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Boundary recognition plays a vital role in real-world scenarios like medical imaging and surveillance. The classical edge detector fails to preserve minute details in the image. The abdominal CT images were first analyzed using two edge detection techniques based on gauss gradient are proposed here for real-time data processing. The performance of the edge detectors is validated by performance metrics and verified for benchmark dataset images. The results reveal that the gauss gradient edge detector was efficient for the boundary extraction in benchmark and medical images. The VLSI implementation of the proposed gauss gradient edge detectors is done using the Kintex 7-FPGA board, hardware implementation also generates efficient results with reduced execution time.

With this manuscript the authors sought to write a succinct review of the origins, as well as the latest advancements in endoscopic spine surgery to serve as a reference frame for physicians looking to learn this approach.At its infancy, the indications for posterolateral and transforaminal endoscopic decompression remained narrow, which prevented the procedure from gaining rapid traction during those days. However, more recently the tides have turned and an increasing number of surgeons are starting to adopt this technique given all its advantages. With the advent of higher quality camera systems and instruments, indications to use a minimally invasive option have gotten significantly broader. The most basic indication for the use of this technology is a soft disc herniation causing compromise of a neural structure that has failed to be managed successfully with non-surgical therapies. The use of endoscopic techniques provides significant advantages to patient outcomes and patient recovery. Endoscopic procedures should not be used as a blanket approach to nerve root decompression, as they certainly have limitations. Most contraindications to this procedure are relative and serve mostly as points to consider when selecting the methods to address neural compression. As these techniques become more widely accepted, we expect its reach and indications to continue to broaden and diversify. The full integration of navigation technologies will likely leapfrog this procedure into the mainstream use.

Smart agriculture has been a promising model to supervise farms utilizing contemporary wireless technologies to enhance the quantity and quality of yield at the same time as minimizing the individual labor requirement. Also, the effective utilization of the sensors as communication components is the key one to monitor and manage soil, water, light, humidity, temperature. A mobile ad hoc sensor node comprises sensors to gather a real-time environment from the agricultural land with wireless communication technology and process the data before sharing information with other nodes in the network. On the other hand, the challenges have been enormously high path loss and lack of communication range under the environment when passing through the soil, sand, water, and other climatic conditions. As wireless sensor network (WSN) has self-organized and ad hoc wireless capability to monitor physical or environmental conditions, it can be used effectively in smart agriculture. As sensor nodes have been limited by means of power to be inactive mode always, the design of such energy-efficient agriculture WSN is a paramount issue. Hence, it has been planned to utilize the WSN as well as ubiquitous technology for smart agriculture with energy efficiency. With the purpose of building up a model, a ubiquitous agriculture mobile sensor network-based threshold built-in MAC routing protocol (TBMP) has been proposed to make it fit for minimal resource utilization by comparing with the existing protocols IMR and PTSR. The necessary resources for agriculture sensor network have been temperature, soil, and water. Also, the testing will be done to monitor changes in environmental surroundings in the agricultural land smartly to obtain maximum usage of the ubiquitous concept by applying existing and proposed protocols.

Background There is limited evidence to direct the management of unruptured intracranial aneurysms. Models extrapolated from existing data have been proposed to guide treatment recommendations. The aim of this study is to assess whether a consensus-based treatment score (UIATS) or rupture rate estimation model (PHASES) can be used to benchmark UK multi-disciplinary team (MDT) practice. Methods Prospective data was collected on a consecutive series of all patients with unruptured intracranial aneurysms (UIAs) presenting to a major UK neurovascular centre between 2012 and 2015. The agreement between the UIATS and PHASES scores, and their sensitivity and specificity in predicting the real-world MDT outcome were calculated and compared. Results A total of 366 patients (456 aneurysms) were included in the analysis. The agreement between UIATS and MDT recommendation was low (weighted kappa 0.26 [95% CI 0.19, 0.32]); sensitivity and specificity were also low at 36% and 52% respectively. Groups that the MDT allocated to treatment, equipoise or no treatment had significantly different PHASES scores (p = 0.004). There was no significant difference between the two scores when predicting patients for whom MDT outcome was to recommend aneurysm treatment, but the UIATS score was superior in predicting patients who received an MDT recommendation of ‘treatment-equipoise’, or ‘not-for-treatment’ (AUC of 0.73 compared to 0.59 for PHASES). Conclusions The models studied failed to agree with the consensus view of multi-disciplinary team in a major neurovascular centre. We conclude that decision support tools such as the UIATS and PHASES scores should not be blindly introduced in respective institutions without prior internal validation, as they may not represent the local reality.

This research article proposes high-performance square-root carry select adder (SQRT CSLA) architectures with high speed, area and energy efficiency when compared to the existing SQRT CSLA architectures. The first proposed method uses an optimized design of binary to excess-1 converter (BEC)-based SQRT CSLA by incorporating a carry enable binary to excess-1 converter (CEBEC) design that exploits a new logic optimization on the carry propagation path to improve speed of operation, area and energy efficiency. The second proposed method is an optimized design of the regular SQRT CSLA by employing the carry enable and add-one ripple carry adder (ARCA) architectures to decrease the number of gates. Simulation results show that the proposed CEBEC SQRT CSLA offers a savings of 22.81%, 9.95%, 7.95% and 3.98% on area, 14.50%, 5.21%, 3.72% and 3.11% in power consumption and offers 6.78%, 15.46%, 6.57% and 3.83% lesser delay, 20.33%, 19.92%, 10.09% and 6.89% lesser PDP, 28%, 23.85%, 13.78% and 7.58% lesser ADP than the existing regular, BEC SQRT CSLA, SQRT CSLA1 and SQRT CSLA2 architectures. The proposed ARCA SQRT CSLA architecture exhibits 9.26%, 17.71%, 9.06% and 6.39% lesser delay than the existing regular, BEC SQRT CSLA, SQRT CSLA1 and SQRT CSLA2 architectures.

Introduction and objectivesThe novel severe acute respiratory syndrome coronavirus 2 (COVID-19) pandemic has had drastic effects on global healthcare with the UK amongst the countries most severely impacted. The aim of this study was to examine how COVID-19 challenged the neurosurgical delivery of care in a busy tertiary unit serving a socio-economically diverse population.MethodsA prospective single-centre cohort study including all patients referred to the acute neurosurgical service or the subspecialty multidisciplinary teams (MDT) as well as all emergency and elective admissions during COVID-19 (18th March 2020–15th May 2020) compared to pre-COVID-19 (18th of January 2020–17th March 2020). Data on demographics, diagnosis, operation, and treatment recommendation/outcome were collected and analysed.ResultsOverall, there was a reduction in neurosurgical emergency referrals by 33.6% and operations by 55.6% during the course of COVID-19. There was a significant increase in the proportion of emergency operations performed during COVID-19 (75.2% of total,n=155) when compared to pre-COVID-19 (n= 198, 43.7% of total,p< 0.00001). In contrast to other published series, the 30-day perioperative mortality remained low (2.0%) with the majority of post-operative COVID-19-infected patients (n= 13) having underlying medical co-morbidities and/or suffering from post-operative complications.ConclusionThe capacity to safely treat patients requiring urgent or emergency neurosurgical care was maintained at all times. Strategies adopted to enable this included proactively approaching the referrers to maintain lines of communications, incorporating modern technology to run clinics and MDTs, restructuring patient pathways/facilities, and initiating the delivery of NHS care within private sector hospitals. Through this multi-modal approach we were able to minimize service disruptions, the complications, and mortality.

The role of compression is inevitable in the storage and transmission of medical images. The polynomial based image compression is proposed in this work for the compression of abdomen CT medical images. The input images are preprocessed by min–max normalization; the pixels are scanned and subjected to polynomial approximation. The polynomial approximated coefficients are subjected to llyods quantization and encoded by arithmetic coder. The medical image compression using Gaussian Hermite polynomial gives superior results when compared with the legendre polynomial based image compression and JPEG lossless compression techniques in terms of Peak to signal noise ratio (PSNR), Mean square Error (MSE) and other picture quality metrics. The algorithms are tested on real-time DICOM abdomen CT image and can be used for data transfer in teleradiology application.

The present work demonstrates the synthesis of new bio-based benzoxazine monomers via Mannich-like condensation of naturally occurring raw materials, for example, phloretic acid (PA) and furfurylamine (fa)/stearylamine (sa). The structure of the benzoxazine monomers has been established using proton nuclear magnetic resonance, carbon nuclear magnetic resonance and Fourier transform infrared spectroscopies. The monomers undergoes thermally activated ring opening polymerization to form polybenzoxazine networks, as revealed by non-isothermal differential scanning calorimetry, and the curing temperature for both was observed to be less than 473 K. Curing parameters of the developed monomers have also been compared with the reported bio-based monomers. The rheological behaviour of PA-fa monomer shows that the monomer has narrow processing window with liquefaction temperature at 426 K and gelation temperature at 437 K. Thermal degradation behaviour of polybenzoxazines was studied using thermogravimetric analysis which reveals that polybenzoxazine based on furfurylamine shows relatively high thermal stability and char yield which is credited to the additional cross-linking sites provided by the furan ring.

As digital cameras become more enhanced and small, CCD sensors can relate to only one color of a pixel. This color mosaic pattern is called as Bayer Pattern(BP) which requires processing to obtain a color image with a higher resolution. Each image pixel that undergoes interpolation has a full color spectrum based on surrounding pixel colors. Here we introduce Adaptive CFA(ACFA) interpolation model. For normal image regions hue technique is used while edge regions adapt the new technique. It is proposed to apply fuzzy logic and fuzzy rule which is based on Genetic Algorithm that uses random local search to enhance the PSNR. Medical image reconstruction by this proposed fuzzy based method outperforms the other medical image reconstruction methods.

This paper presents an effective traffic video surveillance system for detecting moving vehicles in traffic scenes. Moving vehicle identification process on streets is utilized for vehicle tracking, counts, normal speed of every individual vehicle, movement examination, and vehicle classifying targets and might be executed under various situations. In this paper, we develop a novel hybridization of artificial neural network (ANN) and oppositional gravitational search optimization algorithm (ANN–OGSA)-based moving vehicle detection (MVD) system. The proposed system consists of two main phases such as background generation and vehicle detection. Here, at first, we develop an efficient method to generate the background. After the background generation, we detect the moving vehicle using the ANN–OGSA model. To increase the performance of the ANN classifier, we optimally select the weight value using the OGSA algorithm. To prove the effectiveness of the system, we have compared our proposed algorithm with different algorithms and utilized three types of videos for experimental analysis. The precision of the proposed ANN–OGSA method has been improved over 3% and 6% than the existing GSA-ANN and ANN, respectively. Similarly, the GSA-ANN-based MVD system attained the maximum recall of 89%, 91%, and 91% for video 1, video 2, and video 3, respectively.

Selection of proton conducting membrane is currently a key factor that decides the performance of microbial fuel cell (MFC). Uniaxial pressed polysiloxane-derived ceramer and ceramic membrane with proton conducting fillers like montmorillonite and H3PMo12O40/SiO2 were applied for the first time as separator in MFC. Here, we present a series of polymer-derived ceramic membranes tailored based on pyrolysis temperature and filler addition, in which ion exchange capacity, cation transport number, and oxygen permeability are influenced through the hydrophilic and porous structural property. The maximum power density of MFC with polysiloxane-derived ceramer membrane modified with 20 wt% montmorillonite and 10 wt% H3PMo12O40/SiO2 reached a value of 5.66 W m−3, which was four times higher than that with non-modified polysiloxane-derived ceramer membrane. Furthermore, the specific power recovery per unit cost of the membrane was found to be 2-fold higher than MFC using polymeric Nafion membrane. In contrast, MFC with polysiloxane-derived ceramic membrane modified with 20 wt% montmorillonite delivers 1.2 times lower power density (4.20 W m−3) than that with non-modified macroporous polysiloxane-derived ceramic membrane. Hence, the findings demonstrated that tailoring the hydrophilic and porous structure of the ceramic membrane is a new and promising approach to enhance the performance of MFC.

In practical applications, speaker verification systems have to be developed and trained using data which is outside the domain of the intended application as the collection of significant amount of in-domain data could be difficult. Experimental studies have found that when a GPLDA system is trained using out-domain data, it significantly affects the speaker verification performance due to the mismatch between development data and evaluation data. This paper proposes several unsupervised inter-dataset variability compensation approaches for the purpose of improving the performance of GPLDA systems trained using out-domain data. We show that when GPLDA is trained using out-domain data, we can improve the performance by as much as 39% by using by score normalisation using small amounts of in-domain data. Also in situations where rich out-domain data and only limited in-domain data are available, a pooled-linear-weighted technique to estimate the GPLDA parameters shows 35% relative improvements in equal error rate (EER) on int–int conditions. We also propose a novel inter-dataset covariance normalization (IDCN) approach to overcome in- and out-domain data mismatch problem. Our unsupervised IDCN-compensated GPLDA system shows 14 and 25% improvement respectively in EER over out-domain GPLDA speaker verification on tel–tel and int–int training–testing conditions. We provide intuitive explanations as to why these inter-dataset variability compensation approaches provide improvements to speaker verification accuracy.

FPGA design for complex applications need high capacity of configuration memory. To fullfil the large memory requirement, higher end FPGAs are required and it leads to higher cost. In order to reduce the cost constraint, bit-stream compression is prominently involved to reduce the bit-stream size and the memory requirement of FPGA configuration. In this paper new code compression techniques are proposed with minimum cost. The proposed code compression techniques RG-1 and RG-2 codes are designed based on the combination of run length and Golomb coding. The proposed RG codes overcome the limitation of both run length and Golomb coding techniques. The main contribution of this work is to analyze the proposed work in terms of number of 1’s, number of transitions and size of compressed bits. The comparison result shows that the RG code is more robust when compared to other traditional code compression techniques. The results shows that CR improvement of 9 and 5% compare with RLE for the RG-1 and RG-2 respectively and CR improvement of 7 and 2% compare with golomb for the RG-1 and RG-2 respectively.

Non-steroidal anti-inflammatory drugs (NSAIDs) play an important role in postoperative pain management. However, their use in the setting of spine fusion surgery setting has long been a topic of controversy. In this review we examined relevant research, including in vivo, animal, and clinical human studies, with the aim of understanding the effect of NSAIDs on spinal fusion. Systematic review of study designs of all types from randomized controlled trials and meta-analyses to single-institution retrospective reviews. A search of PubMed and Embase was conducted using the keywords: “spine,” “spinal fracture,” NSAIDs, anti-inflammatory non-steroidal agents, bone, bone healing, fracture, fracture healing, yielding a total of 110 studies. Other 28 studies were identified by cross-referencing, resulting in total 138 studies. There is no level I evidence from human studies regarding the use of NSAIDs on spinal fusion rates. The overall tone of the spine literature in the early 2000s was that NSAIDs increased the rate of non-union; however, nearly all human studies published after 2005 suggest that short-term (

This paper studies the performance degradation of Gaussian probabilistic linear discriminant analysis (GPLDA) speaker verification system, when only short-utterance data is used for speaker verification system development. Subsequently, a number of techniques, including utterance partitioning and source-normalised weighted linear discriminant analysis (SN-WLDA) projections are introduced to improve the speaker verification performance in such conditions. Experimental studies have found that when short utterance data is available for speaker verification development, GPLDA system overall achieves best performance with a lower number of universal background model (UBM) components. As a lower number of UBM components significantly reduces the computational complexity of speaker verification system, that is a useful observation. In limited session data conditions, we propose a simple utterance-partitioning technique, which when applied to the LDA-projected GPLDA system shows over 8% relative improvement on EER values over baseline system on NIST 2008 truncated 10---10 s conditions. We conjecture that this improvement arises from the apparent increase in the number of sessions arising from our partitioning technique and this helps to better model the GPLDA parameters. Further, partitioning SN-WLDA-projected GPLDA shows over 16% and 6% relative improvement on EER values over LDA-projected GPLDA systems respectively on NIST 2008 truncated 10---10 s interview-interview, and NIST 2010 truncated 10---10 s interview-interview and telephone-telephone conditions.

Purpose of review The aim of this review is to provide the theoretical and practical knowledge essential for non-radiologists to develop the skills necessary to apply thoracic ultrasound as an extension of clinical assessment and intervention. Recent findings Issues relating to training and competence are discussed and a library of thoracic ultrasound videos is provided to illustrate artefacts, pleural, parenchymal and pneumothorax pathology as well as important pitfalls to consider. Novel and future diagnostic applications of thoracic ultrasound in the setting of acute cardiorespiratory pathology including consolidation, acute interstitial syndromes and pulmonary embolism are explored. Summary Thoracic ultrasound requires an understanding of imaging artefact specific to lung and pleura and a working knowledge of machine knobology for image optimisation and interpretation. Ultrasound is a valuable tool for the practicing chest clinician providing diagnostic information for the assessment of pleural and parenchymal disease and increased safety and cost effectiveness of thoracic interventions. Electronic supplementary material The online version of this article (doi:10.1007/s13665-017-0164-1) contains supplementary material, which is available to authorized users.

To investigate the relationship between lumbar facet fluid and dynamic instability in degenerative spondylolisthesis (DS), as well as the relationship between facet fluid and patient-reported outcomes following a posterior lumbar fusion. We analyzed consecutive patients with degenerative spondylolisthesis undergoing single level posterior lumbar fusion from December 2010 to January 2013 at a single academic institution. We investigated the relationship between fluid in the facet joint as measured on axial MRI and the presence of dynamic instability. We investigated the impact of facet fluid, Modic changes, and dynamic instability on patient-reported outcomes. There was a significant association between the amount of facet joint fluid and the presence of dynamic instability (p = 0.03); as facet fluid increases, the probability of dynamic instability also increases. For every 1 mm of facet fluid, there was a 41.6 % increase (95 % CI 1.8–97) in the odds of dynamic instability. A facet fluid amount less than 0.5 mm gave a 90 % probability that there was no dynamic instability. The presence of facet fluid and dynamic instability were associated with achieving minimal clinical important difference (MCID) in low back pain following lumbar fusion (p = 0.04 and 0.05, respectively). Facet joint fluid is associated with the presence of dynamic instability in DS. The presence of facet fluid and dynamic instability may predict increased likelihood of achieving MCID for improvement in back pain following posterior lumbar fusion.

To compare the image quality between fine focal spot size (FFSS) and standard focal spot size (SFSS) in computed tomography of the abdomen and pelvis (CTAP) This retrospective review included all consecutive adult patients undergoing contrast-enhanced CTAP between June and September 2014. Two blinded radiologists assessed the margin clarity of the abdominal viscera and the detected lesions using a five-point grading scale. Cohen’s kappa test was used to examine the inter-observer reliability between the two reviewers for organ margin clarity. Mann–Whitney U testing was utilised to assess the statistical difference of the organ and lesion margin clarity. 100 consecutive CTAPs were recruited. 52 CTAPs were examined with SFSS of 1.1 × 1.2 mm and 48 CTAPs were examined with FFSS of 0.6 × 0.7 mm. Results showed that there was substantial agreement for organ margin clarity (mean κ = 0.759, p

This study was performed to evaluate the efficacy of a novel computed tomography (CT) liver detection algorithm (LDA), which allows for targeted increase of radiation dose to the upper abdomen, on image quality of the liver. We retrospectively evaluated the LDA by comparing 40 consecutive patients who had portal venous CT abdomen performed without use of the algorithm, to 40 patients in whom the algorithm was used. Image quality was assessed objectively by comparing the standard deviation (SD) of attenuation values in Hounsfield units (HU) of the abdominal organs. Qualitative analysis was performed by two blinded radiologists who independently graded the image quality of abdominal organs There was significant noise reduction in the liver (P