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Objective Automated segmentation of lymph nodes (LNs) in ultrasound images is a challenging task mainly due to the presence of speckle noise and echogenic hila. In this paper, we propose a fully automatic and accurate method for LN segmentation in ultrasound. Methods The proposed segmentation method integrates diffusion-based despeckling, U-Net convolutional neural networks and morphological operations. Firstly, we suppress speckle noise and enhance lymph node edges using the Gabor-based anisotropic diffusion (GAD). Secondly, a modified U-Net model is proposed to segment LNs excluding echogenic hila. Finally, morphological operations are adopted to segment entire LNs by filling the regions of echogenic hila.Results A total of 531 lymph nodes from 526 patients were included to evaluate the proposed method. Quantitative metrics of segmentation performance, including the accuracy, sensitivity, specificity, Jaccard similarity and Dice coefficient, reached 0.934, 0.939, 0.937, 0.763 and 0.865, respectively.Conclusion The proposed method automatically and accurately segments LNs in ultrasound, which may assist artificially intelligent diagnosis of lymph node diseases.

Ultrasound image segmentation is a crucial step in computer-aided diagnosis. In this study, we propose a cross-tissue/organ segmentation method based on the transfer learning method and a modified deep residual U-Net model. We present a modified deep residual U-Net model by integrating a U-Net architecture with residual blocks to leverage the advantages of both components. Next, we explore a cross-tissue/organ transfer learning method for ultrasound image segmentation, which transfers the knowledge of ultrasound image segmentation from one tissue/organ to another, e.g. from tendon images to breast tumor images and vice versa. We evaluated the proposed method by performing four groups of experiments on three medical ultrasound datasets, consisting of one tendon dataset and two breast datasets, along with one non-medical dataset. The results showed an overall performance improvement by our method in terms of the Dice coefficient and Jaccard index. It was demonstrated that our modified deep residual U-Net exceeded the standard U-Net and residual U-Net, and the cross-tissue/organ transfer learning was superior to training from scratch and to transfer learning between divergent domains. Our method shows potential to accurately segment medical ultrasound images.

The current study investigated the cognitive and neural substrates that underpin writing ability. We explored similarities and differences in writing numbers and words and compared these to language and manual actions in a large group of sub-acute, stroke patients (n = 740). The behavioral data showed association and dissociation in the ability to write words and numbers. Comorbidities of writing deficits with both language and motor impairments were prevalent, with less than a handful showing deficits restricted to the writing tasks. A second analysis with a subset of patients (n = 267) explored the neural networks that mediate writing abilities. Lesion to right temporal contributed to writing words, while lesions to left postcentral contributed to writing numbers. Overlapping neural mechanisms included the bilateral prefrontal cortex, right inferior parietal, left middle occipital and the right cerebellum. With the former regions associated with error pattern typical to writing based on prior knowledge (the lexical route), while lesion to left MOG was associated with errors to the phonological (non-lexical) route. Using principle components extracted from the behavioral data, we showed that right prefrontal and right parietal contributed to the ability to use pen, while lesion to bilateral prefrontal, inferior temporal and cerebellum supported unique use of pen for writing. The behavioral and imaging data suggested that writing numbers and words primarily relied on overlapping cognitive and neural functions. Incidents of pure writing deficits, in the absence of motor or language deficits were rare. Nevertheless, the PCA and neural data suggested that writing abilities were associated with some unique neuro-cognitive functions, specifically dedicated to the use of pen and the ability to transform meaning to motor command.

Background: The double random phase encoding techniques have received considerable attention from researchers in recent years because of its advantages of parallel and high speed processing capability. Meanwhile, the security of cryptosystem is also one of the major concerns. Methods : We experimentally demonstrated the ciphertext redundancy vulnerability of the coherent double random encryption system (DRPE). Based on the statistical ergodicity of speckles and the consistency of the power spectral density (ESD), we have proved that the most plaintext information can be retrieved from partial ciphertext alone. Results: In this paper, the simulation and experiment result were performed to verify whether the algorithm is effectiveness. The ciphertext redundancy of the DRPE system is analyzed from the results of ciphertext occlusion test. There is a risk of plaintext leakage of this scheme, as long as the average ESD can be estimated from the sub-images. The results will help to open up deeper understanding of limitation of current optical security techniques. Conclusions: The DRPE system has potential redundancy risk. Even one-time-pad manner is not secured in DRPE system. This vulnerability allows a cryptanalyst to estimate the plaintext information with only a half or less ciphertext.

Speckle noise contaminates medical ultrasound images, and the suppression of speckle noise is helpful for image interpretation. Traditional ultrasound denoising (i.e., despeckling) methods are developed on two-dimensional static images. However, one of the advantages of ultrasonography is its nature of dynamic imaging. A method for dynamic ultrasound despeckling is expected to incorporate both the spatial and temporal information in successive images of dynamic ultrasound and thus yield better denoising performance. Here we regard a dynamic ultrasound video as three-dimensional (3-D) images with two dimensions in the spatial domain and one in the temporal domain, and we propose a despeckling algorithm for dynamic ultrasound named the 3-D Gabor-based anisotropic diffusion (GAD-3D). The GAD-3D expands the classic two-dimensional Gabor-based anisotropic diffusion (GAD) into 3-D domain. First, we proposed a robust 3-D Gabor-based edge detector by capturing the edge with 3-D Gabor transformation. Then we embed this novel detector into the partial differential equation of GAD to guide the 3-D diffusion process. In the simulation experiment, when the noise variance is as high as 0.14, the GAD-3D improves the Pratt's figure of merit, mean structural similarity index and peak signal-to-noise ratio by 24.32%, 10.98%, and 6.51%, respectively, compared with the best values of seven other methods. Experimental results on clinical dynamic ultrasonography suggest that the GAD-3D outperforms the other seven methods in noise reduction and detail preservation. The GAD-3D is effective for dynamic ultrasound despeckling and may be potentially valuable for disease assessment in dynamic medical ultrasonography.

Our meta-analysis aims to evaluate the association of Asp299Gly and Thr399Ile with rheumatoid arthritis (RA) susceptibility and severity. By manually searching 3 electronic databases (PubMed, Embase and Web of Science), relevant articles were collected. After checking eligibility for every study, this meta-analysis on eligible studies was performed under 5 genetic models: (1) allelic contrast; (2) heterozygous model; (3) homozygous model; (4) dominant model; (5) recessive model. In Spanish populations, a significantly decreased RA risk was identified in allelic comparison (odds ratio [OR] = 0.73, 95% CI 0.55 ~ 0.96) and dominant model (OR = 0.74, 95% CI 0.56 ~ 0.99) of Asp299Gly polymorphism. A trend of reduced risk was also observed under the heterozygous model (OR = 0.77, 95% CI 0.58 ~ 1.03). As for Thr399Ile, it might also have a protective effect on Spanish populations in allelic comparison (OR = 0.71, 95% CI 0.44 ~ 1.15). In contrast, for both Asp299Gly and Thr399Ile, a higher risk of RA was detected in Chinese Han populations. The frequency of both Asp299Gly and Thr399Ile increased in rheumatoid factor (RF)-positive subjects in Chinese patients (Asp299Gly, RF+:RF- = 0.165:0.145; Thr399Ile, RF+:RF- = 0.170:0.161) and decreased in Spanish patients (Asp299Gly, RF+:RF- = 0.060:0.073; Thr399Ile, RF+:RF- = 0.046:0.056), but not to a statistically significant extent. Our meta-analysis suggested that both Asp299Gly and Thr399Ile might have a protective effect on Spanish populations, but the 2 polymorphisms could act as a susceptible factor in Chinese Han populations. To confirm our results, further investigation concerning the functional impacts of Asp299Gly and Thr399Ile are still needed.

This work reports new evidence of the versatility of soft and environmentally responsive micron-sized colloidal gel particles as stabilizers at ionic liquid-water droplet interfaces. These particles display a duality with properties ascribed typically to both polymeric and colloidal systems. The utilization of fluorescently labeled composite microgel particles allows in-situ and facile visualization without the necessity of invasive sample preparation. When the prepared particles form monolayers equilibrated at the ionic liquid-water interface on fully covered droplets, the colloidal lattice re-orders itself depending on the surface charge of these particles. Finally, we demonstrate that the spontaneously formed and densely packed layer of microgel particles can be employed for extraction applications, as the interface remains permeable to small active species.

Objective The purposes of this study are to investigate the regional homogeneity (ReHo) of spontaneous brain activities in Parkinson's disease (PD) patients with freeze of gait (FOG) and to investigate the neural correlation of movement function through resting-state functional magnetic resonance imaging (RS-fMRI). Methods A total of 35 normal controls (NC), 33 PD patients with FOG (FOG+), and 35 PD patients without FOG (FOG-) were enrolled. ReHo was applied to evaluate the regional synchronization of spontaneous brain activities. Analysis of covariance (ANCOVA) was performed on ReHo maps of the three groups, followed by post hoc two-sample t-tests between every two groups. Moreover, the ReHo signals of FOG+ and FOG- were extracted across the whole brain and correlated with movement scores (FOGQ, FOG questionnaire; GFQ, gait and falls questionnaire). Results Significant ReHo differences were observed in the left cerebrum. Compared to NC subjects, the ReHo of PD subjects was increased in the left angular gyrus (AG) and decreased in the left rolandic operculum/postcentral gyrus (Rol/PostC), left inferior opercular-frontal cortex, left middle occipital gyrus, and supramarginal gyrus (SMG). Compared to that of FOG-, the ReHo of FOG+ was increased in the left caudate and decreased in the left Rol/PostC. Within the significant regions, the ReHo of FOG+ was negatively correlated with FOGQ in the left SMG/PostC (r = -0.39, p < 0.05). Negative correlations were also observed between ReHo and GFQ/FOGQ (r = -0.36/-0.38, p < 0.05) in the left superior temporal gyrus (STG) of the whole brain analysis based on AAL templates. Conclusion The ReHo analysis suggested that the regional signal synchronization of brain activities in FOG+ subjects was most active in the left caudate and most hypoactive in the left Rol/PostC. It also indicated that ReHo in the left caudate and left Rol/PostC was critical for discriminating the three groups. The correlation between ReHo and movement scores (GFQ/FOGQ) in the STG has the potential to differentiate FOG+ from FOG-. This study provided new insight into the understanding of PD with and without FOG.

Background: Abnormalities of cognitive and movement functions are widely reported in Parkinson’s disease (PD). The mechanisms therein are complicated and assumed to a coordination of various brain regions. This study explored the alterations of global synchronizations of brain activities and investigated the neural correlations of cognitive and movement function in PD patients.Methods: Thirty-five age-matched patients with PD and 35 normal controls (NC) were enrolled in resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Degree centrality (DC) was calculated to measure the global synchronizations of brain activity for two groups. Neural correlations between DC and cognitive function Frontal Assessment Battery (FAB), as well as movement function Unified Parkinson’s Disease Rating Scale (UPDRS-III), were examined across the whole brain within Anatomical Automatic Labeling (AAL) templates.Results: In the PD group, increased DC was observed in left fusiform gyrus extending to inferior temporal gyrus, left middle temporal gyrus (MTG) and angular gyrus, while it was decreased in right inferior opercular-frontal gyrus extending to superior temporal gyrus (STG). The DC in a significant region of the fusiform gyrus was positively correlated with UPDRS-III scores in PD (r = 0.41, p = 0.0145). Higher FAB scores were shown in NC than PD (p < 0.0001). Correlative analysis of PD between DC and FAB showed negative results (p < 0.05) in frontal cortex, whereas positive in insula and cerebellum. As for the correlations between DC and UPDRS-III, negative correlation (p < 0.05) was observed in bilateral inferior parietal lobule (IPL) and right cerebellum, whereas positive correlation (p < 0.05) in bilateral hippocampus and para-hippocampus gyrus (p < 0.01).Conclusion: The altered global synchronizations revealed altered cognitive and movement functions in PD. The findings suggested that the global functional connectivity in fusiform gyrus, cerebellum and hippocampus gyrus are critical regions in the identification of cognitive and movement functions in PD. This study provides new insights on the interactions among global coordination of brain activity, cognitive and movement functions in PD.

Complex figure copying is a commonly used neuropsychological test. Here we explored the neural basis of the factors underlying complex figure copying (CFC), using data from the Birmingham Cognitive Screen (BCoS) in a large group of sub-acute, ischemic stroke patients (239). We computed two analyses: in the first we assessed the contribution of co-morbid deficits (i.e. in gesture processing, object use, visual neglect, pictures naming and sustained attention) to the lesions associated with CFC. In a second analysis a Principle Component Analysis (PCA) was used to isolate different underlying task components and to link to clinical neuroimaging scans. A voxel-based morphometry (VBM) analysis showed that poor CFC performance was associated with lesions to bi-lateral thalamus, lingual, right fusiform and right inferior parietal cortices (rIPC). The latter association with the posterior parietal cortex was diminished after controlling for neglect. Follow up analysis showed the neglect partially mediated the correlation of CFC and rIPC. The PCA revealed three main underlying components: (1) a component associated with high-level motor control common to different measures of apraxia and linked to the left postcentral gyrus, the right thalamus and middle frontal gyrus; (2) a visuo-motor transformation component unique to the CFC and associated with lesions to the posterior occipital and sensory cortices; (3) a component associated with multistep object use tasks which was correlated with lesions to the left inferior frontal orbital gyrus, the right fusiform and cerebellum. Using clinical symptoms, cognitive profiles and lesion mapping we showed that beyond visual perception, CFC performance is supported by three functional networks: one for high-level motor control, a visuo-motor transformation component, and multistep object use network., Graphical abstract Image 1, Highlights • Symptoms comorbidity, PCA and VBM were combined to report the neuro-cognitive mechansims underlying complex figure copy. • Beyond vision, CFC is supported by 3 functional networks: high level motor, visuo-motor transformation and object use. • The association between right inferior parietal cortices and CFC is partially mediated by neglect.

NaNO3 and other alkali nitrate salts, which are present in the molten state during use, have been described as facilitators or catalysts for CO2 absorption by both MgO and MgO-containing double salts. Although MgO exhibits a high capacity (exceeding 70 wt %), its regenerability in multicycle tests shows a significant loss of capacity with cycle number prior to lining out. On the other hand, the MgO–Na2CO3 double salt shows a lower (∼16 wt %) but stable capacity over multiple cycles under pressure swing operation. The purpose of this paper is to elaborate on the concept of molten salts as catalysts for CO2 absorption by MgO, and extend these observations to the MgO-containing double salt oxides. We will show that the phenomena involved with CO2 absorption by MgO and MgO-based double salts are similar and general, but with some important differences. This paper focuses on the following key concepts: (i) identification of conditions that favor or disfavor participation of isolated MgO during double salt abso...

In recent years, wide attention has been drawn to how to reduce the energy consumption for data collection in wireless sensor networks (WSNs). Unlike existing energy-efficient data collection models in WSNs, we present a hybrid data collection scheme based on Compressed Sensing (CS) to collect the compressed sensed data in an energy-efficient and load-balanced manner. In our proposed scheme, the data collection process is divided into the intra-cluster data collection process and the inter-cluster data collection process. By modelling the optimal clustering problem as a separable convex optimization problem, we can obtain the optimal clustering size and the optimal data transmission radius. Furthermore, a Cluster Head (CH) chain based on pseudo Hilbert curve is built to collect the compressed sensed data among CHs in an accumulative way. The experimental results show that the proposed method not only reduces the total energy consumption, but also effectively balance the distribution of energy consumption among CHs.

In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.

Xiaoping Pan,1,* Haobo Chen,1,2,* Wai-Ling Bickerton,2 Johnny King Lam Lau,2 Anthony Pak Hin Kong,3 Pia Rotshtein,2 Aihua Guo,1 Jianxi Hu,1 Glyn W Humphreys4 1Department of Neurology, Guangzhou First People’s Hospital, Guangzhou Medical University, Guangzhou, People’s Republic of China; 2School of Psychology, University of Birmingham, Birmingham, UK; 3Department of Communication Sciences and Disorders, University of Central Florida, Orlando, FL, USA; 4Department of Experimental Psychology, University of Oxford, Oxford, UK *These authors contributed equally to this work Background: There are no currently effective cognitive assessment tools for patients who have suffered stroke in the People’s Republic of China. The Birmingham Cognitive Screen (BCoS) has been shown to be a promising tool for revealing patients’ poststroke cognitive deficits in specific domains, which facilitates more individually designed rehabilitation in the long run. Hence we examined the reliability and validity of a Cantonese version BCoS in patients with acute ischemic stroke, in Guangzhou.Method: A total of 98 patients with acute ischemic stroke were assessed with the Cantonese version of the BCoS, and an additional 133 healthy individuals were recruited as controls. Apart from the BCoS, the patients also completed a number of external cognitive tests, including the Montreal Cognitive Assessment Test (MoCA), Mini Mental State Examination (MMSE), Albert’s cancellation test, the Rey–Osterrieth Complex Figure Test, and six gesture matching tasks. Cutoff scores for failing each subtest, ie, deficits, were computed based on the performance of the controls. The validity and reliability of the Cantonese BCoS were examined, as well as interrater and test–retest reliability. We also compared the proportions of cases being classified as deficits in controlled attention, memory, character writing, and praxis, between patients with and without spoken language impairment.Results: Analyses showed high test–retest reliability and agreement across independent raters on the qualitative aspects of measurement. Significant correlations were observed between the subtests of the Cantonese BCoS and the other external cognitive tests, providing evidence for convergent validity of the Cantonese BCoS. The screen was also able to generate measures of cognitive functions that were relatively uncontaminated by the presence of aphasia.Conclusion: This study suggests good reliability and validity of the Cantonese version of the BCoS. The Cantonese BCoS is a very promising tool for the detection of cognitive problems in Cantonese speakers. Keywords: cerebral infarction, cognitive impairment, neuropsychological testing, validation test, reliability test, Cantonese speakers&nbsp

Iodide-based ionic liquids have been widely employed as iodide sources in electrolytes for applications utilizing the triiodide/iodide redox couple. While adding a low-viscosity solvent such as water to ionic liquids can greatly enhance their usefulness, mixtures of highly viscous iodide-containing ILs with water have never been studied. This paper investigates, for the first time, mixtures of water and the ionic liquid 1-butyl-3-methylimidazolium iodide ([BMIM][I]) through a combined experimental and molecular dynamics study. The density, melting point, viscosity, and conductivity of these mixtures were measured by experiment. The composition region below 50% water by mole was found to differ dramatically from the region above 50% water, with trends in density and melting point differing before and after that point. Water was found to have a profound effect on viscosity and conductivity of the IL, and the effect of hydrogen bonding was discussed. Molecular dynamics simulations representing the same mixture compositions were performed. Molecular ordering was observed, as were changes in this ordering corresponding to water content. Molecular ordering was related to the experimentally measured mixture properties, providing a possible explanation for the two distinct composition regions identified by experiment.

We synthesize monodispersed zwitterionic microgel (ZI-MG) particles that undergo an extensive, reversible change in volume in response to environmental stimuli such as pH and temperature. These aqueous ZI-MG dispersions exhibit a minimum hydrodynamic diameter value at an adjustable isoelectric point (IEP). In addition, the study elucidates the controlled uptake and release of ionic and nonionic surfactants from these particle systems. The extent of surfactant loading and the ensuing relative swelling/deswelling behaviors within the colloidal polymer networks are explained in terms of their binding interactions.

Spectral reflectance provides the most fundamental information of objects and is recognized as the “fingerprint” of them, since reflectance is independent of illumination and viewing conditions. However, reconstructing high-dimensional spectral reflectance from relatively low-dimensional camera outputs is an illposed problem and most of methods requaired camera’s spectral responsivity. We propose a method to reconstruct spectral reflectance from digital camera outputs without prior knowledge of camera’s spectral responsivity. This method respectively averages reflectances of selected subset from main training samples by prescribing a limit to tolerable color difference between the training samples and the camera outputs. Different tolerable color differences of training samples were investigated with Munsell chips under D65 light source. Experimental results show that the proposed method outperforms classic PI method in terms of multiple evaluation criteria between the actual and the reconstructed reflectances. Besides, the reconstructed spectral reflectances are between 0-1, which make them have actual physical meanings and better than traditional methods.

We synthesize monodisperse ionic microgel particles which undergo a large change in volume in response to environmental stimuli such as pH and temperature. In addition, the study elucidates the effective uptake and release of rheology modifiers from these microgel particles to alter the bulk viscosity of a surrounding fluid. Moreover, we found that the prepared ionic microgel particles can demonstrate abilities to adsorb and repel iron oxide nanoparticles (Fe3O4-NPs) upon pH variation. The extent of the loading of Fe3O4-NPs within the colloidal particles and morphology can be manipulated by tunable interactions between the Fe3O4-NPs and ionic microgel particles.