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Hiroki Matsuura, Hironori Kurokawa
No abstract text is available yet for this article.
June 21, 2017: QJM: Monthly Journal of the Association of Physicians
Ain A Neuhaus, Yvonne Couch, Gina Hadley, Alastair M Buchan
Acute ischaemic stroke accounts for 6.5 million deaths per year, and by 2030 will result in the annual loss of over 200 million disability-adjusted life years globally. There have been considerable recent advances in the gold standard of acute ischaemic stroke treatment, some aspects of which-aspirin to prevent recurrence, and treating patients in specialized stroke wards-are widely applicable. Recanalization of the occluded artery through thrombolysis and/or endovascular thrombectomy is restricted to only a small proportion of patients, due to contra-indications and the costs associated with establishing the infrastructure to deliver these treatments...
June 20, 2017: Brain: a Journal of Neurology
Inha Jung, Min Jung Kim, Hee Jung Moon, Jung Hyun Yoon, Eun-Kyung Kim
Purpose: This study assessed the outcomes of ultrasound (US)-guided core needle biopsies (CNBs) of breast lesions with at least 2 years of follow-up to determine the false-negative rate and to evaluate the diagnostic accuracy of CNB. Methods: We retrospectively analyzed 13,254 consecutive US-guided 14-gauge CNBs for breast lesions. We excluded biopsies if non-malignant biopsy result was not confirmed by surgical excision or US-guided vacuum-assisted biopsy, or fewer than 2 years of follow-up data were available...
May 17, 2017: Ultrasonography
Vincent Varlet, Alejandro Dominguez, Marc Augsburger, Maisy Lossois, Coraline Egger, Cristian Palmiere, Raquel Vilarino, Silke Grabherr
INTRODUCTION: Important developments in the diagnosis of scuba diving fatalities have been made thanks to forensic imaging tool improvements. Multi-detector computed tomography (MDCT) permits reliable interpretation of the overall gaseous distribution in the cadaver. However, due to post-mortem delay, the radiological interpretation is often doubtful because the distinction between gas related to the dive and post-mortem decomposition artifactual gases becomes less obvious. METHODS: We present six cases of fatal scuba diving showing gas in the heart and other vasculature...
June 2017: Diving and Hyperbaric Medicine: the Journal of the South Pacific Underwater Medicine Society
Lami Yeo, Suchaya Luewan, Dor Markush, Navleen Gill, Roberto Romero
Fetal dextrocardia is a type of cardiac malposition where the major axis from base to apex points to the right side. This condition is usually associated with a wide spectrum of complex cardiac defects. As a result, dextrocardia is conceptually difficult to understand and diagnose on prenatal ultrasound. The advantage of four-dimensional sonography with spatiotemporal image correlation (STIC) is that this modality can facilitate fetal cardiac examination. A novel method known as fetal intelligent navigation echocardiography (FINE) allows automatic generation of nine standard fetal echocardiography views in normal hearts by applying intelligent navigation technology to STIC volume datasets...
June 23, 2017: Fetal Diagnosis and Therapy
Zhiwei Dong, Jian Zhou, Ying Zhang, Yajie Chen, Zichen Yang, Guangtao Huang, Yu Chen, Zhiqiang Yuan, Yizhi Peng, Tongtong Cao
BACKGROUND: Thermal injury is the main cause of pulmonary disease in stroke after burn and can be life threatening. Heat-induced inflammation is an important factor that triggers a series of induces pathological changes. However, this mechanism underlying heat-induced inflammation in thermal inhalation injury remains unclear. Studies have revealed that astragaloside-IV (AS-IV), a natural compound extracted from Astragalus membranaceus, has protective effects in inflammatory diseases. Here, we investigated whether the protective effects of AS-IV occur because of the suppression of heat-induced endoplasmic reticulum (ER) stress and excessive autophagy Methods: AS-IV was administered to Wistar rats after thermal inhalation injury and 16HBE140-cells were treated with AS-IV...
June 23, 2017: Cellular Physiology and Biochemistry
Diane L Murzin, Eric C Belanger, John P Veinot, Nataliya Milman
BACKGROUND: Idiopathic aortitis became recognized relatively recently, and the body of knowledge concerning this condition is scarce. We aimed to determine the frequency of idiopathic aortitis in aortic specimens, the clinical, laboratory and radiologic characteristics at diagnosis and during follow-up, and the approach to investigation, treatment and monitoring taken by the treating physicians. METHODS: We identified cases of aortitis diagnosed on pathological specimens of the aorta between Jan...
June 19, 2017: CMAJ Open
Shintami C Hidayati, Chuang-Wen You, Wen-Huang Cheng, Kai-Lung Hua
According to the theory of clothing design, the genres of clothes can be recognized based on a set of visually differentiable style elements, which exhibit salient features of visual appearance and reflect high-level fashion styles for better describing clothing genres. Instead of using less-discriminative low-level features or ambiguous keywords to identify clothing genres, we proposed a novel approach for automatically classifying clothing genres based on the visually differentiable style elements. A set of style elements, that are crucial for recognizing specific visual styles of clothing genres, were identified based on the clothing design theory...
June 19, 2017: IEEE Transactions on Cybernetics
Zhigang Ma, Xiaojun Chang, Zhongwen Xu, Nicu Sebe, Alexander G Hauptmann
Semantic attributes have been increasingly used the past few years for multimedia event detection (MED) with promising results. The motivation is that multimedia events generally consist of lower level components such as objects, scenes, and actions. By characterizing multimedia event videos with semantic attributes, one could exploit more informative cues for improved detection results. Much existing work obtains semantic attributes from images, which may be suboptimal for video analysis since these image-inferred attributes do not carry dynamic information that is essential for videos...
June 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Hong Tao, Chenping Hou, Feiping Nie, Jubo Zhu, Dongyun Yi
With the advent of multi-view data, multi-view learning has become an important research direction in machine learning and image processing. Considering the difficulty of obtaining labeled data in many machine learning applications, we focus on the multi-view semi-supervised classification problem. In this paper, we propose an algorithm named Multi-View Semi-Supervised Classification via Adaptive Regression (MVAR) to address this problem. Specifically, regression based loss functions with ℓ2,1 matrix norm are adopted for each view and the final objective function is formulated as the linear weighted combination of all the loss functions...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Mengqiu Hu, Yang Yang, Fumin Shen, Luming Zhang, Heng Tao Shen, Xuelong Li
Driven by the rapid development of Internet and digital technologies, we have witnessed the explosive growth of Web images in recent years. Seeing that labels can reflect the semantic contents of the images, automatic image annotation, which can further facilitate the procedure of image semantic indexing, retrieval and other image management tasks, has become one of the most crucial research directions in multimedia. Most of the existing annotation methods heavily rely on well-labeled training data (expensive to collect) and/or single view of visual features (insufficient representative power)...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Deepak G Skariah, Muthuvel Arigovindan
We develop a novel optimization algorithm, which we call Nested Non-Linear Conjugate Gradient algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient (CG) iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT based non-iterative preconditioner...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Reuben A Farrugia, Christine Guillemot
Most face super-resolution methods assume that low- and high-resolution manifolds have similar local geometrical structure, hence learn local models on the low-resolution manifold (e.g. sparse or locally linear embedding models), which are then applied on the high- resolution manifold. However, the low-resolution manifold is distorted by the one-to-many relationship between low- and high- resolution patches. This paper presents the Linear Model of Coupled Sparse Support (LM-CSS) method which learns linear models based on the local geometrical structure on the high-resolution manifold rather than on the low-resolution manifold...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jongyoo Kim, Taewan Kim, Sanghoon Lee, Alan C Bovik
Crosstalk is one of the most severe factors affecting the perceived quality of stereoscopic 3D (S3D) images. It arises from a leakage of light intensity between multiple views, as in auto-stereoscopic displays. Well-known determinants of crosstalk include the co-location contrast and disparity of the left and right images, which have been dealt with in prior studies. However, when a natural stereo image that contains complex naturalistic spatial characteristics is viewed on an auto-stereoscopic display, other factors may also play an important role in the perception of crosstalk...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Martin Storath, Dennis Rickert, Michael Unser, Andreas Weinmann
We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model which are capable of dealing with 3D images defined on non-cubic grids. Our discretization allows us to utilize a specific splitting approach which results in decoupled subproblems of moderate size. The crucial point in the 3D setup is that the number of independent subproblems is so large that we can reasonably exploit the parallel processing capabilities of the graphics processing units (GPU)...
June 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Mansoor Rezghi
Image restoration is one of the main parts of image processing. Mathematically, this problem can be modeled as a large scale structured ill-posed linear system. Ill-posedness of this problem results in low convergence rate of iterative solvers. For speeding up the convergence, preconditioning usually is used. Despite the existing preconditioners for image restoration which are constructed based on approximations of the blurring matrix, in this paper, we propose a novel preconditioner with a different viewpoint...
June 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Massimo Zanetti, Lorenzo Bruzzone
Variational models are known to work well for addressing image restoration/regularization problems. However, most of the methods proposed in literature are defined for scalar inputs and are used on multiband images (such as RGB or multispectral imagery) by the composition of a simple band-wise processing. This involves suboptimal results and may introduce artifacts. Only in a few cases variational models are extended to the case of vector-valued inputs. However, the known implementations are restricted to 1st-order models, while 2nd-order models are never considered...
June 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Christopher G R Wallis, Yves Wiaux, Jason D McEwen
We develop techniques to solve ill-posed inverse problems on the sphere by sparse regularisation, exploiting sparsity in both axisymmetric and directional scale-discretised wavelet space. Denoising, inpainting, and deconvolution problems, and combinations thereof, are considered as examples. Inverse problems are solved in both the analysis and synthesis settings, with a number of different sampling schemes. The most effective approach is that with the most restricted solution-space, which depends on the interplay between the adopted sampling scheme, the selection of the analysis/synthesis problem, and any weighting of the ℓ1 norm appearing in the regularisation problem...
June 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Csaba Benedek
In this paper we introduce a probabilistic approach for extracting complex hierarchical object structures from digital images used by various vision applications. The proposed framework extends conventional Marked Point Process (MPP) models by (i) admitting object-subobject ensembles in parent-child relationships and (ii) allowing corresponding objects to form coherent object groups, by a Bayesian segmentation of the population. Different from earlier, highly domain specific attempts on MPP generalization, the proposed model is defined at an abstract level, providing clear interfaces for applications in various domains...
June 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Kyong Hwan Jin, Michael T McCann, Emmanuel Froustey, Michael Unser
In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. These methods produce excellent results, but can be challenging to deploy in practice due to factors including the high computational cost of the forward and adjoint operators and the difficulty of hyper parameter selection. The starting point of our work is the observation that unrolled iterative methods have the form of a CNN (filtering followed by point-wise nonlinearity) when the normal operator ( H*H where H* is the adjoint of the forward imaging operator, H ) of the forward model is a convolution...
June 15, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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