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Li Kuo Tan, Yih Miin Liew, Einly Lim, Robert A McLaughlin
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints...
April 12, 2017: Medical Image Analysis
Shatha Alnafea, Stefano Fedele, Stephen Porter, Richeal Ni Riordain
AIMS: To evaluate the quality and readability of online information about the treatment of burning mouth syndrome (BMS). METHODS: An internet search using the phrase "burning mouth syndrome treatment" was carried out on the Google search engine ( on 8 June 2015, and the first 100 websites listed were examined. Data collection included DISCERN score, the Journal of the American Medical Association (JAMA) benchmarks for website analysis score, the presence of the Health on the Net (HON) Foundation seal, and the Flesch Reading Ease Score (FRES)...
April 2017: Journal of Oral & Facial Pain and Headache
Honggui Han, Wei Lu, Junfei Qiao
Multiobjective particle swarm optimization (MOPSO) algorithms have attracted much attention for their promising performance in solving multiobjective optimization problems (MOPs). In this paper, an adaptive MOPSO (AMOPSO) algorithm, based on a hybrid framework of the solution distribution entropy and population spacing (SP) information, is developed to improve the search performance in terms of convergent speed and precision. First, an adaptive global best (gBest) selection mechanism, based on the solution distribution entropy, is introduced to analyze the evolutionary tendency and balance the diversity and convergence of nondominated solutions in the archive...
April 17, 2017: IEEE Transactions on Cybernetics
Zhengming Ding, Yun Fu
Multiview data are of great abundance in real-world applications, since various viewpoints and multiple sensors desire to represent the data in a better way. Conventional multiview learning methods aimed to learn multiple view-specific transformations meanwhile assumed the view knowledge of training, and test data were available in advance. However, they would fail when we do not have any prior knowledge for the probe data's view information, since the correct view-specific projections cannot be utilized to extract effective feature representations...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
Ahana Gangopadhyay, Oindrila Chatterjee, Shantanu Chakrabartty
Growth transformations constitute a class of fixed-point multiplicative update algorithms that were originally proposed for optimizing polynomial and rational functions over a domain of probability measures. In this paper, we extend this framework to the domain of bounded real variables which can be applied towards optimizing the dual cost function of a generic support vector machine (SVM). The approach can, therefore, not only be used to train traditional soft-margin binary SVMs, one-class SVMs, and probabilistic SVMs but can also be used to design novel variants of SVMs with different types of convex and quasi-convex loss functions...
April 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
Yuchen Guo, Guiguang Ding, Jungong Han, Yue Gao
By transferring knowledge from the abundant labeled samples of known source classes, zero-shot learning (ZSL) makes it possible to train recognition models for novel target classes that have no labeled samples. Conventional ZSL approaches usually adopt a two-step recognition strategy, in which the test sample is projected into an intermediary space in the first step, and then the recognition is carried out by considering the similarity between the sample and target classes in the intermediary space. Due to this redundant intermediate transformation, information loss is unavoidable, thus degrading the performance of overall system...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Sebastien C Wong, Victor Stamatescu, Adam Gatt, David Kearney, Ivan Lee, Mark D McDonnell
This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fastlearning image classifier that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Peihua Li, Hui Zeng, Qilong Wang, Simon Shiu, Lei Zhang
Local pooling (LP) in configuration (feature) space proposed by Boureau et al. explicitly restricts similar features to be aggregated, which can preserve as much discriminative information as possible. At the time it appeared, this method combined with sparse coding achieved competitive classification results with only a small dictionary. However, its performance lags far behind state-of-the-art results as only zero-order information is exploited. Inspired by the success of high-order statistical information in existing advanced feature coding or pooling methods, we make an attempt to address the limitation of LP...
April 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Di Lin, Cewu Lu, Hui Huang, Jiaya Jia
Towards weather condition recognition, we emphasize the importance of regional cues in this paper and address a few important problems regarding appropriate representation, its differentiation among regions, and weather-condition feature construction. Our major contribution is, first, to construct a multi-class benchmark dataset containing 65,000 images from 6 common categories for sunny, cloudy, rainy, snowy, haze and thunder weather. This dataset also benefits weather classification and attribute recognition...
April 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Bin Wang, Zhijian Ou, Zhiqiang Tan
To describe trans-dimensional observations in sample spaces of different dimensions, we propose a probabilistic model, called the trans-dimensional random field (TRF) by explicitly mixing a collection of random fields. In the framework of stochastic approximation (SA), we develop an effective training algorithm, called augmented SA, which jointly estimates the model parameters and normalizing constants while using trans-dimensional mixture sampling to generate observations of different dimensions. Furthermore, we introduce several statistical and computational techniques to improve the convergence of the training algorithm and reduce computational cost, which together enable us to successfully train TRF models on large datasets...
April 24, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Raghudeep Gadde, Varun Jampani, Renaud Marlet, Peter Gehler
This paper introduces a fast and efficient segmentation technique for 2D images and 3D point clouds of building facades. Facades of buildings are highly structured and consequently most methods that have been proposed for this problem aim to make use of this strong prior information. Contrary to most prior work, we are describing a system that is almost domain independent and consists of standard segmentation methods. We train a sequence of boosted decision trees using auto-context features. This is learned using stacked generalization...
April 24, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Miranda F Shaw, David L Osborn, Meredith J T Jordan, Scott H Kable
Fourier transform infrared spectra of isolated 1-propenol and 2-propenol in the gas-phase have been collected in the range of 900-3800 cm-1, and the absolute infrared absorption cross sections reported for the first time. Both cis and trans isomers of 1-propenol were observed with the trans isomer in greater abundance. Syn and anti conformers of both 1- and 2-propenol were also observed, with abundance consistent with thermal population. The FTIR spectrum of the smaller ethenol (vinyl alcohol) was re-measured as a benchmark for our computational results...
April 24, 2017: Journal of Physical Chemistry. A
Leyi Wei, Pengwei Xing, Ran Su, Gaotao Shi, Zhanshan Sam Ma, Quan Zou
Cell-penetrating peptides (CPPs), have been proven as important drug delivery vehicles, demonstrating the potential as therapeutic candidates. The last decade has witnessed a rapid growth in CPP-based research. Recently, many computational efforts have been made to develop machine learning based methods for identifying CPPs. Although much progress has been made, existing methods still suffer low feature representation capability that limits further performance improvement. In this study, we propose a novel predictor called CPPred-RF, in which we integrate multiple sequence-based feature descriptors to sufficiently explore distinct information embedded in CPPs, employ a well-established feature selection technique to improve the feature representation, and at the first time, construct a 2-layer prediction framework based on the random forest algorithm...
April 24, 2017: Journal of Proteome Research
Jindal K Shah, Eliseo Marin-Rimoldi, Ryan Gotchy Mullen, Brian P Keene, Sandip Khan, Andrew S Paluch, Neeraj Rai, Lucienne L Romanielo, Thomas W Rosch, Brian Yoo, Edward J Maginn
Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc.
April 24, 2017: Journal of Computational Chemistry
Dariusz W Szczepanik, Miquel Solà, Marcin Andrzejak, Barbara Pawełek, Justyna Dominikowska, Mercedes Kukułka, Karol Dyduch, Tadeusz M Krygowski, Halina Szatylowicz
In this article, we address the role of the long-range exchange corrections in description of the cyclic delocalization of electrons in aromatic systems at the density functional theory level. A test set of diversified monocyclic and polycyclic aromatics is used in benchmark calculations involving various exchange-correlation functionals. A special emphasis is given to the problem of local aromaticity in acenes, which has been a subject of long-standing debate in the literature. The presented results indicate that the noncorrected exchange-correlation functionals significantly overestimate cyclic delocalization of electrons in heteroaromatics and aromatic systems with fused rings, which in the case of acenes leads to conflicting local aromaticity predictions from different criteria...
April 24, 2017: Journal of Computational Chemistry
Jorge Echeverría, Jordi Cirera, Santiago Alvarez
In this work, a theoretical analysis of intermolecular HgHg contacts in the presence of different ligands is presented. A survey of structural databases to explore the geometrical preferences among experimental structures presenting short Hg(ii)Hg(ii) contacts reveals the main interaction topologies depending on the nature of the ligand. A benchmark study of several dispersion corrected-density functional methods is carried out to determine the optimal computational methodology for the theoretical study of such interaction...
April 24, 2017: Physical Chemistry Chemical Physics: PCCP
Dan DeBlasio, John Kececioglu
BACKGROUND: In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins...
2017: Algorithms for Molecular Biology: AMB
Osman M Ahmed, Brian D O'Donnell, Anthony G Gallagher, George D Shorten
PURPOSE: Change in the landscape of medical education coupled with a paradigm shift toward outcome-based training mandates the trainee to demonstrate specific predefined performance benchmarks in order to progress through training. A valid and reliable assessment tool is a prerequisite for this process. The objective of this study was to characterize ultrasound-guided axillary brachial plexus block to develop performance and error metrics and to verify face and content validity using a modified Delphi method...
2017: Advances in Medical Education and Practice
Iris Schleicher, Karsten Leitner, Jana Juenger, Andreas Moeltner, Miriam Ruesseler, Bernd Bender, Jasmina Sterz, Tina Stibane, Sarah Koenig, Susanne Frankenhauser, Joachim Gerhard Kreuder
BACKGROUND: Practical skills are often assessed using Objective Structured Clinical Skill Exams (OSCE). Nevertheless, in Germany, interchange and agreement between different medical faculties or a general agreement on the minimum standard for passing is lacking. METHODS: We developed standardized OSCE-stations for assessing structured clinical examination of knee and shoulder joint with identical checklists and evaluation standards. These were implemented into the OSCE-course at five different medical faculties...
April 20, 2017: Annals of Anatomy, Anatomischer Anzeiger: Official Organ of the Anatomische Gesellschaft
David J Wilkinson, Patrick A Green, Shanthi Beglinger, Jessica Myers, Rachel Hudson, David Edgar, Simon E Kenny
INTRODUCTION: Hypospadias surgery has progressed steadily over recent years. There remains considerable variation in the operative management of boys with hypospadias in the UK, and it is therefore difficult to identify acceptable standards with regards to reoperation rates. OBJECTIVE: To determine the frequency of reoperations and complications from all centres performing hypospadias surgery in England and to identify variables that influence outcome. METHODS: All children undergoing NHS hypospadias surgery in England between 1999 and 2009 were identified using the Hospital Episode Statistics database...
February 20, 2017: Journal of Pediatric Urology
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