با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
MISS-D: A fast and scalable framework of medical image storage service based on distributed file system
MISS-D: یک چارچوب سریع و مقیاس پذیر از خدمات ذخیره سازی تصویر پزشکی بر اساس سیستم فایل توزیع شده-2020
Background and Objective Processing of medical imaging big data is deeply challenging due to the size of data, computational complexity, security storage and inherent privacy issues. Traditional picture archiving and communication system, which is an imaging technology used in the healthcare industry, generally uses centralized high performance disk storage arrays in the practical solutions. The existing storage solutions are not suitable for the diverse range of medical imaging big data that needs to be stored reliably and accessed in a timely manner. The economical solution is emerging as the cloud computing which provides scalability, elasticity, performance and better managing cost. Cloud based storage architecture for medical imaging big data has attracted more and more attention in industry and academia. Methods This study presents a novel, fast and scalable framework of medical image storage service based on distributed file system. Two innovations of the framework are introduced in this paper. An integrated medical imaging content indexing file model for large-scale image sequence is designed to adapt to the high performance storage efficiency on distributed file system. A virtual file pooling technology is proposed, which uses the memory-mapped file method to achieve an efficient data reading process and provides the data swapping strategy in the pool. Result The experiments show that the framework not only has comparable performance of reading and writing files which meets requirements in real-time application domain, but also bings greater convenience for clinical system developers by multiple client accessing types. The framework supports different user client types through the unified micro-service interfaces which basically meet the needs of clinical system development especially for online applications. The experimental results demonstrate the framework can meet the needs of real-time data access as well as traditional picture archiving and communication system. Conclusions This framework aims to allow rapid data accessing for massive medical images, which can be demonstrated by the online web client for MISS-D framework implemented in this paper for real-time data interaction. The framework also provides a substantial subset of features to existing open-source and commercial alternatives, which has a wide range of potential applications.
Keywords: Hadoop distributed file system | Data packing | Memory mapping file | Message queue | Micro-service | Medical imaging
To Hop or not to Hop: Exceptions in the FCS Diffusion Law
به هاپ آری یا نه : استثنائات در قانون پخش FCS-2020
Diffusion obstacles in membranes have not been directly visualized because of fast membrane dynamics and the occurrence of subresolution molecular complexes. To understand the obstacle characteristics, mobility-based methods are often used as an indirect way of assessing the membrane structure. Molecular movement in biological plasma membranes is often characterized by anomalous diffusion, but the exact underlying mechanisms are still elusive. Imaging total internal reflection fluorescence correlation spectroscopy (ITIR-FCS) is a well-established mobility-based method that provides spatially resolved diffusion coefficient maps and is combined with FCS diffusion law analysis to examine subresolution membrane organization. In recent years, although FCS diffusion law analysis has been instrumental in providing new insights into the membrane structure below the optical diffraction limit, there are certain exceptions and anomalies that require further clarification. To this end, we correlate the membrane structural features imaged by atomic force microscopy (AFM) with the dynamics measured using ITIR-FCS. We perform ITIR-FCS measurements on supported lipid bilayers (SLBs) of various lipid compositions to characterize the anomalous diffusion of lipid molecules in distinct obstacle configurations, along with the high-resolution imaging of the membrane structures with AFM. Furthermore, we validate our experimental results by performing simulations on image grids with experimentally determined obstacle configurations. This study demonstrates that FCS diffusion law analysis is a powerful tool to determine membrane heterogeneities implied from dynamics measurements. Our results corroborate the commonly accepted interpretations of imaging FCS diffusion law analysis, and we show that exceptions happen when domains reach the percolation threshold in a biphasic membrane and a network of domains behaves rather like a meshwork, resulting in hop diffusion.
Computational analysis of NIRS and BOLD signal from neurovascular coupling with three neuron-system feedforward inhibition network
تجزیه و تحلیل محاسباتی سیگنال های NIRS و BOLD از اتصال جفت عصبی عروقی با سه شبکه مهار کننده تغذیه ای سیستم عصبی-2020
Several neurological disorders occur due to hypoxic condition in brain arising from impairment of cere- bral functionality, which can be controlled by neural stimulation driven vasoactive response mediated through biological response in astrocyte, a phenomenon known as neurovascular coupling. Brain can ad- just with the problem of hypoxic condition by causing vasodilation with the help of this mechanism. To deduce the mechanism behind vasodilation of blood vessel caused by neuronal stimulus, current study articulates a mathematical model involving neuronal system feedforward inhibition network model (FFI) with two other functional components of neurovascular coupling, i.e. astrocyte and smooth muscle cell lining blood vessel. This study includes the neural inhibition network system where glutamatergic pyra- midal neuron and GABAergic interneuron act antagonistically with each other. The proposed model suc- cessfully includes the implication of the inhibition system to design mathematical model for neurovas- cular coupling. Result of the proposed model shows that the increase in neuronal stimulus from 20 to 60 μA/cm 2 has the ability to increase the vasodilatory activity of blood tissue vasculature. Oxygenation level and hemodynamic response due to input synaptic stimulation has been calculated by regional cere- bral oxygenation level (rS0 2 ) and blood oxygen level dependent (BOLD) imaging signal which supports vasodilation of blood vessel with increase in synaptic input stimulus.
Keywords: Neurovascular coupling unit | Hodgkin-Huxley model | Neurotransmitter | Feedforward-inhibition network | Regional cerebral oxygen saturation
Remote sensing and social sensing for socioeconomic systems: A comparison study between nighttime lights and location-based social media at the 500m spatial resolution
سنجش از دور و سنجش اجتماعی برای سیستمهای اقتصادی اقتصادی: مطالعه مقایسه ای بین چراغ های شب و رسانه های اجتماعی مبتنی بر مکان در وضوح مکانی 500 متر-2020
With the advent of “social sensing” in the Big Data era, location-based social media (LBSM) data are increasingly used to explore anthropogenic activities and their impacts on the environment. This study converts a typical kind of LBSM data, geo-tagged tweets, into raster images at the 500m spatial resolution and compares them with the new generation nighttime lights (NTL) image products, the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) monthly image composites. The results show that the monthly tweet images are significantly correlated with the VIIRS-DNB images at the pixel level. The tweet images have nearly the same ability on estimating electric power consumption and better performance on assessing personal incomes and population than the NTL images. Tweeted areas (i.e. the pixels with at least one posted tweet) are closer to satellite-derived built-up/urban areas than lit areas in NTL imagery, making tweet images an alternative to delimit extents of human activities. Moreover, the monthly tweet images do not show apparent seasonal changes, and the values of tweet images are more stable across different months than VIIRS-DNB monthly image composites. This study explores the potential of LBSM data at relatively fine spatiotemporal resolutions to estimate or map socioeconomic factors as an alternative to NTL images in the United States
Keywords: Nighttime lights imagery | Geo-tagged tweets | Socioeconomic factors | Social sensing
Synaptic Specificity, Recognition Molecules, and Assembly of Neural Circuits
ویژگی سیناپسی ، مولکولهای تشخیص و مونتاژ مدارهای عصبی-2020
Developing neurons connect in specific and stereotyped ways to form the complex circuits that underlie brain function. By comparison to earlier steps in neural development, progress has been slow in identifying the cell surface recognition molecules that mediate these synaptic choices, but new high-throughput imaging, genetic, and molecular methods are accelerating progress. Over the past decade, numerous large and small gene families have been implicated in target recognition, including members of the immunoglobulin, cadherin, and leucine-rich repeat superfamilies. We review these advances and propose ways in which combinatorial use of multifunctional recognition molecules enables the complex neuron-neuron interactions that underlie synaptic specificity.
Phase volume quantification of agarose-ghee gels using 3D confocal laser scanning microscopy and blending law analysis: A comparison
اندازه گیری حجم فاز ژل های agarose-ghee با استفاده از میکروسکوپ اسکن لیزر کانفوکال 3D و تجزیه و تحلیل قانون: یک مقایسه -2020
A thorough understanding of the phase behaviour of biomaterial composites is imperative for manipulating the structural and textural properties in novel food products. This study probed the phase behaviour of a model system comprising agarose and a varying concentration of ghee. Results obtained from scanning electron microscopy (SEM), micro differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR) and dynamic oscillation in-shear revealed discontinuous and hard inclusions of ghee reinforcing the continuous, weaker agarose matrix with increasing concentrations of the former. Phase behaviour of the system was quantified in parallel with a novel method combining 3D confocal laser scanning microscopy (CLSM) imaging and image analysis software - FIJI and Imaris - in an effort to substantiate the efficacy of the microscopic protocol in quantifying phase behaviour. Phase volumes recorded with the microscopic protocol were in close agreement to those modelled with the Lewis-Nielsen blending law using small-deformation dynamic oscillation. However, results indicated that the inner filtering effect or ‘self-shadowing’ observed commonly in CLSM images may pose a limitation to the application of this technique, necessitating further development before it can be applied to more complex, industrially relevant systems.
Keywords: Lewis-Nielsen blending law | Phase behaviour | Confocal laser scanning microscopy | 3D imaging | Image analysis
Towards the interpretation of complex visual hallucinations in termsof self-reorganization of neural networks
به سمت تفسیر توهمات پیچیده بصری از نظر خود سازماندهی مجدد شبکه های عصبی-2020
Patients suffering from dementia with Lewy body (DLB) often see complex visual hallucinations (CVH).Despite many pathological, clinical, and neuroimaging studies, the mechanism of CVH remains unknown.One possible scenario is that top-down information is being used to compensate for the lack of bottom-up information. To investigate this possibility and understand the underlying mathematical structureof the CVH mechanism, we propose a simple computational model of synaptic plasticity with particu-lar focus on the effect of selective damage to the bottom-up network on self-reorganization. We showneurons that undergo a change in activity from a bottom-up to a top-down network framework duringthe reorganization process, which can be understood in terms of state transitions. Assuming that thepre-reorganization representation of this neuron remains after reorganization, it is possible to interpretneural response induced by top-down information as the sensation of bottom-up information. This sit-uation might correspond to a hallucinatory situation in DLB patients. Our results agree with existingexperimental evidence and provide new insights into data that have hitherto not been experimentallyvalidated on patients with DLB.
Keywords : Network self-reorganization | Complex visual hallucinations| Synaptic plasticity | State transition | Oscillology
STrategically Acquired Gradient Echo (STAGE) imaging, part III: Technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method
تصویربرداری گرادیان اکو (STAGE) استراتژیک ، بخش سوم: پیشرفت های فنی و برنامه های بالینی از یک روش تصویربرداری سریع مغزی چند پارامتری سریع با کنتراست-2020
One major thrust in radiology today is image standardization with a focus on rapidly acquired quantitative multi-contrast information. This is critical for multi-center trials, for the collection of big data and for the use of artificial intelligence in evaluating the data. Strategically acquired gradient echo (STAGE) imaging is one such method that can provide 8 qualitative and 7 quantitative pieces of information in 5 min or less at 3 T. STAGE provides qualitative images in the form of proton density weighted images, T1 weighted images, T2* weighted images and simulated double inversion recovery (DIR) images. STAGE also provides quantitative data in the form of proton spin density, T1, T2* and susceptibility maps as well as segmentation of white matter, gray matter and cerebrospinal fluid. STAGE uses vendors product gradient echo sequences. It can be applied from 0.35 T to 7 T across all manufacturers producing similar results in contrast and quantification of the data. In this paper, we discuss the strengths and weaknesses of STAGE, demonstrate its contrast-to-noise (CNR) behavior relative to a large clinical data set and introduce a few new image contrasts derived from STAGE, including DIR images and a new concept referred to as true susceptibility weighted imaging (tSWI) linked to fluid attenuated inversion recovery (FLAIR) or tSWI-FLAIR for the evaluation of multiple sclerosis lesions. The robustness of STAGE T1 mapping was tested using the NIST/NIH phantom, while the reproducibility was tested by scanning a given individual ten times in one session and the same subject scanned once a week over a 12-week period. Assessment of the CNR for the enhanced T1W image (T1WE) showed a significantly better contrast between gray matter and white matter than conventional T1W images in both patients with Parkinsons disease and healthy controls. We also present some clinical cases using STAGE imaging in patients with stroke, metastasis, multiple sclerosis and a fetus with ventriculomegaly. Overall, STAGE is a comprehensive protocol that provides the clinician with numerous qualitative and quantitative images.
Keywords: Quantitative magnetic resonance imaging | Susceptibility weighted imaging | T1 mapping | Quantitative susceptibility mapping | Multi-parametric magnetic resonance imaging | Strategically acquired gradient echo
French magistrates perception of the introduction of neuroscientific data in expert reports: Effects on the assessment of the expert’s report and criminal case
تصور دادرسان فرانسوی از معرفی داده های علوم اعصاب در گزارش های کارشناسی : تأثیرات ارزیابی گزارش کارشناسی و پرونده جنایی-2020
Objective. – To analyze whether the judge’s perception of the quality, and scientific basis of a psychiatric expert report of a criminal defendant can vary according to whether or not this evaluation includes neuroscientific data (a written description of a structural neuroimaging MRI scan) and their effects on the decisions made by judges. Experimental psychology has demonstrated a number of cognitive effects arising from exposure to neuroscientific explanations and/or neuroimaging data and which may bias judgments and lead to (mis)interpretations that can affect decisions. This research suggests that including neuroscience evidence in an expert report may impact they way the report is assessed by nonspecialists, such as judges, whose work requires them to take into account such reports. Method. – We conducted a study on 41 French judges in order to determine whether their perceptions of the expert report (objectivity, reliability, scientific basis, quality, relevance, credibility, and persuasiveness) and their assessment of risk of recidivism, link between the disorder and offense and the influence of expert report on their decision-making, vary according to whether or not the evaluation includes neuroscientific data. The magistrates had to read a clinical case, summarizing an expertise, with or without neuroscientific data, and then answer various closed (criteria were evaluated using 7-point Likert-scales) and open-ended questions (asking respondents to indicate the reasons underlying their Likert-scale responses). Half of the magistrates received report containing neuroscientific data and the other half a similar report, without this type of data. Quantitative analyses were carried out to assess the effect of the sample’s characteristics on the responses given and to compare the results between the two conditions (correlation analyses and Student T). Qualitative analyses, terminological and thematic, were also carried out. Results. – Quantitative and qualitative results show that the presence of neuroscience data in an expert report affects judges’ perceptions of the report and the magistrates’ perceptions of the link between disorder and offense. The judges considered the expert report including neuroscientific data to be more relevant, more objective, better quality, and more reliable than the report without such data. Furthermore, they found the expert’s arguments to be more persuasive and that these arguments had a greater scientific basis when the report included neuroscientific data than when such data was absent. Moreover, this phenomenon was stronger in more experienced magistrates than in less experienced magistrates. The qualitative finding shows a greater ability to recognize shortcomings in expert reports when they do not contain neuroscience data. The Expert reports including neuroscience data are perceived as more scientific and objective. Conclusion. – The presence of neuroscience data in an expert report affects judges’ perceptions of that report. These effects may be related to cognitive biases described in the literature, in particular the perceived scientific nature of neuroscience data. If judges are aware of their limits when it comes to assessing technical data, they appear relatively unaware that scientific data can induce cognitive biases and thereby affect their perceptions of expert reports.
Keywords: Criminal liability | Evaluation | Justice decision | Magistrate | Neuroscience | Psychiatric expertise
Detection and classification of bruises of pears based on thermal images
تشخیص و طبقه بندی کبودی گلابی بر اساس تصاویر حرارتی-2020
The detection and classification of bruises of pears based on thermal images have been investigated. A simple thermal imaging system in the long-wavelength ranges (8–14 μm) assembledμwith hot air equipment was constructed to capture cleaner images. Higher velocity and temperature of the air reduced the time required to obtain a clean image, but the images were not sufficient able to discriminate the slight and invisible variation of bruises over consecutive days. The grey-level co-occurrence matrix of the thermal images were analysed, and the slight differences in the pears over consecutive days were presented in the form of a line chart. A traditional deep learning algorithm commonly used in classification of big data sets was modified to one suitable for classification of a small sample data set of thermasl images (3246 samples were used as the training data set and 1125 were used as a test data set) collected from 300 pears over 10 days. The best test prediction accuracy obtained was 99.25%.
Keywords: Detection and classification | Thermal images | Grey-level co-occurrence matrix | Deep learning