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https://www.readbyqxmd.com/read/28329307/eacvi-appropriateness-criteria-for-the-use-of-transthoracic-echocardiography-in-adults-a-report-of-literature-and-current-practice-review
#1
Richard P Steeds, Madalina Garbi, Nuno Cardim, Jaroslaw D Kasprzak, Elif Sade, Petros Nihoyannopoulos, Bogdan Alexandru Popescu, Alexandros Stefanidis, Bernard Cosyns, Mark Monaghan, Svend Aakhus, Thor Edvardsen, Frank Flachskampf, Leonarda Galiuto, George Athanassopoulos, Patrizio Lancellotti
The European Association for Cardiovascular Imaging (EACVI) has outlined the rationale for setting appropriate use criteria (AUC) in cardiovascular (CV) imaging. Transthoracic echocardiography (TTE) is the most common imaging modality in CV disease and is a central tool in diagnosis, follow-up, management planning and intervention. The purpose of AUC is to inform referrers, both to avoid under-use, which may result in incomplete or incorrect diagnosis and treatment, and also over-use, which may delay correct diagnosis, lead to 'treatment cascade', and wastes resources...
February 25, 2017: European Heart Journal Cardiovascular Imaging
https://www.readbyqxmd.com/read/28328512/multitarget-sparse-latent-regression
#2
Xiantong Zhen, Mengyang Yu, Feng Zheng, Ilanit Ben Nachum, Mousumi Bhaduri, David Laidley, Shuo Li
Multitarget regression has recently generated intensive popularity due to its ability to simultaneously solve multiple regression tasks with improved performance, while great challenges stem from jointly exploring inter-target correlations and input-output relationships. In this paper, we propose multitarget sparse latent regression (MSLR) to simultaneously model intrinsic intertarget correlations and complex nonlinear input-output relationships in one single framework. By deploying a structure matrix, the MSLR accomplishes a latent variable model which is able to explicitly encode intertarget correlations via ℓ2,1-norm-based sparse learning; the MSLR naturally admits a representer theorem for kernel extension, which enables it to flexibly handle highly complex nonlinear input-output relationships; the MSLR can be solved efficiently by an alternating optimization algorithm with guaranteed convergence, which ensures efficient multitarget regression...
March 16, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28328502/spatial-statistics-for-segmenting-histological-structures-in-h-e-stained-tissue-images
#3
Luong Nguyen, A Burak Tosun, Jeffrey Fine, Adrian Lee, D Lansing Taylor, Chakra Chennubhotla
Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g. tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. Our paper focuses on segmenting histological structures in hematoxylin and eosin (H&E) stained images of breast tissues, e...
March 16, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28328293/history-of-knowledge-and-evolution-of-occupational-health-and-regulatory-aspects-of-asbestos-exposure-science-1900-1975
#4
Christy A Barlow, Jennifer Sahmel, Dennis J Paustenbach, John L Henshaw
The understanding by industrial hygienists of the hazards of asbestos and appropriate ways to characterize and control exposure has evolved over the years. Here, a detailed analysis of the evolution of industrial hygiene practices regarding asbestos and its health risks, from the early 1900s until the advent of the national occupational health and safety regulatory structure currently in place in the US (early-to-mid 1970s) is presented. While industrial hygienists recognized in the early 1900s that chronic and high-level exposures to airborne concentrations of asbestos could pose a serious health hazard, it was not until the mid-1950s that the carcinogenic nature of asbestos began to be characterized and widespread concern followed...
March 22, 2017: Critical Reviews in Toxicology
https://www.readbyqxmd.com/read/28328291/evaluation-of-multi-parameter-test-statistics-for-multiple-imputation
#5
Yu Liu, Craig K Enders
In Ordinary Least Square regression, researchers often are interested in knowing whether a set of parameters is different from zero. With complete data, this could be achieved using the gain in prediction test, hierarchical multiple regression, or an omnibus F test. However, in substantive research scenarios, missing data often exist. In the context of multiple imputation, one of the current state-of-art missing data strategies, there are several different analogous multi-parameter tests of the joint significance of a set of parameters, and these multi-parameter test statistics can be referenced to various distributions to make statistical inferences...
March 22, 2017: Multivariate Behavioral Research
https://www.readbyqxmd.com/read/28327500/a-review-of-sustainability-enhancements-in-the-beef-value-chain-state-of-the-art-and-recommendations-for-future-improvements
#6
Danielle Maia de Souza, Ruaraidh Petre, Fawn Jackson, Monica Hadarits, Sarah Pogue, Cameron N Carlyle, Edward Bork, Tim McAllister
The beef sector is working towards continually improving its sustainability in order to achieve environmentally, socially and economically desirable outcomes, all of which are of increasing concern to consumers. In this context, the Global Roundtable for Sustainable Beef (GRSB) provides guidance to advance the sustainability of the beef industry, through increased stakeholder engagement and the formation of national roundtables. Recently, the 2nd Global Conference on Sustainable Beef took place in Banff, Alberta, Canada, hosted by the GRSB and the Canadian Roundtable for Sustainable Beef...
March 22, 2017: Animals: An Open Access Journal From MDPI
https://www.readbyqxmd.com/read/28324124/osteoporosis-in-frail-patients-a-consensus-paper-of-the-belgian-bone-club
#7
REVIEW
E Gielen, P Bergmann, O Bruyère, E Cavalier, P Delanaye, S Goemaere, J-M Kaufman, M Locquet, J-Y Reginster, S Rozenberg, A-M Vandenbroucke, J-J Body
In this consensus paper, the Belgian Bone Club aims to provide a state of the art on the epidemiology, diagnosis, and management of osteoporosis in frail individuals, including patients with anorexia nervosa, patients on dialysis, cancer patients, persons with sarcopenia, and the oldest old. All these conditions may indeed induce bone loss that is superimposed on physiological bone loss and often remains under-recognized and under-treated. This is of particular concern because of the major burden of osteoporotic fractures in terms of morbidity, mortality, and economic cost...
March 21, 2017: Calcified Tissue International
https://www.readbyqxmd.com/read/28321912/boosting-joint-models-for-longitudinal-and-time-to-event-data
#8
Elisabeth Waldmann, David Taylor-Robinson, Nadja Klein, Thomas Kneib, Tania Pressler, Matthias Schmid, Andreas Mayr
Joint models for longitudinal and time-to-event data have gained a lot of attention in the last few years as they are a helpful technique clinical studies where longitudinal outcomes are recorded alongside event times. Those two processes are often linked and the two outcomes should thus be modeled jointly in order to prevent the potential bias introduced by independent modeling. Commonly, joint models are estimated in likelihood-based expectation maximization or Bayesian approaches using frameworks where variable selection is problematic and that do not immediately work for high-dimensional data...
March 21, 2017: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/28321246/medical-image-fusion-based-on-feature-extraction-and-sparse-representation
#9
Yin Fei, Gao Wei, Song Zongxi
As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information...
2017: International Journal of Biomedical Imaging
https://www.readbyqxmd.com/read/28320671/an-indoor-wayfinding-system-based-on-geometric-features-aided-graph-slam-for-the-visually-impaired
#10
He Zhang, Cang Ye
This paper presents a 6-DOF pose estimation (PE) method and an indoor wayfinding system based on the method for the visually impaired. The PE method involves two graph SLAM processes to reduce the accumulative pose error of the device. In the first step, the floor plane is extracted from the 3D camera's point cloud and added as a landmark node into the graph for 6-DOF SLAM to reduce roll, pitch and Z errors. In the second step, the wall lines are extracted and incorporated into the graph for 3-DOF SLAM to reduce X, Y and yaw errors...
March 15, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28320666/rgbd-salient-object-detection-via-deep-fusion
#11
Liangqiong Qu, Shengfeng He, Jiawei Zhang, Jiandong Tian, Yandong Tang, Qingxiong Yang
Numerous efforts have been made to design various low-level saliency cues for RGBD saliency detection, such as color and depth contrast features as well as background and color compactness priors. However, how these low-level saliency cues interact with each other and how they can be effectively incorporated to generate a master saliency map remain challenging problems. In this paper, we design a new convolutional neural network (CNN) to automatically learn the interaction mechanism for RGBD salient object detection...
March 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28320661/fast-unsupervised-bayesian-image-segmentation-with-adaptive-spatial-regularisation
#12
Marcelo Pereyra, Stephen McLaughlin
This paper presents a new Bayesian estimation technique for hidden Potts-Markov random fields with unknown regularisation parameters, with application to fast unsupervised K-class image segmentation. The technique is derived by first removing the regularisation parameter from the Bayesian model by marginalisation, followed by a small-variance-asymptotic (SVA) analysis in which the spatial regularisation and the integer-constrained terms of the Potts model are decoupled. The evaluation of this SVA Bayesian estimator is then relaxed into a problem that can be computed efficiently by iteratively solving a convex total-variation denoising problem and a least-squares clustering (K-means) problem, both of which can be solved straightforwardly, even in high-dimensions, and with parallel computing techniques...
March 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28320652/spectral-learning-for-supervised-topic-models
#13
Yong Ren, Yining Wang, Jun Zhu
Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA)...
March 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28316615/a-robust-shape-reconstruction-method-for-facial-feature-point-detection
#14
Shuqiu Tan, Dongyi Chen, Chenggang Guo, Zhiqi Huang
Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28300783/person-recognition-system-based-on-a-combination-of-body-images-from-visible-light-and-thermal-cameras
#15
Dat Tien Nguyen, Hyung Gil Hong, Ki Wan Kim, Kang Ryoung Park
The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel in the following three ways compared to previous studies. First, we use the images of human body for recognizing individuals. To overcome the limitations of previous studies on body-based person recognition that use only visible light images for recognition, we use human body images captured by two different kinds of camera, including a visible light camera and a thermal camera...
March 16, 2017: Sensors
https://www.readbyqxmd.com/read/28296919/image-mosaicking-using-surf-features-of-line-segments
#16
Zhanlong Yang, Dinggang Shen, Pew-Thian Yap
In this paper, we present a novel image mosaicking method that is based on Speeded-Up Robust Features (SURF) of line segments, aiming to achieve robustness to incident scaling, rotation, change in illumination, and significant affine distortion between images in a panoramic series. Our method involves 1) using a SURF detection operator to locate feature points; 2) rough matching using SURF features of directed line segments constructed via the feature points; and 3) eliminating incorrectly matched pairs using RANSAC (RANdom SAmple Consensus)...
2017: PloS One
https://www.readbyqxmd.com/read/28294043/polysaccharide-based-materials-associated-with-or-coordinated-to-gold-nanoparticles-synthesis-and-medical-application
#17
Débora P Facchi, Joziel A da Cruz, Elton G Bonafé, Antonio G B Pereira, André R Fajardo, Sandro A S Venter, Johny P Monteiro, Edvani C Muniz, Alessandro F Martins
BACKGROUND: Gold nanoparticles (AuNPs) have enormous potential for application in imaging, diagnosis, and therapies in the medical field. AuNPs are renowned for their localized surface plasmon resonance (LSPR) properties, large surface area, and biocompatibility with body fluids. Further, AuNPs have featured prominently in new methodologies for cancer treatments, like photothermal and imaging therapies. Although AuNPs present enormous potential for application in the medical field, their instability under physiological conditions prevents further uses...
March 9, 2017: Current Medicinal Chemistry
https://www.readbyqxmd.com/read/28293256/ranking-support-vector-machine-with-kernel-approximation
#18
Kai Chen, Rongchun Li, Yong Dou, Zhengfa Liang, Qi Lv
Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28287987/computational-model-based-on-neural-network-of-visual-cortex-for-human-action-recognition
#19
Haihua Liu, Na Shu, Qiling Tang, Wensheng Zhang
In this paper, we propose a bioinspired model for human action recognition through modeling neural mechanisms of information processing in two visual cortical areas: the primary visual cortex (V1) and the middle temporal cortex (MT) dedicated to motion. This model, named V1-MT, is composed of V1 and MT models (layers) corresponding to their cortical areas, which are built with layered spiking neural networks (SNNs). Some neuron properties in V1 and MT, such as direction and speed selectivity, spatiotemporal inseparability, and center surround suppression, are integrated into SNNs...
March 8, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28287986/deepx-deep-learning-accelerator-for-restricted-boltzmann-machine-artificial-neural-networks
#20
Lok-Won Kim
Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs...
March 8, 2017: IEEE Transactions on Neural Networks and Learning Systems
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