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Kaibao Sun, Rong Xue, Peng Zhang, Zhentao Zuo, Zhongwei Chen, Bo Wang, Thomas Martin, Yi Wang, Lin Chen, Sheng He, Danny J J Wang
Balanced steady-state free precession (bSSFP) offers an alternative and potentially important tool to the standard gradient-echo echo-planar imaging (GE-EPI) for functional MRI (fMRI). Both passband and transition band based bSSFP have been proposed for fMRI. The applications of these methods, however, are limited by banding artifacts due to the sensitivity of bSSFP signal to off-resonance effects. In this article, a unique case of the SSFP-FID sequence, termed integrated-SSFP or iSSFP, was proposed to overcome the obstacle by compressing the SSFP profile into the width of a single voxel...
December 30, 2016: Journal of Magnetic Resonance
Qiyu Chen, Caixia Li, Zhiyuan Gong, Eric Chun Yong Chan, Shane A Snyder, Siew Hong Lam
Synthetic glucocorticoids have been detected in environmental waters and their biological potency have raised concerns of their impact on aquatic vertebrates especially fish. In this study, developing zebrafish larvae exposed to representative glucocorticoids (dexamethasone, prednisolone and triamcinolone) at 50 pM to 50 nM from 3 h post-fertilisation to 5 days post-fertilisation were investigated. Microarray analysis identified 1255, 1531, and 2380 gene probes, which correspondingly mapped to 660, 882 and 1238 human/rodent homologs, as deregulated by dexamethasone, prednisolone and triamcinolone, respectively...
January 6, 2017: Chemosphere
Victoria Blanes-Vidal, Manuella Lech Cantuaria, Esmaeil S Nadimi
Many epidemiological studies have used proximity to sources as air pollution exposure assessment method. However, proximity measures are not generally good surrogates because of their complex non-linear relationship with exposures. Neuro-fuzzy inference systems (NFIS) can be used to map complex non-linear systems, but its usefulness in exposure assessment has not been extensively explored. We present a novel approach for exposure assessment using NFIS, where the inputs of the model were easily-obtainable proximity measures, and the output was residential exposure to an air pollutant...
January 13, 2017: Environmental Research
Sarah Wood Pallas, Jennifer Prah Ruger
Development aid for health increased dramatically during the past two decades, raising concerns about inefficiency and lack of coherence among the growing number of global health donors. However, we lack a framework for how donor proliferation affects health program performance to inform theory-based evaluation of aid effectiveness policies. A review of academic and gray literature was conducted. Data were extracted from the literature sample on study design and evidence for hypothesized effects of donor proliferation on health program performance, which were iteratively grouped into categories and mapped into a new conceptual framework...
January 4, 2017: Social Science & Medicine
Gabor Maasz, Zita Zrinyi, Peter Takacs, Sandor Lovas, Istvan Fodor, Tibor Kiss, Zsolt Pirger
In our previous study, we measured 0.23-13.67ng/L progestogens (progesterone, drospirenone, levonorgestrel) in natural waters in the catchment area of the largest shallow lake of Central Europe, Lake Balaton. Progestogen contaminations act as potent steroids with mixed progestagenic, androgenic and mild estrogenic effects that is why our aim was to investigate the morphological and molecular effects of mixture of progesterone, drospirenone, and levonorgestrel in environmentally relevant (10ng/L) and higher (50 and 500ng/L) exposure concentrations in common roach, Rutilus rutilus...
January 13, 2017: Ecotoxicology and Environmental Safety
Gilberto A Gamboa-Bernal
The Universal Declaration of Human Rights recognizes the family as the basic cell of society, highlighting its importance, the need to protect it, to promote it as a natural and fundamental group unit of society. To reflect on the effects that the actual culture is in the family is important from the situation as it is now presented, then move to raise the changes seen necessary to ensure their own future and that of their habitat that is Earth. To accomplish this first task some study results World Family Map 2015 is glossed...
September 2016: Cuadernos de Bioética: Revista Oficial de la Asociación Española de Bioética y Ética Médica
Jimmy Z Liu, Yaniv Erlich, Joseph K Pickrell
Collecting cases for case-control genetic association studies can be time-consuming and expensive. In some situations (such as studies of late-onset or rapidly lethal diseases), it may be more practical to identify family members of cases. In randomly ascertained cohorts, replacing cases with their first-degree relatives enables studies of diseases that are absent (or nearly absent) in the cohort. We refer to this approach as genome-wide association study by proxy (GWAX) and apply it to 12 common diseases in 116,196 individuals from the UK Biobank...
January 16, 2017: Nature Genetics
Deirdre M McGrath, Jenny Lee, Warren D Foltz, Navid Samavati, Theo van der Kwast, Michael A S Jewett, Peter Chung, Cynthia Ménard, Kristy K Brock
MRI is under evaluation for image-guided intervention for prostate cancer. The sensitivity and specificity of MRI parameters is determined via correlation with the gold-standard of histopathology. Whole-mount histopathology of prostatectomy specimens can be digitally registered to in vivo imaging for correlation. When biomechanical-based deformable registration is employed to account for deformation during histopathology processing, the ex vivo biomechanical properties are required. However, these properties are altered by pathology fixation, and vary with disease...
February 7, 2017: Physics in Medicine and Biology
Baiying Lei, Peng Yang, Tianfu Wang, Siping Chen, Dong Ni
Accurate identification and understanding informative feature is important for early Alzheimer's disease (AD) prognosis and diagnosis. In this paper, we propose a novel discriminative sparse learning method with relational regularization to jointly predict the clinical score and classify AD disease stages using multimodal features. Specifically, we apply a discriminative learning technique to expand the class-specific difference and include geometric information for effective feature selection. In addition, two kind of relational information are incorporated to explore the intrinsic relationships among features and training subjects in terms of similarity learning...
January 16, 2017: IEEE Transactions on Cybernetics
Chen Zhao, Shiqin Jiang, Yanhua Wu, Junjie Zhu, Dafang Zhou, Birgit Hailer, Dietrich Gronemeyer, Peter Van Leeuwen
We present a new approach of integrated maximum current density (IMCD) for the noninvasive detection of myocardial infarction (MI) using magnetocardiography (MCG) data acquired from a superconducting quantum interference device (SQUID) system. In this study, we investigated the relationship of the maximum current density (MCD) in the current density map and the underlying equivalent current dipole (ECD) based on a novel method of reconstructing the ECD in the extremum circle of the magnetic field map. The performance of IMCD and the integrated ECD (IECD) approaches were also evaluated by using 61-channel MCG data from 39 healthy subjects and 102 patients with ST elevation myocardial infarction (STEMI)...
January 9, 2017: IEEE Journal of Biomedical and Health Informatics
E Emary, Hossam M Zawbaa, Crina Grosan
In this paper, a variant of gray wolf optimization (GWO) that uses reinforcement learning principles combined with neural networks to enhance the performance is proposed. The aim is to overcome, by reinforced learning, the common challenge of setting the right parameters for the algorithm. In GWO, a single parameter is used to control the exploration/exploitation rate, which influences the performance of the algorithm. Rather than using a global way to change this parameter for all the agents, we use reinforcement learning to set it on an individual basis...
January 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
Ismael Seanez-Gonzalez, Camilla Pierella, Ali Farshchiansadegh, Elias Barry Thorp, Farnaz Abdollahi, Jessica P Pedersen, Ferdinando A Mussa-Ivaldi
In this study, we consider a non-invasive bodymachine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a highdimensional body-signal vector into a lower dimensional control vector on 6 subjects with high-level SCI and 8 controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter...
December 15, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Jae-Seok Choi, Munchurl Kim
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition (FHD) input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between PSNR performances and computational complexity...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jiansheng Chen, Zhengqin Li, Bo Huang
In this paper, we present a superpixel segmentation algorithm called linear spectral clustering (LSC), which is capable of producing superpixels with both high boundary adherence and visual compactness for natural images with low computational costs. In LSC, a normalized cuts based formulation of image segmentation is adopted using a distance metric that measures both the color similarity and the space proximity between image pixels. However, rather than directly using the traditional eigen-based algorithm, we approximate the similarity metric through a deliberately designed kernel function such that pixel values can be explicitly mapped to a high-dimensional feature space...
January 11, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Pengfei Wu, Yiguang Liu, Mao Ye, Zhenyu Xu, Yunan Zheng
In depth discontinuous and untextured regions, depth maps created by multiple view stereopsis are with heavy noises, but existing depth map fusion methods cannot handle it explicitly. To tackle the problem, two novel strategies are proposed: 1) a more discriminative fusion method, which is based on geometry consistency, measuring the consistency and stability of surface geometry computed on both partial and global surfaces, different from traditional methods only using visibility consistency; 2) a graph optimization method which fuses pyramids of depth maps as mutual complementary information is available in different scales, and differs from existing multiscale fusion methods...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Miguel Arevalillo-Herraez, Maximo Cobos, Miguel Garcia Pineda
In this paper, we present an effective algorithm to reduce the number of wraps in a two-dimensional (2-D) phase signal provided as input. The technique is based on an accurate estimate of the fundamental frequency of a 2-D complex signal with the phase given by the input, and the removal of a dependent additive term from the phase map. Unlike existing methods based on the Discrete Fourier Transform (DFT), the frequency is computed by using noise-robust estimates that are not restricted to integer values. Then, to deal with the problem of a non-integer shift in the frequency domain, an equivalent operation is carried out on the original phase signal...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Huazhu Fu, Dong Xu, Stephen Lin
We present an RGBD video segmentation method that takes advantage of depth data and can extract multiple foregrounds in the scene. This video segmentation is addressed as an object proposal selection problem formulated in a fullyconnected graph where a flexible number of foregrounds may be chosen. In the graph, each node represents a proposal, and the edges model intra-frame and inter-frame constraints on the solution. The proposals are generated based on an RGBD video saliency map in which depth-based features are utilized to enhance identification of foregrounds...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto Del Bimbo
Object detection is one of the most important tasks of computer vision. It is usually performed by evaluating a subset of the possible locations of an image that are more likely to contain the object of interest. Exhaustive approaches have now been superseded by object proposal methods. The interplay of detectors and proposal algorithms has not been fully analyzed and exploited up to now, although this is a very relevant problem for object detection in video sequences. We propose to connect, in a closed-loop, detectors and object proposal generator functions exploiting the ordered and continuous nature of video sequences...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Zhengguo Li, Zhe Wei, Changyun Wen, Jinghong Zheng
Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter (WGIF) to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image...
January 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Xiao-Yuan Jing, Xiaoke Zhu, Fei Wu, Ruimin Hu, Xinge You, Yunhong Wang, Hui Feng, Jing-Yu Yang
Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high-resolution (HR) while probe images are usually low-resolution (LR) in the identification scenarios with large variation of illumination, weather or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD2L) approach for SR person re-identification task...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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