague Asterix Laser System (PALS), with a pulse of 500 J, 0.3 ns FWHM. We elucidate this controversial subject within the framework of a simple two-population model for protons, based on the binary collision theory in a plasma. We find an avalanche characteristic time of almost 1 μs for the 675 keV fusion cross section resonance in typical PALS plasma, upon idealized confinement conditions. This avalanche time is one order of magnitude higher than previously reported, meaning that no such process can substantially develop in plasma at the PALS on the 675 keV resonance, not even in the most optimistic confinement scenarios. Nevertheless, we put forward for further investigation that more realistic conditions for setting up the avalanche regime could rather be attained by suitably targeting the narrow 163 keV resonance in the fusion cross section, also in connection to recently proposed laser-driven magnetic trapping techniques.

Viral fusion efficacy of specific H3N2 influenza virus reassortant combinations at single-particle level

NASA Astrophysics Data System (ADS)

Hsu, Hung-Lun; Millet, Jean K.; Costello, Deirdre A.; Whittaker, Gary R.; Daniel, Susan

2016-10-01

Virus pseudotyping is a useful and safe technique for studying entry of emerging strains of influenza virus. However, few studies have compared different reassortant combinations in pseudoparticle systems, or compared entry kinetics of native viruses and their pseudotyped analogs. Here, vesicular stomatitis virus (VSV)-based pseudovirions displaying distinct influenza virus envelope proteins were tested for fusion activity. We produced VSV pseudotypes containing the prototypical X-31 (H3) HA, either alone or with strain-matched or mismatched N2 NAs. We performed single-particle fusion assays using total internal reflection fluorescence microscopy to compare hemifusion kinetics among these pairings. Results illustrate that matching pseudoparticles behaved very similarly to native virus. Pseudoparticles harboring mismatched HA-NA pairings fuse at significantly slower rates than native virus, and NA-lacking pseudoparticles exhibiting the slowest fusion rates. Relative viral membrane HA density of matching pseudoparticles was higher than in mismatching or NA-lacking pseudoparticles. An equivalent trend of HA expression level on cell membranes of HA/NA co-transfected cells was observed and intracellular trafficking of HA was affected by NA co-expression. Overall, we show that specific influenza HA-NA combinations can profoundly affect the critical role played by HA during entry, which may factor into viral fitness and the emergence of new pandemic influenza viruses.

Segregation and transmission of mitochondrial markers in fusion products of the asporogenous yeast Torulopsis glabrata.

PubMed

Sriprakash, K S; Batum, C

1981-09-01

Using a protoplast fusion technique we have been able to locate to the mitochondrial genome of the asporogenous yeast Torulopsis glabrata mutations conferring resistance to oligomycin, antimycin and diuron. When two strains differing in the size of their mtDNAs were fused the mitochondrial markers from the parent with the larger mtDNA (71-91) were transmitted predominantly among the fusion products. Both genetical and physical evidence support the occurrence of recombination in T. glabrata mitochondrial genome. Segregation of the mitochondrial genome appears to take place before the separation of the first bud from the fusion product.

Visualization of conserved structures by fusing highly variable datasets.

PubMed

Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

2002-01-01

Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual Reality (VR) environment. The accuracy of the fusions was determined qualitatively by comparing the transformed atlas overlaid on the appropriate CT. It was examined for where the transformed structure atlas was incorrectly overlaid (false positive) and where it was incorrectly not overlaid (false negative). According to this method, fusions 1 and 2 were correct roughly 50-75% of the time, while fusions 3 and 4 were correct roughly 75-100%. The CT dataset augmented with transformed dataset was viewed arbitrarily in user-centered perspective stereo taking advantage of features such as scaling, windowing and volumetric region of interest selection. This process of auto-coloring conserved structures in variable datasets is a step toward the goal of a broader, standardized automatic structure visualization method for radiological data. If successful it would permit identification, visualization or deletion of structures in radiological data by semi-automatically applying canonical structure information to the radiological data (not just processing and visualization of the data's intrinsic dynamic range). More sophisticated selection of control points and patterns of warping may allow for more accurate transforms, and thus advances in visualization, simulation, education, diagnostics, and treatment planning.

SU-G-BRB-01: A Novel 3D Printed Patient-Specific Phantom for Spine SBRT Quality Assurance: Comparison of 3D Printing Techniques

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

Lee, S; Kim, M; Lee, M

Purpose: The novel 3 dimensional (3D)-printed spine quality assurance (QA) phantoms generated by two different 3D-printing technologies, digital light processing (DLP) and Polyjet, were developed and evaluated for spine stereotactic body radiation treatment (SBRT). Methods: The developed 3D-printed spine QA phantom consisted of an acrylic body and a 3D-printed spine phantom. DLP and Polyjet 3D printers using the high-density acrylic polymer were employed to produce spine-shaped phantoms based on CT images. To verify dosimetric effects, the novel phantom was made it enable to insert films between each slabs of acrylic body phantom. Also, for measuring internal dose of spine, 3D-printedmore » spine phantom was designed as divided laterally exactly in half. Image fusion was performed to evaluate the reproducibility of our phantom, and the Hounsfield unit (HU) was measured based on each CT image. Intensity-modulated radiotherapy plans to deliver a fraction of a 16 Gy dose to a planning target volume (PTV) based on the two 3D-printing techniques were compared for target coverage and normal organ-sparing. Results: Image fusion demonstrated good reproducibility of the fabricated spine QA phantom. The HU values of the DLP- and Polyjet-printed spine vertebrae differed by 54.3 on average. The PTV Dmax dose for the DLP-generated phantom was about 1.488 Gy higher than for the Polyjet-generated phantom. The organs at risk received a lower dose when the DLP technique was used than when the Polyjet technique was used. Conclusion: This study confirmed that a novel 3D-printed phantom mimicking a high-density organ can be created based on CT images, and that a developed 3D-printed spine phantom could be utilized in patient-specific QA for SBRT. Despite using the same main material, DLP and Polyjet yielded different HU values. Therefore, the printing technique and materials must be carefully chosen in order to accurately produce a patient-specific QA phantom.« less

High-performance fused indium gallium arsenide/silicon photodiode

NASA Astrophysics Data System (ADS)

Kang, Yimin

Modern long haul, high bit rate fiber-optic communication systems demand photodetectors with high sensitivity. Avalanche photodiodes (APDs) exhibit superior sensitivity performance than other types of photodetectors by virtual of its internal gain mechanism. This dissertation work further advances the APD performance by applying a novel materials integration technique. It is the first successful demonstration of wafer fused InGaAs/Si APDs with low dark current and low noise. APDs generally adopt separate absorption and multiplication (SAM) structure, which allows independent optimization of materials properties in two distinct regions. While the absorption material needs to have high absorption coefficient in the target wavelength range to achieve high quantum efficiency, it is desirable for the multiplication material to have large discrepancy between its electron and hole ionization coefficients to reduce noise. According to these criteria, InGaAs and Si are the ideal materials combination. Wafer fusion is the enabling technique that makes this theoretical ideal an experimental possibility. APDs fabricated on the fused InGaAs/Si wafer with mesa structure exhibit low dark current and low noise. Special device fabrication techniques and high quality wafer fusion reduce dark current to nano ampere level at unity gain, comparable to state-of-the-art commercial III/V APDs. The small excess noise is attributed to the large difference in ionization coefficients between electrons and holes in silicon. Detailed layer structure designs are developed specifically for fused InGaAs/Si APDs based on principles similar to those used in traditional InGaAs/InP APDs. An accurate yet straightforward technique for device structural parameters extraction is also proposed. The extracted results from the fabricated APDs agree with device design parameters. This agreement also confirms that the fusion interface has negligible effect on electric field distributions for devices fabricated from high quality fusion materials. The feasibility of fused InGaAs/Si APD for analog systems is also explored. Preliminary two-tone measurement shows that a moderately high dynamic range of 70 dBc/Hz1/2 for broadband Spur Free Dynamic Range (SFDR) or 82 dBc/Hz2/3 suboctave SFDR, up to 50 muA of optical current, can be achieved. The theoretical analyses of SNR show that fused InGaAs/Si APD receivers can provide larger Signal-to-Noise Ratio (SNR) than their III/V counterparts.

A new deflection technique applied to an existing scheme of electrostatic accelerator for high energy neutral beam injection in fusion reactor devices

NASA Astrophysics Data System (ADS)

Pilan, N.; Antoni, V.; De Lorenzi, A.; Chitarin, G.; Veltri, P.; Sartori, E.

2016-02-01

A scheme of a neutral beam injector (NBI), based on electrostatic acceleration and magneto-static deflection of negative ions, is proposed and analyzed in terms of feasibility and performance. The scheme is based on the deflection of a high energy (2 MeV) and high current (some tens of amperes) negative ion beam by a large magnetic deflector placed between the Beam Source (BS) and the neutralizer. This scheme has the potential of solving two key issues, which at present limit the applicability of a NBI to a fusion reactor: the maximum achievable acceleration voltage and the direct exposure of the BS to the flux of neutrons and radiation coming from the fusion reactor. In order to solve these two issues, a magnetic deflector is proposed to screen the BS from direct exposure to radiation and neutrons so that the voltage insulation between the electrostatic accelerator and the grounded vessel can be enhanced by using compressed SF6 instead of vacuum so that the negative ions can be accelerated at energies higher than 1 MeV. By solving the beam transport with different magnetic deflector properties, an optimum scheme has been found which is shown to be effective to guarantee both the steering effect and the beam aiming.

A new deflection technique applied to an existing scheme of electrostatic accelerator for high energy neutral beam injection in fusion reactor devices.

PubMed

Pilan, N; Antoni, V; De Lorenzi, A; Chitarin, G; Veltri, P; Sartori, E

2016-02-01

A scheme of a neutral beam injector (NBI), based on electrostatic acceleration and magneto-static deflection of negative ions, is proposed and analyzed in terms of feasibility and performance. The scheme is based on the deflection of a high energy (2 MeV) and high current (some tens of amperes) negative ion beam by a large magnetic deflector placed between the Beam Source (BS) and the neutralizer. This scheme has the potential of solving two key issues, which at present limit the applicability of a NBI to a fusion reactor: the maximum achievable acceleration voltage and the direct exposure of the BS to the flux of neutrons and radiation coming from the fusion reactor. In order to solve these two issues, a magnetic deflector is proposed to screen the BS from direct exposure to radiation and neutrons so that the voltage insulation between the electrostatic accelerator and the grounded vessel can be enhanced by using compressed SF6 instead of vacuum so that the negative ions can be accelerated at energies higher than 1 MeV. By solving the beam transport with different magnetic deflector properties, an optimum scheme has been found which is shown to be effective to guarantee both the steering effect and the beam aiming.

Information fusion performance evaluation for motion imagery data using mutual information: initial study

NASA Astrophysics Data System (ADS)

Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik

2015-06-01

As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

Noncontact Sleep Study by Multi-Modal Sensor Fusion.

PubMed

Chung, Ku-Young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-07-21

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

PubMed Central

Chung, Ku-young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-01-01

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. PMID:28753994

Feature level fusion for enhanced geological mapping of ophiolile complex using ASTER and Landsat TM data

NASA Astrophysics Data System (ADS)

Pournamdari, M.; Hashim, M.

2014-02-01

Chromite ore deposit occurrence is related to ophiolite complexes as a part of the oceanic crust and provides a good opportunity for lithological mapping using remote sensing data. The main contribution of this paper is a novel approaches to discriminate different rock units associated with ophiolite complex using the Feature Level Fusion technique on ASTER and Landsat TM satellite data at regional scale. In addition this study has applied spectral transform approaches, consisting of Spectral Angle Mapper (SAM) to distinguish the concentration of high-potential areas of chromite and also for determining the boundary between different rock units. Results indicated both approaches show superior outputs compared to other methods and can produce a geological map for ophiolite complex rock units in the arid and the semi-arid region. The novel technique including feature level fusion and Spectral Angle Mapper (SAM) discriminated ophiolitic rock units and produced detailed geological maps of the study area. As a case study, Sikhoran ophiolite complex located in SE, Iran has been selected for image processing techniques. In conclusion, a suitable approach for lithological mapping of ophiolite complexes is demonstrated, this technique contributes meaningfully towards economic geology in terms of identifying new prospects.

Application of data fusion techniques and technologies for wearable health monitoring.

PubMed

King, Rachel C; Villeneuve, Emma; White, Ruth J; Sherratt, R Simon; Holderbaum, William; Harwin, William S

2017-04-01

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market. Copyright © 2017. Published by Elsevier Ltd.

Four-corner fusion: comparison of patient satisfaction and functional outcome of conventional K-wire technique vs. a new locking plate.

PubMed

Hernekamp, J F; Reinecke, A; Neubrech, F; Bickert, B; Kneser, U; Kremer, T

2016-04-01

Four-corner fusion is a standard procedure for advanced carpal collapse. Several operative techniques and numerous implants for osseous fixation have been described. Recently, a specially designed locking plate (Aptus©, Medartis, Basel, Switzerland) was introduced. The purpose of this study was to compare functional results after osseous fixation using K-wires (standard of care, SOC) with four-corner fusion and locking plate fixation. 21 patients who underwent four-corner fusion in our institution between 2008 and 2013 were included in a retrospective analysis. In 11 patients, osseous fixation was performed using locking plates whereas ten patients underwent bone fixation with conventional K-wires. Outcome parameters were functional outcome, osseous consolidation, patient satisfaction (DASH- and Krimmer Score), pain and perioperative morbidity and the time until patients returned to daily work. Patients were divided in two groups and paired t-tests were performed for statistical analysis. No implant related complications were observed. Osseous consolidation was achieved in all cases. Differences between groups were not significant regarding active range of motion (AROM), pain and function. Overall patient satisfaction was acceptable in all cases; differences in the DASH questionnaire and the Krimmer questionnaire were not significant. One patient of the plate group required conversion to total wrist arthrodesis without implant-related complications. Both techniques for four-corner fusion have similar healing rates. Using the more expensive locking implant avoids a second operation for K-wire removal, but no statistical differences were detected in functional outcome as well as in patient satisfaction when compared to SOC.

Computation of Hemagglutinin Free Energy Difference by the Confinement Method

PubMed Central

2017-01-01

Hemagglutinin (HA) mediates membrane fusion, a crucial step during influenza virus cell entry. How many HAs are needed for this process is still subject to debate. To aid in this discussion, the confinement free energy method was used to calculate the conformational free energy difference between the extended intermediate and postfusion state of HA. Special care was taken to comply with the general guidelines for free energy calculations, thereby obtaining convergence and demonstrating reliability of the results. The energy that one HA trimer contributes to fusion was found to be 34.2 ± 3.4kBT, similar to the known contributions from other fusion proteins. Although computationally expensive, the technique used is a promising tool for the further energetic characterization of fusion protein mechanisms. Knowledge of the energetic contributions per protein, and of conserved residues that are crucial for fusion, aids in the development of fusion inhibitors for antiviral drugs. PMID:29151344

[Detection of bcr/abl fusion gene and its derivative chromosome 9 deletions in CML by using home-made bcr/abl extra-signal probe].

PubMed

Lai, Yue-Yun; Feng, Lin; Wang, Zheng; Lü, Shan; Dang, Hui; Shi, Yan; He, Qi; Huang, Xiao-Jun

2010-02-01

This study was aimed to verify the efficacy of home-made LSI bcr/abl ES probe for detection of bcr/abl fusion gene and derivative chromosome 9 deletions in chronic myeloid leukemia (CML). Fluorescence in situ hybridization (FISH) was carried out with dual color bcr/abl extra signal (ES) probe in 97 cases of CML based on morphology and cytogenetic karyotype and 129 cases of non-hematological malignancies/non-myeloproliferative diseases with normal cytogenetic karyotype. For the patients with signals of 1R1G1F indicating der(9) deletions, FISH were done using ASS DNA probe. The results showed that 91 cases with standard t(9;22) and 6 cases with variant translocation of t(9;22) were detected by conventional G banding technique. All of the 97 patients displayed bcr/abl fusion gene by ES-FISH, including 16 cases with signal patterns of 1R1G1F showing der(9) deletions. Among the 16 cases with der(9) deletions, 13 cases were detected to have deletions of ASS gene. Meanwhile, none of the 129 cases of negative control showed bcr/abl fusion gene by ES-FISH. It is concluded that home-made LSI bcr/abl ES probe is effective to identify the bcr/abl fusion gene and der(9) deletions in CML, and the ES-FISH results are consistent with conventional cytogenetic karyotype.

A color fusion method of infrared and low-light-level images based on visual perception

NASA Astrophysics Data System (ADS)

Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

2014-11-01

The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.

Face-iris multimodal biometric scheme based on feature level fusion

NASA Astrophysics Data System (ADS)

Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

2015-11-01

Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

Characterization of 3D printing techniques: Toward patient specific quality assurance spine-shaped phantom for stereotactic body radiation therapy.

PubMed

Kim, Min-Joo; Lee, Seu-Ran; Lee, Min-Young; Sohn, Jason W; Yun, Hyong Geon; Choi, Joon Yong; Jeon, Sang Won; Suh, Tae Suk

2017-01-01

Development and comparison of spine-shaped phantoms generated by two different 3D-printing technologies, digital light processing (DLP) and Polyjet has been purposed to utilize in patient-specific quality assurance (QA) of stereotactic body radiation treatment. The developed 3D-printed spine QA phantom consisted of an acrylic body phantom and a 3D-printed spine shaped object. DLP and Polyjet 3D printers using a high-density acrylic polymer were employed to produce spine-shaped phantoms based on CT images. Image fusion was performed to evaluate the reproducibility of our phantom, and the Hounsfield units (HUs) were measured based on each CT image. Two different intensity-modulated radiotherapy plans based on both CT phantom image sets from the two printed spine-shaped phantoms with acrylic body phantoms were designed to deliver 16 Gy dose to the planning target volume (PTV) and were compared for target coverage and normal organ-sparing. Image fusion demonstrated good reproducibility of the developed phantom. The HU values of the DLP- and Polyjet-printed spine vertebrae differed by 54.3 on average. The PTV Dmax dose for the DLP-generated phantom was about 1.488 Gy higher than that for the Polyjet-generated phantom. The organs at risk received a lower dose for the 3D printed spine-shaped phantom image using the DLP technique than for the phantom image using the Polyjet technique. Despite using the same material for printing the spine-shaped phantom, these phantoms generated by different 3D printing techniques, DLP and Polyjet, showed different HU values and these differently appearing HU values according to the printing technique could be an extra consideration for developing the 3D printed spine-shaped phantom depending on the patient's age and the density of the spinal bone. Therefore, the 3D printing technique and materials should be carefully chosen by taking into account the condition of the patient in order to accurately produce 3D printed patient-specific QA phantom.

Characterization of 3D printing techniques: Toward patient specific quality assurance spine-shaped phantom for stereotactic body radiation therapy

PubMed Central

Lee, Min-Young; Sohn, Jason W.; Yun, Hyong Geon; Choi, Joon Yong; Jeon, Sang Won

2017-01-01

Development and comparison of spine-shaped phantoms generated by two different 3D-printing technologies, digital light processing (DLP) and Polyjet has been purposed to utilize in patient-specific quality assurance (QA) of stereotactic body radiation treatment. The developed 3D-printed spine QA phantom consisted of an acrylic body phantom and a 3D-printed spine shaped object. DLP and Polyjet 3D printers using a high-density acrylic polymer were employed to produce spine-shaped phantoms based on CT images. Image fusion was performed to evaluate the reproducibility of our phantom, and the Hounsfield units (HUs) were measured based on each CT image. Two different intensity-modulated radiotherapy plans based on both CT phantom image sets from the two printed spine-shaped phantoms with acrylic body phantoms were designed to deliver 16 Gy dose to the planning target volume (PTV) and were compared for target coverage and normal organ-sparing. Image fusion demonstrated good reproducibility of the developed phantom. The HU values of the DLP- and Polyjet-printed spine vertebrae differed by 54.3 on average. The PTV Dmax dose for the DLP-generated phantom was about 1.488 Gy higher than that for the Polyjet-generated phantom. The organs at risk received a lower dose for the 3D printed spine-shaped phantom image using the DLP technique than for the phantom image using the Polyjet technique. Despite using the same material for printing the spine-shaped phantom, these phantoms generated by different 3D printing techniques, DLP and Polyjet, showed different HU values and these differently appearing HU values according to the printing technique could be an extra consideration for developing the 3D printed spine-shaped phantom depending on the patient’s age and the density of the spinal bone. Therefore, the 3D printing technique and materials should be carefully chosen by taking into account the condition of the patient in order to accurately produce 3D printed patient-specific QA phantom. PMID:28472175

Fusion or confusion: knowledge or nonsense?

NASA Astrophysics Data System (ADS)

Rothman, Peter L.; Denton, Richard V.

1991-08-01

The terms 'data fusion,' 'sensor fusion,' multi-sensor integration,' and 'multi-source integration' have been used widely in the technical literature to refer to a variety of techniques, technologies, systems, and applications which employ and/or combine data derived from multiple information sources. Applications of data fusion range from real-time fusion of sensor information for the navigation of mobile robots to the off-line fusion of both human and technical strategic intelligence data. The Department of Defense Critical Technologies Plan lists data fusion in the highest priority group of critical technologies, but just what is data fusion? The DoD Critical Technologies Plan states that data fusion involves 'the acquisition, integration, filtering, correlation, and synthesis of useful data from diverse sources for the purposes of situation/environment assessment, planning, detecting, verifying, diagnosing problems, aiding tactical and strategic decisions, and improving system performance and utility.' More simply states, sensor fusion refers to the combination of data from multiple sources to provide enhanced information quality and availability over that which is available from any individual source alone. This paper presents a survey of the state-of-the- art in data fusion technologies, system components, and applications. A set of characteristics which can be utilized to classify data fusion systems is presented. Additionally, a unifying mathematical and conceptual framework within which to understand and organize fusion technologies is described. A discussion of often overlooked issues in the development of sensor fusion systems is also presented.

Optical Design And Analysis Of Carbon Dioxide Laser Fusion Systems Using Interferometry And Fast Fourier Transform Techniques

NASA Astrophysics Data System (ADS)

Viswanathan, V. K.

1980-11-01

The optical design and analysis of the LASL carbon dioxide laser fusion systems required the use of techniques that are quite different from the currently used method in conventional optical design problems. The necessity for this is explored and the method that has been successfully used at Los Alamos to understand these systems is discussed with examples. This method involves characterization of the various optical components in their mounts by a Zernike polynomial set and using fast Fourier transform techniques to propagate the beam, taking diffraction and other nonlinear effects that occur in these types of systems into account. The various programs used for analysis are briefly discussed.

A Ratiometric Two-Photon Fluorescent Probe for Tracking the Lysosomal ATP Level: Direct in cellulo Observation of Lysosomal Membrane Fusion Processes.

PubMed

Jun, Yong Woong; Wang, Taejun; Hwang, Sekyu; Kim, Dokyoung; Ma, Donghee; Kim, Ki Hean; Kim, Sungjee; Jung, Junyang; Ahn, Kyo Han

2018-06-05

Vesicles exchange its contents through membrane fusion processes-kiss-and-run and full-collapse fusion. Indirect observation of these fusion processes using artificial vesicles enhanced our understanding on the molecular mechanisms involved. Direct observation of the fusion processes in a real biological system, however, remains a challenge owing to many technical obstacles. We disclose a ratiometric two-photon probe offering real-time tracking of lysosomal ATP with quantitative information for the first time. By applying the probe to two-photon live-cell imaging technique, lysosomal membrane fusion process in cells has been directly observed along with the concentration of its content-lysosomal ATP. Results show that the kiss-and-run process between lysosomes proceeds through repeating transient interactions with gradual content mixing, whereas the full-fusion process occurs at once. Furthermore, it is confirmed that both the fusion processes proceed with conservation of the content. Such a small-molecule probe exerts minimal disturbance and hence has potential for studying various biological processes associated with lysosomal ATP. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

PubMed

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer.

PubMed

Panigrahi, Priyabrata; Jere, Abhay; Anamika, Krishanpal

2018-01-01

Gene fusion is a chromosomal rearrangement event which plays a significant role in cancer due to the oncogenic potential of the chimeric protein generated through fusions. At present many databases are available in public domain which provides detailed information about known gene fusion events and their functional role. Existing gene fusion detection tools, based on analysis of transcriptomics data usually report a large number of fusion genes as potential candidates, which could be either known or novel or false positives. Manual annotation of these putative genes is indeed time-consuming. We have developed a web platform FusionHub, which acts as integrated search engine interfacing various fusion gene databases and simplifies large scale annotation of fusion genes in a seamless way. In addition, FusionHub provides three ways of visualizing fusion events: circular view, domain architecture view and network view. Design of potential siRNA molecules through ensemble method is another utility integrated in FusionHub that could aid in siRNA-based targeted therapy. FusionHub is freely available at https://fusionhub.persistent.co.in.

Condylar Joint Fusion and Stabilization (by Screws and Plates) in Nontraumatic Atlanto-Occipital Dislocation: Technical Report of 2 Cases.

PubMed

Chowdhury, Forhad H; Haque, Mohammod Raziul; Alam, Sarwar Murshed; Khaled Chowdhury, S M Noman; Khan, Shamsul Islam; Goel, Atul

2017-11-01

Nontraumatic spontaneous atlanto-occipital dislocation (AOD) is rare. In this report, we discuss the technical steps of condylar joint fusion and stabilization (by screws and plates) in nontraumatic AOD. To the best of our knowledge, it is the first report of such techniques. A young girl and a young man with progressive quadriparesis due to nontraumatic spontaneous atlanto-occipital dislocation were managed by microsurgical reduction, fusion, and stabilization of the joint by occipital condylar and C1 lateral mass screw and plate fixation after mobilization of vertebral artery. In both cases, condylar joints fixation and fusion were done successfully. Condylar joint stabilization and fusion may be a good or alternative option for AOD. Copyright © 2017 Elsevier Inc. All rights reserved.

Statistical sensor fusion analysis of near-IR polarimetric and thermal imagery for the detection of minelike targets

NASA Astrophysics Data System (ADS)

Weisenseel, Robert A.; Karl, William C.; Castanon, David A.; DiMarzio, Charles A.

1999-02-01

We present an analysis of statistical model based data-level fusion for near-IR polarimetric and thermal data, particularly for the detection of mines and mine-like targets. Typical detection-level data fusion methods, approaches that fuse detections from individual sensors rather than fusing at the level of the raw data, do not account rationally for the relative reliability of different sensors, nor the redundancy often inherent in multiple sensors. Representative examples of such detection-level techniques include logical AND/OR operations on detections from individual sensors and majority vote methods. In this work, we exploit a statistical data model for the detection of mines and mine-like targets to compare and fuse multiple sensor channels. Our purpose is to quantify the amount of knowledge that each polarimetric or thermal channel supplies to the detection process. With this information, we can make reasonable decisions about the usefulness of each channel. We can use this information to improve the detection process, or we can use it to reduce the number of required channels.

Expression of human peroxisome proliferator-activated receptors ligand binding domain-maltose binding protein fusion protein in Escherichia coli: a convenient and reliable method for preparing receptor for screening ligands.

PubMed

Li, Changqing; Tian, Mi; Yuan, Ye; Zhou, Qinxin

2008-12-01

Human peroxisome proliferator-activated receptors (hPPARs) are ligand-activated transcription factors and are the target for the treatment of many diseases. Screening of their ligands is mainly based on assays of ligand binding to the ligand binding domain (LBD) of hPPARs.However, such assays are difficult because of the preparation of hPPARs LBD. In order to yield functional hPPARs LBD for screening ligands, hPPARs LBD was fused with maltose-binding protein(MBP) using the pMAL-p2x expression system through the gene engineering technique. The radioligand binding assay showed that MBP did not affect ligand binding with hPPARs LBD in the fusion proteins, which means that MBP-hPPARs LBD can be used instead of hPPARs LBD in ligand screening work. The results show that the new strategy using MBP as a fusion tag for preparing hPPARs LBD for screening ligands is a convenient and reliable method. It may be used to easily obtain the other nuclear receptors.

Enhanced image fusion using directional contrast rules in fuzzy transform domain.

PubMed

Nandal, Amita; Rosales, Hamurabi Gamboa

2016-01-01

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.

Comparison of clinical outcomes in decompression and fusion versus decompression only in patients with ossification of the posterior longitudinal ligament: a meta-analysis.

PubMed

Mehdi, Syed K; Alentado, Vincent J; Lee, Bryan S; Mroz, Thomas E; Benzel, Edward C; Steinmetz, Michael P

2016-06-01

OBJECTIVE Ossification of the posterior longitudinal ligament (OPLL) is a pathological calcification or ossification of the PLL, predominantly occurring in the cervical spine. Although surgery is often necessary for patients with symptomatic neurological deterioration, there remains controversy with regard to the optimal surgical treatment. In this systematic review and meta-analysis, the authors identified differences in complications and outcomes after anterior or posterior decompression and fusion versus after decompression alone for the treatment of cervical myelopathy due to OPLL. METHODS A MEDLINE, SCOPUS, and Web of Science search was performed for studies reporting complications and outcomes after decompression and fusion or after decompression alone for patients with OPLL. A meta-analysis was performed to calculate effect summary mean values, 95% CIs, Q statistics, and I(2) values. Forest plots were constructed for each analysis group. RESULTS Of the 2630 retrieved articles, 32 met the inclusion criteria. There was no statistically significant difference in the incidence of excellent and good outcomes and of fair and poor outcomes between the decompression and fusion and the decompression-only cohorts. However, the decompression and fusion cohort had a statistically significantly higher recovery rate (63.2% vs 53.9%; p < 0.0001), a higher final Japanese Orthopaedic Association score (14.0 vs 13.5; p < 0.0001), and a lower incidence of OPLL progression (< 1% vs 6.3%; p < 0.0001) compared with the decompression-only cohort. There was no statistically significant difference in the incidence of complications between the 2 cohorts. CONCLUSIONS This study represents the only comprehensive review of outcomes and complications after decompression and fusion or after decompression alone for OPLL across a heterogeneous group of surgeons and patients. Based on these results, decompression and fusion is a superior surgical technique compared with posterior decompression alone in patients with OPLL. These results indicate that surgical decompression and fusion lead to a faster recovery, improved postoperative neurological functioning, and a lower incidence of OPLL progression compared with posterior decompression only. Furthermore, decompression and fusion did not lead to a greater incidence of complications compared with posterior decompression only.

Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Sensor fusion for synthetic vision

NASA Technical Reports Server (NTRS)

Pavel, M.; Larimer, J.; Ahumada, A.

1991-01-01

Display methodologies are explored for fusing images gathered by millimeter wave sensors with images rendered from an on-board terrain data base to facilitate visually guided flight and ground operations in low visibility conditions. An approach to fusion based on multiresolution image representation and processing is described which facilitates fusion of images differing in resolution within and between images. To investigate possible fusion methods, a workstation-based simulation environment is being developed.

A protocol of a randomized controlled multicenter trial for surgical treatment of lumbar spondylolisthesis: the Lumbar Interbody Fusion Trial (LIFT).

PubMed

de Kunder, Suzanne L; Rijkers, Kim; van Kuijk, Sander M J; Evers, Silvia M A A; de Bie, Rob A; van Santbrink, Henk

2016-10-06

With a steep increase in the number of instrumented spinal fusion procedures, there is a need for comparative data to develop evidence based treatment recommendations. Currently, the available data on cost and clinical effectiveness of the two most frequently performed surgeries for lumbar spondylolisthesis, transforaminal lumbar interbody fusion (TLIF) and posterior lumbar interbody fusion (PLIF), are not sufficient. Therefore, current guidelines do not advise which is the most appropriate surgical treatment strategy for these patients. Non-randomized studies comparing TLIF and PLIF moreover suggest that TLIF is associated with fewer complications, less blood loss, shorter surgical time and hospital duration. TLIF may therefore be more cost-effective. The results of this study will provide knowledge on short- and long-term clinical and economical effects of TLIF and PLIF procedures, which will lead to recommendations for treating patients with lumbar spondylolisthesis. Multicenter blinded Randomized Controlled Trial (RCT; blinding for the patient and statistician, not for the clinician and researcher). A total of 144 patients over 18 years old with symptomatic single level lumbar degenerative, isthmic or iatrogenic spondylolisthesis whom are candidates for LIF (lumbar interbody fusion) surgery through a posterior approach will be randomly allocated to TLIF or PLIF. The study will consist of three parts: 1) a clinical effectiveness study, 2) a cost-effectiveness study, and 3) a process evaluation. The primary clinical outcome measures are: change in disability measured with Oswestry Disability Index (ODI) and change in quality adjusted life years (QALY) measured with EQ-5D-5L. Secondary clinical outcome measures are: Short Form (36) Health Survey (SF-36), VAS back pain, VAS leg pain, Hospital Anxiety Depression Scale (HADS), complications, productivity related costs (iPCQ) and medical costs (iMCQ). Measurements will be carried out at five fixed time points (pre-operatively and at 3, 6, 12 and 24 months). It is hypothesized that TLIF, compared to PLIF, has similar clinical outcome or is possibly better in reducing disability. Moreover, direct medical costs are expected to be lower due to less surgical morbidity, shorter hospital stay and shorter surgical time. Indirect costs are assumed to be lower for TLIF as well, because we suspect less working days are lost. Currently, prospective data comparing clinical and cost-effectiveness of both techniques are not available. Therefore, in clinical practice both techniques are used and the choice for technique is greatly based on surgeon's preference. The demand for spinal fusion surgery has risen steeply over the last 10 years and is expected to increase even further in the near future. As a result, the burden on society (and the working population) will increase. In case our hypothesis is confirmed, treatment guidelines will be adapted, and TLIF will be recommended as first choice surgical treatment of lumbar spondylolisthesis. Ultimately this will lead to reduction of (direct and indirect) costs and better clinical outcome for spondylolisthesis patients eligible for instrumented spinal surgery. Netherlands Trial Registry, number 5722 (registration date March 30, 2016).

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

The SIGN nail for knee fusion: technique and clinical results

PubMed Central

Anderson, Duane Ray; Anderson, Lucas Aaron; Haller, Justin M.; Feyissa, Abebe Chala

2016-01-01

Purpose: Evaluate the efficacy of using the SIGN nail for instrumented knee fusion. Methods: Six consecutive patients (seven knees, three males) with an average age of 30.5 years (range, 18–50 years) underwent a knee arthrodesis with SIGN nail (mean follow-up 10.7 months; range, 8–14 months). Diagnoses included tuberculosis (two knees), congenital knee dislocation in two knees (one patient), bacterial septic arthritis (one knee), malunited spontaneous fusion (one knee), and severe gout with 90° flexion contracture (one knee). The nail was inserted through an anteromedial entry point on the femur and full weightbearing was permitted immediately. Results: All knees had clinical and radiographic evidence of fusion at final follow-up and none required further surgery. Four of six patients ambulated without assistive device, and all patients reported improved overall physical function. There were no post-operative complications. Conclusion: The technique described utilizing the SIGN nail is both safe and effective for knee arthrodesis and useful for austere environments with limited fluoroscopy and implant options. PMID:27163095