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https://www.readbyqxmd.com/read/27908249/automated-system-for-referral-of-cotton-wool-spots
#1
Syed Ali Gohar Naqvi, Hafiz Muhammad Faisal Zafar, Ihsan Ul Haq
BACKGROUND: Cotton-wool spots also referred as soft exudates are the early sign of complications in the eye fundus of the patients suffering from diabetic retinopathy. Early detection of exudates helps in diagnosis of the disease and provides better medical attention. METHODS: In the paper an automated system for detection of soft exudates has been suggested. The system has been developed by the combination of different techniques like scale invariant feature transform (SIFT), Visual Dictionaries, K-means clustering and support vector machine (SVM)...
December 1, 2016: Current Diabetes Reviews
https://www.readbyqxmd.com/read/27903921/a-two-pool-model-to-describe-the-ivim-cerebral-perfusion
#2
Gabrielle Fournet, Jing-Rebecca Li, Alex M Cerjanic, Bradley P Sutton, Luisa Ciobanu, Denis Le Bihan
IntraVoxel Incoherent Motion (IVIM) is a magnetic resonance imaging (MRI) technique capable of measuring perfusion-related parameters. In this manuscript, we show that the mono-exponential model commonly used to process IVIM data might be challenged, especially at short diffusion times. Eleven rat datasets were acquired at 7T using a diffusion-weighted pulsed gradient spin echo sequence with b-values ranging from 7 to 2500 s/mm(2) at three diffusion times. The IVIM signals, obtained by removing the diffusion component from the raw MR signal, were fitted to the standard mono-exponential model, a bi-exponential model and the Kennan model...
November 30, 2016: Journal of Cerebral Blood Flow and Metabolism
https://www.readbyqxmd.com/read/27893388/sparse-representation-based-multiple-frame-video-super-resolution
#3
Qiqin Dai, Seunghwan Yoo, Armin Kappeler, Aggelos K Katsaggelos
In this paper, we propose two multiple-frame superresolution (SR) algorithms based on dictionary learning and motion estimation. First, we adopt the use of video bilevel dictionary learning which has been used for single-frame SR. It is extended to multiple frames by using motion estimation with subpixel accuracy. We propose a batch and a temporally recursive multi-frame SR algorithm, which improve over single frame SR. Finally, we propose a novel dictionary learning algorithm utilizing consecutive video frames, rather than still images or individual video frames, which further improves the performance of the video SR algorithms...
November 22, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27888009/a-novel-approach-for-the-chromatographic-purification-and-peptide-mass-fingerprinting-of-urinary-free-light-chains
#4
Bhupesh C Mali, Shamkant B Badgujar, Kunal K Shukla, Paresh B Bhanushali
We describe a chromatographic approach for the purification of urinary free light chains (FLCs) viz., lambda free light chains (λ-FLCs) and kappa free light chains (κ-FLCs). Isolated urinary FLCs were analyzed by SDS-PAGE, immunoblotting and mass spectrometry (MS). The relative molecular masses of λ-FLC and κ-FLC are 22,933.397 and 23,544.336Da respectively. Moreover, dimer forms of each FLC were also detected in mass spectrum which corresponds to 45,737.747 and 47,348.028Da respectively for λ-FLCs and κ-FLCs...
November 22, 2016: International Journal of Biological Macromolecules
https://www.readbyqxmd.com/read/27886096/service-demand-discovery-mechanism-for-mobile-social-networks
#5
Dapeng Wu, Junjie Yan, Honggang Wang, Ruyan Wang
In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation...
November 23, 2016: Sensors
https://www.readbyqxmd.com/read/27882837/determining-multiple-sclerosis-phenotype-from-electronic-medical-records
#6
Richard E Nelson, Jorie Butler, Joanne LaFleur, Kristin Knippenberg, Aaron W C Kamauu, Scott L DuVall
BACKGROUND: Multiple sclerosis (MS), a central nervous system disease in which nerve signals are disrupted by scarring and demyelination, is classified into phenotypes depending on the patterns of cognitive or physical impairment progression: relapsing-remitting MS (RRMS), primary-progressive MS (PPMS), secondary-progressive MS (SPMS), or progressive-relapsing MS (PRMS). The phenotype is important in managing the disease and determining appropriate treatment. The ICD-9-CM code 340.0 is uninformative about MS phenotype, which increases the difficulty of studying the effects of phenotype on disease...
December 2016: Journal of Managed Care & Specialty Pharmacy
https://www.readbyqxmd.com/read/27871720/-guidelines-for-the-prescription-of-mood-stabilizers-for-adolescents-a-literature-review
#7
G Munch, N Godart
INTRODUCTION: Adolescence is a unique phase of the human developmental process. In adolescents, psychotropic medications may have different efficacy and tolerance profiles compared to those at other stages of the lifespan. Mood stabilizers are a complex pharmacological category including lithium, some anticonvulsants, and some second generation antipsychotics. Focusing on this class of pharmacological agents, we aim to answer the following questions: in which indications and according to which modalities should mood stabilizers be prescribed during adolescence? METHODS: Information was sought from the websites of the French Haute Autorité de santé (HAS) and Agence nationale de sécurité du médicament et des produits de santé (ANSM), the American Food and Drug Administration (FDA) and the British National Institute for Health and Clinical Excellence (NICE)...
November 18, 2016: L'Encéphale
https://www.readbyqxmd.com/read/27870999/sparse-bayesian-registration-of-medical-images-for-self-tuning-of-parameters-and-spatially-adaptive-parametrization-of-displacements
#8
Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache
We extend Bayesian models of non-rigid image registration to allow not only for the automatic determination of registration parameters (such as the trade-off between image similarity and regularization functionals), but also for a data-driven, multiscale, spatially adaptive parametrization of deformations. Adaptive parametrizations have been used with success to promote both the regularity and accuracy of registration schemes, but so far on non-probabilistic grounds - either as part of multiscale heuristics, or on the basis of sparse optimization...
November 9, 2016: Medical Image Analysis
https://www.readbyqxmd.com/read/27868321/dementia-related-adverse-events-in-paradigm-hf-and-other-trials-in-heart-failure-with-reduced-ejection-fraction
#9
Jane A Cannon, Li Shen, Pardeep S Jhund, Søren L Kristensen, Lars Køber, Fabian Chen, Jianjian Gong, Martin P Lefkowitz, Jean L Rouleau, Victor C Shi, Karl Swedberg, Michael R Zile, Scott D Solomon, Milton Packer, John J V McMurray
AIMS: Inhibition of neprilysin, an enzyme degrading natriuretic and other vasoactive peptides, is beneficial in heart failure with reduced ejection fraction (HFrEF), as shown in PARADIGM-HF which compared the angiotensin receptor-neprilysin inhibitor (ARNI) sacubitril/valsartan with enalapril. As neprilysin is also one of many enzymes clearing amyloid-β peptides from the brain, there is a theoretical concern about the long-term effects of sacubitril/valsartan on cognition. Therefore, we have examined dementia-related adverse effects (AEs) in PARADIGM-HF and placed these findings in the context of other recently conducted HFrEF trials...
November 20, 2016: European Journal of Heart Failure
https://www.readbyqxmd.com/read/27868105/feasibility-of-automated-3-dimensional-magnetic-resonance-imaging-pancreas-segmentation
#10
Shuiping Gou, Percy Lee, Peng Hu, Jean-Claude Rwigema, Ke Sheng
PURPOSE: With the advent of MR guided radiotherapy, internal organ motion can be imaged simultaneously during treatment. In this study, we evaluate the feasibility of pancreas MRI segmentation using state-of-the-art segmentation methods. METHODS AND MATERIAL: T2 weighted HASTE and T1 weighted VIBE images were acquired on 3 patients and 2 healthy volunteers for a total of 12 imaging volumes. A novel dictionary learning (DL) method was used to segment the pancreas and compared to t mean-shift merging (MSM), distance regularized level set (DRLS), graph cuts (GC) and the segmentation results were compared to manual contours using Dice's index (DI), Hausdorff distance and shift of the-center-of-the-organ (SHIFT)...
July 2016: Advances in Radiation Oncology
https://www.readbyqxmd.com/read/27867889/liraglutide-effect-and-action-in-diabetes-in-lead-in-a-prospective-observational-study-assessing-safety-and-effectiveness-of-liraglutide-in-patients-with-type-2-diabetes-mellitus-treated-under-routine-clinical-practice-conditions-in-india
#11
Subhash Kumar Wangnoo, Surender Kumar, Arpandev Bhattacharyya, Sudhir Tripathi, Shahid Akhtar, Raman Shetty, Samit Ghosal
BACKGROUND: This 26-week, open-label observational study assessed the incidence and type of adverse events (AEs) associated with liraglutide use according to the standard clinical practice settings and the local label in India. MATERIALS AND METHODS: A total of 1416 adults with type 2 diabetes (T2D) treated with liraglutide in 125 sites across India were included in the study. Participants were newly diagnosed or already receiving antidiabetic medications. Safety and efficacy data were collected at baseline and at approximately weeks 13 and 26...
November 2016: Indian Journal of Endocrinology and Metabolism
https://www.readbyqxmd.com/read/27867052/accelerating-mri-fat-quantification-using-a-signal-model-based-dictionary-to-assess-gastric-fat-volume-and-distribution-of-fat-fraction
#12
Dian Liu, Andreas Steingoetter, Helen L Parker, Jelena Curcic, Sebastian Kozerke
To quantify intragastric fat volume and distribution with accelerated magnetic resonance (MR) imaging using signal model-based dictionaries (DICT) in comparison to conventional parallel imaging (CG-SENSE). This study was approved by the local ethics committee and written informed consent was obtained. Seven healthy subjects were imaged after intake of a lipid emulsion and data at three different time points during the gastric emptying process was acquired in order to cover a range of fat fractions. Fully sampled and prospectively undersampled image data at a reduction factor of 4 were acquired using a multi gradient echo sequence at 1...
November 17, 2016: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/27851871/robust-sliding-window-reconstruction-for-accelerating-the-acquisition-of-mr-fingerprinting
#13
Xiaozhi Cao, Congyu Liao, Zhixing Wang, Ying Chen, Huihui Ye, Hongjian He, Jianhui Zhong
PURPOSE: To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes. THEORY AND METHODS: A sliding-window (SW) strategy was applied to MRF, in which signal and dictionary matching was conducted between fingerprints consisting of mixed-contrast image series reconstructed from consecutive data frames segmented by a sliding window, and a precalculated mixed-contrast dictionary. The effectiveness and performance of this new method, dubbed SW-MRF, was evaluated in both phantom and in vivo...
November 7, 2016: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/27849551/information-clustering-using-manifold-based-optimization-of-the-bag-of-features-representation
#14
Nikolaos Passalis, Anastasios Tefas
In this paper, a manifold-based dictionary learning method for the bag-of-features (BoF) representation optimized toward information clustering is proposed. First, the spectral representation, which unwraps the manifolds of the data and provides better clustering solutions, is formed. Then, a new dictionary is learned in order to make the histogram space, i.e., the space where the BoF historgrams exist, as similar as possible to the spectral space. The ability of the proposed method to improve the clustering solutions is demonstrated using a wide range of datasets: two image datasets, the 15-scene dataset and the Corel image dataset, one video dataset, the KTH dataset, and one text dataset, the RT-2k dataset...
November 10, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/27849534/random-walk-graph-laplacian-based-smoothness-prior-for-soft-decoding-of-jpeg-images
#15
Xianming Liu, Gene Cheung, Xiaolin Wu, Debin Zhao
Given the prevalence of JPEG compressed images, optimizing image reconstruction from the compressed format remains an important problem. Instead of simply reconstructing a pixel block from the centers of indexed DCT coefficient quantization bins (hard decoding), soft decoding reconstructs a block by selecting appropriate coefficient values within the indexed bins with the help of signal priors. The challenge thus lies in how to define suitable priors and apply them effectively. In this paper, we combine three image priors-Laplacian prior for DCT coefficients, sparsity prior and graph-signal smoothness prior for image patches-to construct an efficient JPEG soft decoding algorithm...
November 10, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27848067/validity-and-reliability-of-the-upper-extremity-work-demands-scale
#16
Nora W Jacobs, Redmar J Berduszek, Pieter U Dijkstra, Corry K van der Sluis
Purpose To evaluate validity and reliability of the upper extremity work demands (UEWD) scale. Methods Participants from different levels of physical work demands, based on the Dictionary of Occupational Titles categories, were included. A historical database of 74 workers was added for factor analysis. Criterion validity was evaluated by comparing observed and self-reported UEWD scores. To assess structural validity, a factor analysis was executed. For reliability, the difference between two self-reported UEWD scores, the smallest detectable change (SDC), test-retest reliability and internal consistency were determined...
November 15, 2016: Journal of Occupational Rehabilitation
https://www.readbyqxmd.com/read/27837523/linguistic-evidence-for-the-failure-mindset-as-a-predictor-of-life-span-longevity
#17
Ian B Penzel, Michelle R Persich, Ryan L Boyd, Michael D Robinson
BACKGROUND: When people think that their efforts will fail to achieve positive outcomes, they sometimes give up their efforts after control, which can have negative health consequences. PURPOSE: Problematic orientations of this type, such as pessimism, helplessness, or fatalism, seem likely to be associated with a cognitive mindset marked by higher levels of accessibility for failure words or concepts. Thus, the purpose of the present research was to determine whether there are individual differences in the frequency with which people think about failure, which in turn are likely to impact health across large spans of time...
November 11, 2016: Annals of Behavioral Medicine: a Publication of the Society of Behavioral Medicine
https://www.readbyqxmd.com/read/27831875/bilevel-model-based-discriminative-dictionary-learning-for-recognition
#18
Pan Zhou, Chao Zhang, Zhouchen Lin
Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the `0 or `1 norm to encode each datum independently, limiting the performance of the learnt dictionaries...
October 31, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27831874/content-adaptive-sketch-portrait-generation-by-decompositional-representation-learning
#19
Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan, Ebroul Izquierdo
Sketch portrait generation benefits a wide range of applications such as digital entertainment and law enforcement. Although plenty of efforts have been dedicated to this task, several issues still remain unsolved for generating vivid and detail-preserving personal sketch portraits. For example, quite a few artifacts may exist in synthesizing hairpins and glasses, and textural details may be lost in the regions of hair or mustache. Moreover, the generalization ability of current systems is somewhat limited since they usually require elaborately collecting a dictionary of examples or carefully tuning features/components...
January 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27831873/multi-modal-dictionary-learning-for-image-separation-with-application-in-art-investigation
#20
Nikos Deligiannis, Joao F C Mota, Bruno Cornelis, Miguel R D Rodrigues, Ingrid Daubechies
In support of art investigation, we propose a new source separation method that unmixes a single X-ray scan acquired from double-sided paintings. In this problem, the X-ray signals to be separated have similar morphological characteristics, which brings previous source separation methods to their limits. Our solution is to use photographs taken from the front-and back-side of the panel to drive the separation process. The crux of our approach relies on the coupling of the two imaging modalities (photographs and X-rays) using a novel coupled dictionary learning framework able to capture both common and disparate features across the modalities using parsimonious representations; the common component captures features shared by the multi-modal images, whereas the innovation component captures modality-specific information...
October 31, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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