Optimal detection and classification of grid connected system using MSVM-FSO technique

This paper, a hybrid method, is proposed for protecting the hybrid photovoltaic (PV) and wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the multiple support vector machine (MSVM) and firebug swarm optimization (FSO), commonly named as MSVM-FSO method. The proposed technique is diagnosing the appropriate fault occurring in the hybrid system. The main purpose of the proposed system is to assure the system with lower complexity for the fault diagnosis and detection (FDD) for improving the power quality (PQ) of hybrid method. Here, the MSVM approach is used to detect the fault conditions of grid-tied system. To evaluate the events of voltages, fault and the currents of hybrid systems are analyzed at the feeder of buses. The FSO categorizes the types of fault, which is occurred in grid-connected system. By then, the proposed method's performance is done in the MATLAB software and it is contrasted with different existing methods. From this, the proposed method provides accuracy as 99.7% and efficiency as 98%, which is high compared to existing methods.

Entropy-based grid approach for handling outliers: a case study to environmental monitoring data

Grid-based approaches render an efficient framework for data clustering in the presence of incomplete, inexplicit, and uncertain data. This paper proposes an entropy-based grid approach (EGO) for outlier detection in clustered data. The given hard clusters obtained from a hard clustering algorithm, EGO uses entropy on the dataset as a whole or on an individual cluster to detect outliers. EGO works in two steps: explicit outlier detection and implicit outlier detection. Explicit outlier detection is concerned with those data points that are isolated in the grid cells. They are either far from the dense region or maybe a nearby isolated data point and therefore declared as an explicit outlier. Implicit outlier detection is associated with the detection of outliers that are perplexedly deviated from the normal pattern. The determination of such outliers is achieved using entropy change of the dataset or a specific cluster for each deviation. The elbow based on the trade-off between entropy and object geometries optimizes the outlier detection process. Experimental results on CHAMELEON datasets and other similar datasets suggested that the proposed approach(es) detect the outliers more precisely and extend the capability of outliers detection to an additional 4.5% to 8.6%. Moreover, the resultant clusters became more precise and compact when the entropy-based gridding approach is applied on top of hard clustering algorithms. The performance of the proposed algorithms is compared with well-known outlier detection algorithms, including DBSCAN, HDBSCAN, RE3WC, LOF, LoOP, ABOD, CBLOF and HBOS. Finally, a case study for detecting outliers in environmental data has been carried out using the proposed approach and results are generated on our synthetically prepared datasets. The performance shows that the proposed approach may be an industrial-oriented solution to outlier detection in environmental monitoring data.

Accuracy of Leg Length and Hip Offset Measurements Using a Fluoroscopic Grid During Anterior Approach Total Hip Arthroplasty

Background

Minimizing leg length (LLD) and hip offset (OD) discrepancies is critical for tissue tension and implant longevity in total hip arthroplasty (THA). The direct anterior approach (DAA) helps surgeons recreate these values under fluoroscopy. Several methods to accomplish this have been described, with no consensus on which is superior. This study evaluated the ability to minimize LLD and OD using a surgeon-controlled, adjustable fluoroscopic grid. We hypothesized that this tool would recreate parameters to within 10 mm of the contralateral side.

Methods

One hundred eleven primary THAs performed with an adjustable radiopaque grid to equalize leg length and hip offset were retrospectively reviewed. These values were measured on postoperative radiographs and compared to the contralateral hip. Patients were excluded if they had inadequate imaging, revision arthroplasty, preexisting deformities, or underwent approaches other than DAA.

Results

Mean age was 59.1 ± 11.1 years, 63.1% of patients were female, and average body mass index was 27.8 ± 7.0. Mean LLD was 3.7 ± 3.0 mm, while mean OD was 4.6 ± 3.6 mm. 95.5% of hips showed LLD < 10 mm, while 93.7% of hips had OD < 10 mm. Furthermore, 76.6% of hips had LLD < 5 mm, while 62.2% of hips had OD < 5 mm.

Conclusions

The described technique restored limb length and hip offset during DAA THA. This technique yields consistent results and offers an inexpensive alternative to costly digital software and more cumbersome fixed grid systems.

Power quality improvement of a proposed grid-connected hybrid system by load flow analysis using static var compensator

Renewable resources are most effective for sustainable development of society and economically efficient for small-scale power generation. However, grid integration is challenging because of the randomness of the source effects on power system parameters. This work proposes power quality enhancement by incorporating Static VAR Compensator (SVC) in a grid-integrated renewable hybrid power system. SVC is one of the shunt type Flexible AC Transmission Systems (FACTS) devices that is adopted in this system for the compensation of reactive power requirement. The proposed hybrid system for the Rohingya Refugee camp is energized by a wind and solar based sources. The objective is to enhance the overall bus voltage profile by minimizing both real and reactive power losses as well as boost the power transmission capability of the entire system. Different case studies have been considered by changing the source availability and generation supply for load flow analysis using ETAP software. Moreover, critical system parameters such as bus voltage, power transfer capacity, and power losses have been reported during the inactive time of one or both renewable sources. The results obtained without SVC have been compared against the ones with the presence of SVC. Our analysis reveals that, as a result of using SVC, the voltage profile improves by 2.9-3.3%, branch loss reduces by 2.1-2.4%, and power transfer capability enhances by 7.5-9 units.

The principles and effectiveness of X-ray scatter correction software for diagnostic X-ray imaging: A scoping review

PURPOSE

An anti-scatter grid is often used in X-ray radiography to reduce the scattered X-rays generated from the patient. However, the presence of a grid means the patient dose subsequently increases. Recently,severalmanufacturers have developedsoftwarethat is capable of correctingfor scattered X-rays withouttheuse ofa conventional grid. This scoping review aims to systematically map the research assessing scattering correction software and to identify any existing knowledge gaps.

METHODS

This scoping review involved conducting a systematic search in PubMed, Scopus, and Web of science to reveal studies that were relevant to the research question. Articles published between 01.01.2000 and 31.12.2021 examining X-ray scatter correction software for X-ray imaging were included. A part of the PRISMA model and PICO framework were utilised to establish eligibility criteria. A structured summary table was utilised to extract data from the selected articles.

RESULTS

In this scoping review, 20 years of literature in X-ray conventional radiography. 11 articles were included in the data synthesis. The study populations of the included studies were varied: patients, image quality phantoms and anatomical phantoms. The clinical applications of X-ray scatter correction software were found to be limited to specific body parts (cervical spine, chest, shoulder, lumbar spine, hip and pelvis). The scatter correction software appears to be effective in terms of image quality and in reducing the radiation dose. However, the conventional grid still provides a higher image quality.

CONCLUSIONS

X-ray scatter correction software can be effective and provides potentialbenefits for some circumstances or clinical scenarios.

Component placement accuracy of two digital intraoperative fluoroscopy supplementation systems in direct anterior total hip arthroplasty

INTRODUCTION

Intraoperative fluoroscopy (IF) may increase accuracy of component placement when performing direct anterior approach total hip arthroplasty (THA), however, unguided IF continues to produce inconsistent results. Supplementation of IF, with a digital grid (Grid) system or digital overlay (Overlay), may increase component placement accuracy. The purpose of this study was to compare component placement accuracy following THA when IF was supplemented with the Grid or Overlay technique.

MATERIALS AND METHODS

Acetabular abduction and anteversion, with leg length discrepancy (LLD) and global hip offset (GHO) were retrospectively evaluated for unilateral and bilateral THA patients from 6-week post-operative radiographs. Target component placement were GHO and LLD < 10 mm, abduction 45° ± 10° and anteversion 15° ± 10° for Overlay and 17° ± 10° for Grid. Differences between the Overlay and Grid were determined by univariate analyses.

RESULTS

The Overlay and Grid groups included 178 patients (217 hips) and 262 patients (317 hips), respectively. Target placement with the Overlay and Grid was achieved for GHO in 98.3% and 95.7% of cases (p = 0.108), LLD in 100% and 98.4% of cases (p = 0.121), cup abduction in 98.2% and 97.4% of cases (p = 0.384), and cup anteversion in 97.7% and 71.1% of cases (p < 0.001), respectively. Surgical time was significantly longer in Overlay compared to Grid (Unilateral 77.5 ± 14.1 min and 68.8 ± 12.2; p < 0.001; Bilateral 184.6 ± 27.0 min and 165.5 ± 23.1; p < 0.001, respectively).

CONCLUSION

Although no difference was found between the Grid and the Overlay cohorts for LLD, GHO or abduction angle, the Overlay resulted in greater accuracy for acetabular component anteversion angle, with only a slight decrease in surgical efficiency.

Integrated wafer-scale manufacturing of electron cryomicroscopy specimen supports

We present a process for the manufacture of electron cryomicroscopy (cryoEM) specimen supports with an integrated foil-grid structure, using cryogenic vacuum evaporation (cryoEvap) and patterned electroplating on a silicon wafer substrate. The process is designed to produce a pattern of nanometre scale holes in a thin metal foil, which is attached to a pattern of micrometre scale grid bars that support it and allow handling of the millimetre scale device. All steps are carried out on a single 4 inch (100 mm) silicon wafer, without any need to handle individual grids during processing, and yield about 600 supports per wafer. The approach is generally applicable to the problem of creating a thin foil with nanometre scale features and a micrometre scale support structure; here it is used to make an all gold, HexAuFoil type design. It also allows for the addition of custom fiducial markers and patterns which aid in locating and identifying particular regions of a grid at several length scales: by eye, in an optical microscope, and in the electron microscope. Implemented at scale, this manufacturing process can supply ample grids to support the continued growth of cryoEM for determining the structure of biological molecules.

FIUS: Fixed partitioning undersampling method

BACKGROUND AND OBJECTIVE

In the medical field, data techniques for prediction and finding patterns of prevalent diseases are of increasing interest. Classification is one of the methods used to provide insight into predicting the future onset of type 2 diabetes of those at high risk of progression from pre-diabetes to diabetes. When applying classification techniques to real-world datasets, imbalanced class distribution has been one of the most significant limitations that leads to patients' misclassification. In this paper, we propose a novel balancing method to improve the prediction performance of type 2 diabetes mellitus in imbalanced electronic medical records (EMR).

METHODS

A novel undersampling method is proposed by utilizing a fixed partitioning distribution scheme in a regular grid. The proposed approach retains valuable information when balancing methods are applied to datasets.

RESULTS

The best AUC of 80% compared to other classifiers was obtained from the logistic regression (LR) classifier for EMR by applying our proposed undersampling method to balance the data. The new method improved the performance of the LR classifier compared to existing undersampling methods used in the balancing stage.

CONCLUSION

The results demonstrate the effectiveness and high performance of the proposed method for predicting diabetes in a Canadian imbalanced dataset. Our methodology can be used in other areas to overcome the limitations of imbalanced class distributions.

BION'S GRAPH OF "IN SEARCH OF EXISTENCE"

If we want to understand Bion's psychoanalysis and analytic field theory, its most creative development, there is one point we must always bear in mind. Bion conceives individual therapy as group therapy. Consequently, he invites the analyst to put the patient's past and related causal theories in the background. Rather she should focus on the emotional transformations that occur in the here and now. This is very different from observing the Freudian principles of oneiric and transference distortion, on the one hand, and the (re)construction of the patient's past history, on the other. It is also different from paying attention to so-called deep unconscious fantasies or enactments. Such a crucial aspect, though, is often misunderstood. Here the concepts of the grid and of the regression or "in search of existence" graph are employed as a way of clarifying it. Trying at any given moment to grasp the direction of the vector that represents the sum of the emotional turbulences affecting the field, whether regressive or progressive (in other words, whether reflecting the growth of the mind or its destruction), implies using a radical technique to achieve receptiveness to the unconscious. The analyst treats all narratives in the session as if they were the recounting of a dream dreamt by the analytic dyad or group of two. A few clinical vignettes are presented by way of illustration.

Stereotactic Electroencephalography Is Associated With Reduced Pain and Opioid Use When Compared with Subdural Grids: A Case Series

BACKGROUND

Minimally invasive surgery (MIS) has been shown to decrease length of hospital stay and opioid use.

OBJECTIVE

To identify whether surgery for epilepsy mapping via MIS stereotactically placed electroencephalography (SEEG) electrodes decreased overall opioid use when compared with craniotomy for EEG grid placement (ECoG).

METHODS

Patients who underwent surgery for epilepsy mapping, either SEEG or ECoG, were identified through retrospective chart review from 2015 through 2018. The hospital stay was separated into specific time periods to distinguish opioid use immediately postoperatively, throughout the rest of the stay and at discharge. The total amount of opioids consumed during each period was calculated by transforming all types of opioids into their morphine equivalents (ME). Pain scores were also collected using a modification of the Clinically Aligned Pain Assessment (CAPA) scale. The 2 surgical groups were compared using appropriate statistical tests.

RESULTS

The study identified 43 patients who met the inclusion criteria: 36 underwent SEEG placement and 17 underwent craniotomy grid placement. There was a statistically significant difference in median opioid consumption per hospital stay between the ECoG and the SEEG placement groups, 307.8 vs 71.5 ME, respectively (P = .0011). There was also a significant difference in CAPA scales between the 2 groups (P = .0117).

CONCLUSION

Opioid use is significantly lower in patients who undergo MIS epilepsy mapping via SEEG compared with those who undergo the more invasive ECoG procedure. As part of efforts to decrease the overall opioid burden, these results should be considered by patients and surgeons when deciding on surgical methods.

In-vitro and particle image velocimetry studies of dry powder inhalers

Inhalation drug delivery has seen a swift rise in the use of dry powder inhalers (DPIs) to treat chronic respiratory conditions. However, universal adoption of DPIs has been restrained due to their low efficiencies and significant drug losses in the mouth-throat region. Aerosol efficiency of DPIs is closely related to the fluid-dynamics characteristics of the inhalation flow generated from the devices, which in turn are influenced by the device design. In-vitro and particle image velocimetry (PIV) have been used in this study to assess the aerosol performance of a model carrier formulation delivered by DPI devices and to investigate their flow characteristics. Four DPI device models, with modification to their tangential inlets and addition of a grid, have been explored. Similar aerosol performances were observed for all four device models, with FPF larger than 50%, indicating desirable lung deposition. A high swirling and recirculating jet-flow emerging from the mouthpiece of the DPI models without the grid was observed, which contributed to particle deposition in the throat. DPI models where the grid was present showed a straightened outflow without undesired lateral spreading, that reduced particle deposition in the throat and mass retention in the device. These findings demonstrate that PIV measurements strengthen in-vitro evaluation and can be jointly used to develop high-performance DPIs.

Enhanced response of radioresistant carcinoma cell line to heterogeneous dose distribution of grid; the role of high-dose bystander effect

PURPOSE

The classical dogma that restricted the radiation effect to the directly irradiated cells has been challenged by the bystander effect. This off-target phenomenon which was manifested in adjacent cells via signaling of fully exposed cells might be involved in high-dose Grid therapy as well. Here, an in-vitro study was performed to examine the possible extent of carcinoma cells response to the inhomogeneous dose distribution of Grid irradiation in the context of the bystander effect.

MATERIALS AND METHODS

Bystander effect was investigated in human carcinoma cell lines of HeLa and HN5 adjacent to those received high-dose Grid irradiation using 'medium transfer' and 'cell-to-cell contact' strategies. Based on the Grid peak-to-valley dose profile, medium transfer was exerted from 10 Gy uniformly exposed donors to 1.5 Gy uniformly irradiated recipients. Cell-contact bystander was evaluated after nonuniform dose distribution of 10 Gy Grid irradiation using cloning cylinders. GammaH2AX foci, micronucleus and clonogenic assays besides gene expression analysis were performed.

RESULTS

Various parameters (ɑ/β, D37, D50) extracted from survival curve which fitted to the Linear Quadratic model, verified more radioresistance of HN5. Survival fraction at 2 Gy (SF2) indicated as 0.42 ± 0.06 in HeLa and 0.5 ± 0.03 in HN5. The level of survival decrease, DNA damages and micronucleus of cells located in the Grid shielded areas (1.5 Gy cell-to-cell contact bystander cells) were significantly more than the values obtained from cells which were irradiated by merely uniform dose of 1.5 Gy. The gH2AX foci and micronuclei frequencies were enhanced in cell-contact bystander approximately more than 1.8 times. Relative expression of DNA damage repair pathway genes (Xrcc6 and H2afx) in bystander cells increased significantly. The most cell survival reduction (11.6 times) was revealed in the Grid bystander cells of radioresistant cell line (HN5). No statistically significant difference between 10 Gy uniform beam and Grid non-uniform beam was observed.

CONCLUSIONS

Various endpoints confirmed an augmented response of cells in the valley dose region of the Grid block significantly (compared with the cells irradiated by identical dose of uniform beam), suggesting the role of high-dose bystander effect which was more pronounced in resistant carcinoma cell lines. These findings could provide a partial explanation for the Grid beneficial response seen in a number of pre-clinical and clinical studies.

Quantification of gear inflicted damages on trawl-caught haddock in the Northeast Atlantic fishery

External damages are indicators of the overall quality of fish and fish welfare. Haddock is an important commercial species widespread in the North Atlantic, but few studies related to quality have been carried out on this species. We studied the levels of external damages on haddock captured with a demersal trawl in the Northeast Atlantic. Further, we investigated to what extent the compulsory sorting grid and diamond mesh codend gear configuration employed in this trawl fishery is responsible for the external damages observed during the capture process. We evaluated external damages on 563 haddock captured over 22 hauls. In general, the results showed that catching haddock without any gear inflicted damages using demersal trawls is challenging. However, the results also showed that the severity of most damages is low and the probability to catch haddock with no external damage can be significantly increased removing the grid and changing codend design.

Building a Nest by an Automaton

A robot modeled as a deterministic finite automaton has to build a structure from material available to it. The robot navigates in the infinite oriented grid Z × Z . Some cells of the grid are full (contain a brick) and others are empty. The subgraph of the grid induced by full cells, called the shape, is initially connected. The (Manhattan) distance between the furthest cells of the shape is called its span. The robot starts at a full cell. It can carry at most one brick at a time. At each step it can pick a brick from a full cell, move to an adjacent cell and drop a brick at an empty cell. The aim of the robot is to construct the most compact possible structure composed of all bricks, i.e., a nest. That is, the robot has to move all bricks in such a way that the span of the resulting shape be the smallest. Our main result is the design of a deterministic finite automaton that accomplishes this task and subsequently stops, for every initially connected shape, in time O ( s n ) , where s is the span of the initial shape and n is the number of bricks. We show that this complexity is optimal.

PYTAF: A Python Tool for Spatially Resampling Earth Observation Data

Earth observation data have revolutionized Earth science and significantly enhanced the ability to forecast weather, climate and natural hazards. The storage format of the majority of Earth observation data can be classified into swath, grid or point structures. Earth science studies frequently involve resampling between swath, grid and point data when combining measurements from multiple instruments, which can provide more insights into geophysical processes than using any single instrument alone. As the amount of Earth observation data increases each day, the demand for a high computational efficient tool to resample and fuse Earth observation data has never been greater. We present a software tool, called pytaf, that resamples Earth observation data stored in swath, grid or point structures using a novel block indexing algorithm. This tool is specially designed to process large scale datasets. The core functions of pytaf were implemented in C with OpenMP to enable parallel computations in a shared memory environment. A user-friendly python interface was also built. The tool has been extensively tested on supercomputers and successfully used to resample the data from five instruments on the EOS-Terra platform at a mission-wide scale.

Development of a deep learning-based method to identify "good" regions of a cryo-electron microscopy grid

Recent advances in cryo-electron microscopy (cryo-EM) have enabled protein structure determination at atomic resolutions. Cryo-EM specimens are prepared by rapidly freezing a protein solution on a metal grid coated with a holey carbon film; this results in the formation of an ice film on each hole. The thickness of the ice film is a critical factor for high-resolution structure determination; ice that is too thick degrades the contrast of the protein image while ice that is too thin excludes the protein from the hole or denatures the protein. Therefore, trained researchers need to manually select "good" regions with appropriate ice thicknesses for imaging. To reduce the time spent on such tasks, we developed a deep learning program consisting of a "detector" and a "classifier" to identify good regions from low-magnification EM images. In our method, the holes in a low-magnification EM image are detected via a detector, and the ice image on each hole is classified as either good or bad via a classifier. The detector detected more than 95% of the holes regardless of the type of samples. The classifier was trained for different types of samples because the appropriate ice thickness varies between sample types. The accuracies of the classifiers were 93.8% for a soluble protein sample (β-galactosidase) and 95.3% for a membrane protein sample (bovine heart cytochrome c oxidase). In addition, we found that a training data set containing ~ 2100 hole images from 300 low-magnification EM images was sufficient to obtain good accuracy, such as higher than 90%. We expect that the throughput of the cryo-EM data collection step will be greatly improved by using our method.

Removing uncertainty in neural networks

Neuroscientists draw lines of separation among structures and functions that they judge different, arbitrarily excluding or including issues in our description, to achieve positive demarcations that permits a pragmatic treatment of the nervous activity based on regularity and uniformity. However, uncertainty due to disconnectedness, lack of information and absence of objects' sharp boundaries is a troubling issue that prevents these scientists to select the required proper sets/subsets during their experimental assessment of natural and artificial neural networks. Starting from the detection of metamorphoses of shapes inside a Euclidean manifold, we propose a technique to detect the topological changes that occur during their reciprocal interactions and shape morphing. This method, that allows the detection of topological holes development and disappearance, makes it possible to solve the problem of uncertainty in the assessment of countless dynamical phenomena, such as cognitive processes, protein homeostasis deterioration, fire propagation, wireless sensor networks, migration flows, and cosmic bodies analysis.

How computational chemistry develops: a tribute to Peter Goodford

This editorial discusses the foundation of aspects of computational chemistry and is a tribute to Peter Goodford, one of those founders, who recently passed away. Several colleagues describe Professor Goodford's work and the person himself.

Simulating unmanned aerial vehicle flight control and collision detection

An unmanned aerial vehicle (UAV) is a small, fast aircraft with many useful features. It is widely used in military reconnaissance, aerial photography, searches, and other fields; it also has very good practical-application and development prospects. Since the UAV’s flight orientation is easily changeable, its orientation and flight path are difficult to control, leading to its high damage rate. Therefore, UAV flight-control technology has become the focus of attention. This study focuses on simulating a UAV’s flight and orientation control, and detecting collisions between a UAV and objects in a complex virtual environment. The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment. A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper, to improve the system performance and accelerate the collision-detection process. This provides a practical method for future studies on UAV flight position and orientation control, collision detection, etc.

Quantitative analysis of effects of the grid specifications on the quality of digital radiography images

A grid is one of the key components of a digital radiography (DR) system because it removes scattered radiation, which arises when X-rays penetrate an object and improves diagnostic accuracy by enhancing image quality. With the widespread use of DR systems, demand for grids with high precision has simultaneously increased. Because unsuitable grids may decrease image quality and lead to misdiagnosis, using optimised grids for DR systems is critical. In this study, we aimed to analyse the quality of X-ray images acquired using grids with different specifications and proposed standardised criteria for grid use on the basis of our results. We measured modulation transfer function (MTF), normalised noise power spectrum (NNPS) and detective quantum efficiency (DQE) using grids with different ratios (10:1, 12:1 and 15:1) with or without implementing poly methyl methacrylate (PMMA) phantoms (0-20 cm). Pixel pitch of the detector used in this experiment was 143 μm. Based on this, a grid with a line frequency of 85 line pairs/cm was selected to prevent distortion caused by implementing unoptimised grids. As a result, the NNPS was found to increase when using the grid, and the difference in MTF and DQE was only measured when the scattered X-ray was generated by stacking the PMMA phantom. However, grids showed a positive effect MTF and DQE when the PMMA phantom was implemented. Specifically, MTF and DQE improved with increase in grid ratio. Thus, it is desirable to use a high-ratio grid to improve image quality.

Enhanced co-registration methods to improve intracranial electrode contact localization

Background

Electrode contact locations are important when planning tailored brain surgeries to identify pathological tissue targeted for resection and conversely avoid eloquent tissue. Current methods employ trained experts to use neuroimaging scans that are manually co-registered and localize contacts within ~2 mm. Yet, the state of the art is limited by either the expertise needed for each type of intracranial electrode or the inter-modality co-registration which increases error, reducing accuracy. Patients often have a variety of strips, grids and depths implanted; therefore, it is cumbersome and time-consuming to apply separate localization methods for each type of electrode, requiring expertise across different approaches.

New method

To overcome these limitations, a computational method was developed by separately registering an implant magnetic resonance image (MRI) and implant computed tomography image (CT) to the pre-implant MRI, then calculating an iterative closest point transformation using the contact locations extracted from the signal voids as ground truth.

Results

The implant MRI is robustly co-registered to the pre-implant MRI with a boundary-based registration algorithm. By extracting and utilizing ‘signal voids’ (the metal induced artifacts from the implant MRI) as electrode fiducials, the novel method is an all-in-one approach for all types of intracranial electrodes while eliminating inter-modality co-registration errors.

Comparison with existing methods

The distance between each electrode centroid and the brain's surface was measured, for the proposed method as well as the state of the art method using two available software packages, SPM 12 and FSL 4.1. The method presented here achieves the smallest distances to the brain's surface for all strip and grid type electrodes, i.e. contacts designed to rest directly on the brain surface.

Conclusion

We use one of the largest reported sample sizes in localization studies to validate this novel method for localizing different kinds of intracranial electrodes including grids, strips and depth electrodes.

•

Co-registration between intramodal pre- and implant images allows for accurate localization of all subdural electrode types.

•

Iterative closest point (ICP) assisted grid electrode localization is comparable to existing implant MRI based methods.

•

ICP is a novel, semi-automated method to localize grid, strip and depth electrodes with state-of-the-art accuracy

The Potential Role of Grid-Like Software in Bedside Chest Radiography in Improving Image Quality and Dose Reduction: An Observer Preference Study

Objective

To compare the observer preference of image quality and radiation dose between non-grid, grid-like, and grid images.

Materials and Methods

Each of the 38 patients underwent bedside chest radiography with and without a grid. A grid-like image was generated from a non-grid image using SimGrid software (Samsung Electronics Co. Ltd.) employing deep-learning-based scatter correction technology. Two readers recorded the preference for 10 anatomic landmarks and the overall appearance on a five-point scale for a pair of non-grid and grid-like images, and a pair of grid-like and grid images, respectively, which were randomly presented. The dose area product (DAP) was also recorded. Wilcoxon's rank sum test was used to assess the significance of preference.

Results

Both readers preferred grid-like images to non-grid images significantly (p < 0.001); with a significant difference in terms of the preference for grid images to grid-like images (p = 0.317, 0.034, respectively). In terms of anatomic landmarks, both readers preferred grid-like images to non-grid images (p < 0.05). No significant differences existed between grid-like and grid images except for the preference for grid images in proximal airways by two readers, and in retrocardiac lung and thoracic spine by one reader. The median DAP were 1.48 (range, 1.37-2.17) dGy^*cm² in grid images and 1.22 (range, 1.11-1.78) dGy^*cm² in grid-like images with a significant difference (p < 0.001).

Conclusion

The SimGrid software significantly improved the image quality of non-grid images to a level comparable to that of grid images with a relatively lower level of radiation exposure.

Extratemporal resections in pediatric epilepsy surgery-an overview

Despite optimized medical treatment, approximately one third of all patients with epilepsy continue to have seizures and by definition have medically resistant epilepsy (MRE). For these patients, surgical disruption of the epileptogenic network may enable freedom or great improvement in control of their seizures. The success of surgery is dependent on accurate localization of the epileptogenic zone and network. Epilepsy arising from regions of cortical dysplasia within the neocortex of the frontal, parietal, and occipital lobes show a propensity for reorganization and progressive decline in seizure freedom and consequent poorer surgical outcome. These procedures often require staged investigation with intracranial electrodes via subdural grids or stereoelectroencephalography (SEEG) and are considered extratemporal resections (ETRs). Central concepts include the following: (1) localization of epileptogenic and eloquent functional regions, (2) safe and effective placement of intracranial electrode arrays, (3) resection of epileptogenic cortex, and (4) avoidance of complications. Each of these concepts is summarized and developed in this summary paper.

Segmentation of Skin Tumors in High-Frequency 3-D Ultrasound Images

High-frequency 3-D ultrasound imaging is an informative tool for diagnosis, surgery planning and skin lesion examination. The purpose of this article was to describe a semi-automated segmentation tool providing easy access to the extent, shape and volume of a lesion. We propose an adaptive log-likelihood level-set segmentation procedure using non-parametric estimates of the intensity distribution. The algorithm has a single parameter to control the smoothness of the contour, and we describe how a fixed value yields satisfactory segmentation results with an average Dice coefficient of D = 0.76. The algorithm is implemented on a grid, which increases the speed by a factor of 100 compared with a standard pixelwise segmentation. We compare the method with parametric methods making the hypothesis of Rayleigh or Nakagami distributed signals, and illustrate that our method has greater robustness with similar computational speed. Benchmarks are made on realistic synthetic ultrasound images and a data set of nine clinical 3-D images acquired with a 50-MHz imaging system. The proposed algorithm is suitable for use in a clinical context as a post-processing tool.

From the desktop to the grid: scalable bioinformatics via workflow conversion

Background

Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks.

There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free —an aspect that could potentially drive away members of the scientific community.

Results

We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources.

Conclusions

Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.