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https://www.readbyqxmd.com/read/28441770/direction-of-arrival-estimation-for-mimo-radar-via-unitary-nuclear-norm-minimization
#1
Xianpeng Wang, Mengxing Huang, Xiaoqin Wu, Guoan Bi
In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to double the virtual array aperture, and the real-valued data are obtained by utilizing unitary transformation. Then a real-valued block sparse model is established based on a novel over-complete dictionary, and a UNNM algorithm is formulated for recovering the block-sparse matrix...
April 24, 2017: Sensors
https://www.readbyqxmd.com/read/28439523/tsallis-entropy-and-sparse-reconstructive-dictionary-learning-for-exudate-detection-in-diabetic-retinopathy
#2
Vineeta Das, Niladri B Puhan
Computer-assisted automated exudate detection is crucial for large-scale screening of diabetic retinopathy (DR). The motivation of this work is robust and accurate detection of low contrast and isolated hard exudates using fundus imaging. Gabor filtering is first performed to enhance exudate visibility followed by Tsallis entropy thresholding. The obtained candidate exudate pixel map is useful for further removal of falsely detected candidates using sparse-based dictionary learning and classification. Two reconstructive dictionaries are learnt using the intensity, gradient, local energy, and transform domain features extracted from exudate and background patches of the training fundus images...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28436868/high-order-local-pooling-and-encoding-gaussians-over-a-dictionary-of-gaussians
#3
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
https://www.readbyqxmd.com/read/28434089/pregnancy-and-kidney-disease-from-medicine-based-on-exceptions-to-exceptional-medicine
#4
EDITORIAL
Giorgina Barbara Piccoli, Gianfranca Cabiddu
The Webster dictionary defines exception as an anomaly, a person or thing that does not follow a rule, while the adjective exceptional has a different nuance, and means "above average". These two words may describe how obstetric nephrology has shifted from the description of very rare cases, to the development of a complex new and fascinating branch of medicine, that counterbalances obstetricians' usually optimistic outlook by focusing on subtle challenges posed by chronic diseases, and mitigate the frequently grim approach of nephrologists, with a message of hope: women with kidney disease can have the same basic life goals as healthy women their age...
April 22, 2017: Journal of Nephrology
https://www.readbyqxmd.com/read/28433503/mr-fingerprinting-reconstruction-with-kalman-filter
#5
Xiaodi Zhang, Zechen Zhou, Shiyang Chen, Shuo Chen, Rui Li, Xiaoping Hu
Magnetic resonance fingerprinting (MR fingerprinting or MRF) is a newly introduced quantitative magnetic resonance imaging technique, which enables simultaneous multi-parameter mapping in a single acquisition with improved time efficiency. The current MRF reconstruction method is based on dictionary matching, which may be limited by the discrete and finite nature of the dictionary and the computational cost associated with dictionary construction, storage and matching. In this paper, we describe a reconstruction method based on Kalman filter for MRF, which avoids the use of dictionary to obtain continuous MR parameter measurements...
April 19, 2017: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/28423790/improving-terminology-mapping-in-clinical-text-with-context-sensitive-spelling-correction
#6
Juliusz Dziadek, Aron Henriksson, Martin Duneld
The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28422683/progressive-dictionary-learning-with-hierarchical-predictive-structure-for-scalable-video-coding
#7
Wenrui Dai, Yangmei Shen, Hongkai Xiong, Xiaoqian Jiang, Junni Zou, David Taubman
Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance...
April 12, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28422677/learning-sparse-representation-for-objective-image-retargeting-quality-assessment
#8
Qiuping Jiang, Feng Shao, Weisi Lin, Gangyi Jiang
The goal of image retargeting is to adapt source images to target displays with different sizes and aspect ratios. Different retargeting operators create different retargeted images, and a key problem is to evaluate the performance of each retargeting operator. Subjective evaluation is most reliable, but it is cumbersome and labor-consuming, and more importantly, it is hard to be embedded into online optimization systems. This paper focuses on exploring the effectiveness of sparse representation for objective image retargeting quality assessment...
April 13, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28421225/using-telephony-data-to-facilitate-discovery-of-clinical-workflows
#9
Donald W Rucker
BACKGROUND:  Discovery of clinical workflows to target for redesign using methods such as Lean and Six Sigma is difficult. VoIP telephone call pattern analysis may complement direct observation and EMR-based tools in understanding clinical workflows at the enterprise level by allowing visualization of institutional telecommunications activity. OBJECTIVE:  To build an analytic framework mapping repetitive and high-volume telephone call patterns in a large medical center to their associated clinical units using an enterprise unified communications server log file and to support visualization of specific call patterns using graphical networks...
April 19, 2017: Applied Clinical Informatics
https://www.readbyqxmd.com/read/28421125/automatic-microaneurysms-detection-based-on-multifeature-fusion-dictionary-learning
#10
Wei Zhou, Chengdong Wu, Dali Chen, Zhenzhu Wang, Yugen Yi, Wenyou Du
Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28419628/hla-hd-an-accurate-hla-typing-algorithm-for-next-generation-sequencing-data
#11
Shuji Kawaguchi, Koichiro Higasa, Masakazu Shimizu, Ryo Yamada, Fumihiko Matsuda
The accurate typing of HLA alleles is critical for a variety of medical applications, such as genomic studies of multifactorial diseases, including immune system and inflammation-related disorders, and donor selection in organ transplantation and regenerative medicine. Here we developed a new algorithm for determining HLA alleles using next-generation sequencing (NGS) results. The method consists of constructing an extensive dictionary of HLA alleles, precise mapping of the NGS reads, and calculating a score based on weighted read counts to select the most suitable pair of alleles...
April 16, 2017: Human Mutation
https://www.readbyqxmd.com/read/28417320/patient-reporting-in-the-eu-analysis-of-eudravigilance-data
#12
Marin Banovac, Gianmario Candore, Jim Slattery, Francois Houÿez, David Haerry, Georgy Genov, Peter Arlett
INTRODUCTION: New pharmacovigilance legislation was adopted in the EU in 2010 and became operational in July 2012. The legislation placed an obligation on all national competent authorities (NCAs) and marketing authorisation holders (MAHs) to record and report cases of suspected adverse drug reactions (ADRs) received from patients. OBJECTIVES: This descriptive study aims to provide insight into patient reporting for the totality of the EU by querying the EudraVigilance (EV) database for the period of 3 years before the new pharmacovigilance legislation became operational and the 3 years after as well as comparing patient reports with those from healthcare professionals (HCPs) where feasible...
April 17, 2017: Drug Safety: An International Journal of Medical Toxicology and Drug Experience
https://www.readbyqxmd.com/read/28412455/effects-of-rf-pulse-profile-and-intra-voxel-phase-dispersion-on-mr-fingerprinting-with-balanced-ssfp-readout
#13
Su-Chin Chiu, Te-Ming Lin, Jyh-Miin Lin, Hsiao-Wen Chung, Cheng-Wen Ko, Martin Büchert, Michael Bock
PURPOSE: To investigate possible errors in T1 and T2 quantification via MR fingerprinting with balanced steady-state free precession readout in the presence of intra-voxel phase dispersion and RF pulse profile imperfections, using computer simulations based on Bloch equations. MATERIALS AND METHODS: A pulse sequence with TR changing in a Perlin noise pattern and a nearly sinusoidal pattern of flip angle following an initial 180-degree inversion pulse was employed...
April 13, 2017: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/28411394/improved-magnetic-resonance-fingerprinting-reconstruction-with-low-rank-and-subspace-modeling
#14
Bo Zhao, Kawin Setsompop, Elfar Adalsteinsson, Borjan Gagoski, Huihui Ye, Dan Ma, Yun Jiang, P Ellen Grant, Mark A Griswold, Lawrence L Wald
PURPOSE: This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). THEORY AND METHODS: A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T1 , T2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics...
April 15, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28410983/toward-better-public-health-reporting-using-existing-off-the-shelf-approaches-the-value-of-medical-dictionaries-in-automated-cancer-detection-using-plaintext-medical-data
#15
Suranga N Kasthurirathne, Brian E Dixon, Judy Gichoya, Huiping Xu, Yuni Xia, Burke Mamlin, Shaun J Grannis
OBJECTIVES: Existing approaches to derive decision models from plaintext clinical data frequently depend on medical dictionaries as the sources of potential features. Prior research suggests that decision models developed using non-dictionary based feature sourcing approaches and "off the shelf" tools could predict cancer with performance metrics between 80%-90%. We sought to compare non-dictionary based models to models built using features derived from medical dictionaries. MATERIALS AND METHODS: We evaluated the detection of cancer cases from free text pathology reports using decision models built with combinations of dictionary or non-dictionary based feature sourcing approaches, 4 feature subset sizes, and 5 classification algorithms...
April 11, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28410109/classification-via-sparse-representation-of-steerable-wavelet-frames-on-grassmann-manifold-application-to-target-recognition-in-sar-image
#16
Ganggang Dong, Gangyao Kuang, Na Wang, Wei Wang
Automatic target recognition has been studied widely over the years, yet it is still an open problem. The main obstacle consists in extended operating conditions, e.g., depression angle change, configuration variation, articulation, occlusion. To deal with them, this paper proposes a new classification strategy. We develop a new representation model via the steerable wavelet frames. The proposed representation model is entirely viewed as an element on Grassmann manifolds. To achieve target classification, we embed Grassmann manifolds into an implicit Reproducing Kernel Hilbert Space (RKHS), where the kernel sparse learning can be applied...
April 7, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28410105/dynamic-textures-modeling-via-joint-video-dictionary-learning
#17
Xian Wei, Yuanxiang Li, Hao Shen, Fang Chen, Martin Kleinsteuber, Zhongfeng Wang
Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series...
April 6, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28407249/healthcare-quality-a-concept-analysis
#18
Angela Allen-Duck, Jennifer C Robinson, Mary W Stewart
Worsening quality indicators of health care shake public trust. Although safety and quality of care in hospitals can be improved, healthcare quality remains conceptually and operationally vague. Therefore, the aim of this analysis is to clarify the concept of healthcare quality. Walker and Avant's method of concept analysis, the most commonly used in nursing literature, provided the framework. We searched general and medical dictionaries, public domain websites, and 5 academic literature databases. Search terms included health care and quality, as well as healthcare and quality...
April 13, 2017: Nursing Forum
https://www.readbyqxmd.com/read/28406919/what-are-the-assets-and-weaknesses-of-hfo-detectors-a-benchmark-framework-based-on-realistic-simulations
#19
Nicolas Roehri, Francesca Pizzo, Fabrice Bartolomei, Fabrice Wendling, Christian-George Bénar
High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors...
2017: PloS One
https://www.readbyqxmd.com/read/28400312/assigning-clinical-codes-with-data-driven-concept-representation-on-dutch-clinical-free-text
#20
Elyne Scheurwegs, Kim Luyckx, Léon Luyten, Bart Goethals, Walter Daelemans
Clinical codes are used for public reporting purposes, are fundamental to determining public financing for hospitals, and form the basis for reimbursement claims to insurance providers. They are assigned to a patient stay to reflect the diagnosis and performed procedures during that stay. This paper aims to enrich algorithms for automated clinical coding by taking a data-driven approach and by using unsupervised and semi-supervised techniques for the extraction of multi-word expressions that convey a generalisable medical meaning (referred to as concepts)...
April 8, 2017: Journal of Biomedical Informatics
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