The Convolution algorithm, implemented in Leksell GammaPlan® ver. Here, 10, is the first algorithm for Leksell Gamma Knife that takes heterogeneities into account and models dose build-up effects close to tissue boundaries. The aim of this study was preliminary comparison of the Convolution and TMR10 algorithms for real clinical cases and dosimetric verification of the algorithms, using measurements in a phantom. A total of 25 patients involved in comparison of the Convolution and TMR10 algorithms were divided into three groups: patients with benign tumors close to heterogeneities, patients with functional disorders, and patients with tumors located far from heterogeneities. Differences were observed especially in the group of patients with tumors close to heterogeneities, where the difference in maximal dose to critical structures for the Convolution algorithm was up to 15% compared to the TMR10 algorithm. Dosimetric verification of the algorithm was performed, using a radiochromic gel dosimeter based on Turnbull blue dye in a special heterogeneous phantom. Relative dose distributions measured with the radiochromic gel dosimeter agreed very well with both the TMR10 and Convolution calculations. We observed small discrepancies in the direction in which the largest inhomogeneity was positioned. Verification results indicated that the Convolution algorithm provides a different dose distribution, especially in regions close to heterogeneities and particularly for lower isodose volumes. However, the results obtained with gamma analyses in the gel dosimetry experiment did not verify the assumption that the Convolution algorithm provides more accurate dose calculation.
- Keywords
- gel dosimetry, stereotactic radiosurgery, verification,
- MeSH
- Algorithms * MeSH
- Radiotherapy Dosage MeSH
- Phantoms, Imaging * MeSH
- Film Dosimetry * MeSH
- Organs at Risk radiation effects MeSH
- Humans MeSH
- Monte Carlo Method MeSH
- Neoplasms surgery MeSH
- Radiotherapy Planning, Computer-Assisted methods MeSH
- Radiosurgery methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Comparative Study MeSH
Population-based optimization algorithms are one of the most widely used and popular methods in solving optimization problems. In this paper, a new population-based optimization algorithm called the Teamwork Optimization Algorithm (TOA) is presented to solve various optimization problems. The main idea in designing the TOA is to simulate the teamwork behaviors of the members of a team in order to achieve their desired goal. The TOA is mathematically modeled for usability in solving optimization problems. The capability of the TOA in solving optimization problems is evaluated on a set of twenty-three standard objective functions. Additionally, the performance of the proposed TOA is compared with eight well-known optimization algorithms in providing a suitable quasi-optimal solution. The results of optimization of objective functions indicate the ability of the TOA to solve various optimization problems. Analysis and comparison of the simulation results of the optimization algorithms show that the proposed TOA is superior and far more competitive than the eight compared algorithms.
- Keywords
- optimization, optimization algorithm, optimization problem, population-based, teamwork,
- Publication type
- Journal Article MeSH
BACKGROUND: High frequency oscillations (HFOs) are emerging as potentially clinically important biomarkers for localizing seizure generating regions in epileptic brain. These events, however, are too frequent, and occur on too small a time scale to be identified quickly or reliably by human reviewers. Many of the deficiencies of the HFO detection algorithms published to date are addressed by the CS algorithm presented here. NEW METHOD: The algorithm employs novel methods for: 1) normalization; 2) storage of parameters to model human expertise; 3) differentiating highly localized oscillations from filtering phenomena; and 4) defining temporal extents of detected events. RESULTS: Receiver-operator characteristic curves demonstrate very low false positive rates with concomitantly high true positive rates over a large range of detector thresholds. The temporal resolution is shown to be +/-∼5ms for event boundaries. Computational efficiency is sufficient for use in a clinical setting. COMPARISON WITH EXISTING METHODS: The algorithm performance is directly compared to two established algorithms by Staba (2002) and Gardner (2007). Comparison with all published algorithms is beyond the scope of this work, but the features of all are discussed. All code and example data sets are freely available. CONCLUSIONS: The algorithm is shown to have high sensitivity and specificity for HFOs, be robust to common forms of artifact in EEG, and have performance adequate for use in a clinical setting.
- Keywords
- Detection algorithm, Frequency dominance, HFO, High frequency oscillations, Ripples,
- MeSH
- Algorithms * MeSH
- Artifacts MeSH
- Time Factors MeSH
- Electroencephalography methods MeSH
- Epilepsy diagnosis physiopathology MeSH
- False Positive Reactions MeSH
- Rodentia MeSH
- Humans MeSH
- Brain physiology physiopathology MeSH
- Signal Processing, Computer-Assisted MeSH
- Dogs MeSH
- ROC Curve MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Dogs MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Implementing a suitable load frequency controller to maintain the power balance equation for a multi-area system with many power generating units poses a challenge to a power system engineer. Incorporation of renewable energy sources along with non-renewable units is another challenge while maintaining the stability of the system. Hence a robust intelligent controller is an essential requirement to achieve the objective of automatic load frequency control. This article introduces a novel and efficient controller designed for a three-control area within a deregulated multi-source energy system. The three areas include diverse power generation sources: Area 1 integrates thermal units, hydro units, and solar thermal power plants. In Area 2, there is a combination of distributed solar technology (DST) with thermal and hydro units. Area 3 incorporates a geothermal power plant alongside thermal and hydro unit. The proposed controller is a parallel combination of the tilted integral derivative controller (TID) and the integral derivative with a first-order filter effect (IDN). The controller's parameters are optimized using an advanced Coatis Optimization Algorithm (COA). High effective efficiency and absence of control parameters are the key advantages of Coatis Optimization Algorithm. The article highlights the superior performance of the newly developed TID + IDN controller in comparison to standalone TID and IDN controllers. This assessment is based on the observation of dynamic responses across different controller configurations. Additionally, the study examines the system's behaviour when incorporating energy storage units such as Redox Flow Batteries (RFB). Furthermore, the research investigates the system under various power transactions in a deregulated environment, considering generation rate constraints and governor dead bands. The proposed approach's robustness is demonstrated by subjecting it to extensive variations in system parameters and random load fluctuations. In summary, this paper presents an innovative TID + IDN controller optimized using a novel Coatis Optimization Algorithm within a three-area hybrid system operating in a deregulated context. Considering the poolco transaction and implementing the COA optimized TID + IDN controller with an error margin of 0.02%, the value of the objective function, ITAE for the transient responses is 0.1233. This value is less than the value obtained in other controllers optimized with different optimization techniques. In case of poolco transaction, the settling time of deviation of frequency in area-1, deviation of frequency in area-2, and deviation of frequency in area-3 are 8.129, 3.72, and 2.254 respectively. As compared to other controllers, the transient parameters are better in case of this proposed controller.
- Keywords
- Coatis optimization algorithm (COA), Improved squirrel search algorithm (ISSA), Independent system operator (ISO), Integral derivative with a first-order filter effect (IDN), Integral time multiplied by absolute error (ITAE), Load frequency control (LFC), PID, Particle swarm optimization (PSO), Squirrel search algorithm (SSA), Tilted integral derivative controller (TID),
- Publication type
- Journal Article MeSH
PURPOSE: Sarcopenic obesity (SO) as a new diagnostic entity defined by presence of obesity in combination with sarcopenia represents serious health condition negatively affecting quality of life in old age. Despite the rapidly increasing incidence of SO associated with demographic aging, clear diagnostic criteria for SO have not yet been established. We describe here the applicability of the EWGSOP2 and EWGSOP1 diagnostic criteria in identifying sarcopenia and SO and the development of a refinement algorithm for SO detection. METHODS: In total 156 subjects were pre-screened, 126 had a complete dataset and were included, 20.6% (n = 26) were men and 79.4% (n = 100) women, mean age 81 ± 6.3 years in tertiary hospital, Prague, Czech Republic. Testing of physical performance (hand-grip test, 400 m walk test, chair stand test, gait speed), anthropometric measures and SARC-F, SPPB and MNA-SF were used to determine physical, functional, and nutritional status, while muscle mass and fat mass were measured by DXA scans to confirm sarcopenia and SO diagnosis. RESULTS: The prevalence of sarcopenia (BMI adjusted ALM < 0.789 for men, < 0.512 for women) was 26.2% (n = 33), SO in 20.6% (n = 26). 78.8% of all sarcopenic subjects fulfilled the criteria of SO (FM > 27% for men and > 38% for women; waist circumference > 90 cm for men and > 85 cm for women). EWGSOP1 criteria for diagnosing sarcopenia showed better sensitivity of 97.0% than the EWGSOP2 66.7%, while specificity reached 100% for both criteria. According to DXA measurement, EWGSOP1 identified 3.0% cases (1 out of 33) as false negative meanwhile EWGSOP2 identified 33.3% cases as false negative and this difference was statistically significant (McNemar's test, p < 0.001). An algorithm for SO was developed (which uses sex, BMI, height, waist circumference and SPPB) with sensitivity and specificity of 88.5 and 91.0%, respectively. CONCLUSION: High prevalence of obesity among elderly people and rather low sensitivity of current diagnostic criteria for SO call for ongoing research. Broader international consensus for SO diagnostic criteria, screening and diagnosis algorithm are crucial for early detection of SO in older people in clinical practice so that optimal multi-component therapy can be initiated.
- Keywords
- EWGSOP1, EWGSOP2, Modelling, Sarcopenia, Sarcopenic obesity,
- MeSH
- Algorithms MeSH
- Quality of Life MeSH
- Humans MeSH
- Obesity complications diagnosis epidemiology MeSH
- Sarcopenia * diagnosis epidemiology MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Hand Strength physiology MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
PURPOSE: The aim of this work was to introduce a new algorithm for image reconstruction in bone SPECT and to compare its performances with a commercially available standard OSEM and resolution recovery (RR) reconstruction. MATERIALS AND METHODS: The algorithm was built applying the Lucy-Richardson deconvolution adn logarithmic image processing to the projections. A modification of the coefficients of wavelet decomposition was used to suppress the noise. The comparison with vendor software was performed both in a phantom study, using Signal-to-Noise ratio (SNR), Signal-to-Background ratio (SBR), spatial resolution and in clinical studies, by visual assessment of changes in contrast, spatial resolution and lesion detectability. RESULTS: A change in the SNR (from -4 to 40%), an increase in the SBR (from 19 to 40%), a minor improvement in spatial resolution and a similar noise level were observed in the phantom study in comparison to the standard OSEM. A decrease in the SNR, a worse spatial resolution, but only a 3 to 13 % lower SBR were achieved in comparison with the vendor supplied RR algorithm. The proposed algorithm creates patient images with better contrast and lesion detectability compared to clinically used OSEM. Compared to RR, more than half of obtained images showed better contrast and nearly half of them have better lesion detectability. CONCLUSION: The proposed algorithm compares favorably with the standard OSEM. Although less favorable, the comparison with RR and noise suppression algorithms, suggests that it can be used with only a slight decrease in the SBR.
- Keywords
- Deconvolution, Logarithmic image processing, Wavelet denoising,
- MeSH
- Algorithms * MeSH
- Phantoms, Imaging * MeSH
- Tomography, Emission-Computed, Single-Photon instrumentation MeSH
- Bone and Bones diagnostic imaging MeSH
- Humans MeSH
- Image Processing, Computer-Assisted methods MeSH
- Signal-To-Noise Ratio MeSH
- Wavelet Analysis * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
In this paper, we analysed the steady state fluorescence spectra of cell suspensions containing healthy and carcinoma fibroblast mouse cells, using a genetic-algorithm-spectra-decomposition software (GASpeD). In contrast to other deconvolution algorithms, such as polynomial or linear unmixing software, GASpeD takes into account light scatter. In cell suspensions, light scatter plays an important role as it depends on the number of cells, their size, shape, and coagulation. The measured fluorescence spectra were normalized, smoothed and deconvoluted into four peaks and background. The wavelengths of intensities' maxima of lipopigments (LR), FAD, and free/bound NAD(P)H (AF/AB) of the deconvoluted spectra matched published data. In deconvoluted spectra at pH = 7, the fluorescence intensities of the AF/AB ratio in healthy cells was always higher in comparison to carcinoma cells. In addition, the AF/AB ratio in healthy and carcinoma cells were influenced differently by changes in pH. In mixtures of healthy and carcinoma cells, AF/AB decreases when more than 13% of carcinoma cells are present. Expensive instrumentation is not required, and the software is user friendly. Due to these attributes, we hope that this study will be a first step in the development of new cancer biosensors and treatments with the use of optical fibers.
- Keywords
- cancer biosensor, cell suspension auto-fluorescence, endogenous fluorophores, genetic algorithm, steady state fluorescence,
- MeSH
- Algorithms * MeSH
- Cell Culture Techniques MeSH
- Fluorescence MeSH
- Spectrometry, Fluorescence MeSH
- Carcinoma * MeSH
- Mice MeSH
- Software MeSH
- Animals MeSH
- Check Tag
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
This study introduces a novel approach for analyzing photovoltaic (PV) systems that employ block lookup tables for speedy and efficient simulation. It introduces an innovative method for tracking the Global Maximum Power Point (GMPP) by utilizing Zebra Optimization Algorithm (ZOA). The suggested method was carefully evaluated under difficult Partial Shading Conditions (PSCs) and Dynamic Shading Conditions (DSCs) to determine its global and local search capability. ZOA's performance was examined in four scenarios and compared to four existing MPPT algorithms: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), and Whale Optimization Algorithm (WOA). ZOA surpassed its competitors with an average tracking time of 0.875 s and a tracking efficiency of 99.95% in PSCs. In comparison, ZOA increased tracking efficiency by up to 2%, increased resilience under varied circumstances, and produced a faster convergence speed-approaching the maximum Power Point 10-15% faster than the other algorithms. Furthermore, ZOA significantly decreased operating point variations. The algorithm's overall performance was tested using an experimental setup with a DSPACE board and a PV emulator. These findings demonstrate that ZOA is a highly efficient and dependable MPPT solution for PV systems, especially in severe PSCs.
Many of the differential item functioning (DIF) detection methods rely on a principle of testing for DIF item by item, while considering the rest of the items or at least some of them being DIF-free. Computational algorithms of these DIF detection methods involve the selection of DIF-free items in an iterative procedure called item purification. Another aspect is the need to correct for multiple comparisons, which can be done with a number of existing multiple comparison adjustment methods. In this article, we demonstrate that implementation of these two controlling procedures together may have an impact on which items are detected as DIF items. We propose an iterative algorithm combining item purification and adjustment for multiple comparisons. Pleasant properties of the newly proposed algorithm are shown with a simulation study. The method is demonstrated on a real data example.
- Keywords
- Differential item functioning, item purification, multiple comparison adjustments,
- MeSH
- Algorithms * MeSH
- Emotions * MeSH
- Computer Simulation MeSH
- Publication type
- Journal Article MeSH
MOTIVATION: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. RESULTS: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately. AVAILABILITY AND IMPLEMENTATION: The challenge Web site (http://www.codesolorzano.com/celltrackingchallenge) provides access to the training and competition datasets, along with the ground truth of the training videos. It also provides access to Windows and Linux executable files of the evaluation software and most of the algorithms that competed in the challenge.
