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At least 217 records · Page 12Linked to original sources

PubMed1996

A computer algorithm to impute interrupted heart rate data for the spectral analysis of heart rate variability--the ARIC study.

The shorter term beat-to-beat heart rate data collected from the general population are often interrupted by artifacts, and an arbitrary exclusion of such individuals from analysis may significantly reduce the sample size and/or introduce selection bias. A computer algorithm was developed to label as artifacts any data points outside the upper and lower limits generated by a 5-beat moving average +/- 25% (or set manually by an operator using a mouse) and to impute beat-to-beat heart rate throughout an artifact period to preserve the timing relationships of the adjacent, uncorrupted heart rate data. The algorithm applies Fast Fourier Transformation to the smoothed data to estimate low-frequency (LF; 0.025-0.15 Hz) and high-frequency (HF; 0.16-0.35 Hz) spectral powers and the HF/LF ratio as conventional indices of sympathetic, vagal, and vagal-sympathetic balance components, respectively. We applied this algorithm to resting, supine, 2-min beat-to-beat heart rate data collected in the population-based Atherosclerosis Risk in Communities study to assess the performance (success rate) of the algorithm (N = 526) and the inter-and intra-data-operator repeatability of using this computer algorithm (N = 108). Eighty-eight percent (88%) of the records could be smoothed by the computer-generated limits, an additional 4.8% by manually set limits, and 7.4% of the data could not be processed due to a large number of artifacts in the beginning or the end of the records. For the repeatability study, 108 records were selected at random, and two trained data operators applied this algorithm to the same records twice within a 6-month interval of each process (blinded to each other's results and their own prior results). The inter-data-operator reliability coefficients were 0.86, 0.92, and 0.90 for the HF, LF, and HF/LF components, respectively. The average intra-data-operator reliability coefficients were 0.99, 0.99, and 0.98 for the HF, LF, and HF/LF components, respectively. These results indicate that this computer algorithm is efficient and highly repeatable in processing short-term beat-to-beat heart rate data collected from the general population, given that the data operators are trained according to standardized protocol.

Algorithms↗

PubMed1998

Comparative investigations of algorithms for the detection of breaths in newborns with disturbed respiratory signals.

The correct detection of the beginning of inspiration and expiration in the respiratory signals is an essential prerequisite for accurate lung function testing in newborns. Five algorithms for breath detection using pneumotachographically measured flow and volume signals were investigated with regard to the error rate. To compare and to evaluate the reliability of these algorithms 12 minimally and 12 severely disturbed flow and volume signals from spontaneously breathing newborns were used. With the exception of an algorithm based on Walsh-transformed signals, all algorithms work reliably (error rate <1.1%) if disturbances are minimal. In severely disturbed signals there is a great difference between the algorithms. The most robust algorithm tested (trigger of the flow signal with an additional plausibility check of the recognized breath) resulted in an error rate of <3.4%. Not all algorithms tested are suitable for real-time applications because they differ considerably in delay time for breath detection.

Algorithms↗

PubMed1999

A dynamic programming algorithm for RNA structure prediction including pseudoknots.

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of O(N6) in time and O(N4) in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm that generates the optimal minimum energy structure for a single RNA sequence, using standard RNA folding thermodynamic parameters augmented by a few parameters describing the thermodynamic stability of pseudoknots. We demonstrate the properties of the algorithm by using it to predict structures for several small pseudoknotted and non-pseudoknotted RNAs. Although the time and memory demands of the algorithm are steep, we believe this is the first algorithm to be able to fold optimal (minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model.

Algorithms↗

PubMed2000

A time-domain algorithm for NMR spectral normalization.

Recently, a new method for quantitatively comparing NMR spectra of control and treated samples, in order to examine the possible occurring variations in cell metabolism and/or structure in response to numerous physical, chemical, and biological agents, was proposed. This method is based upon the utilization of the maximum superposition normalization algorithm (MaSNAl) operative in the frequency domain and based upon maximizing, by an opportune sign variable measure, the spectral region in which control and treated spectra are superimposed. Although the frequency-domain MaSNAl algorithm was very precise in normalizing spectra, it showed some limitations in relation to the signal-to-noise ratio and to the degree of diversity of the two spectra being analyzed. In particular, it can rarely be applied to spectra with a small number of visible signals not buried in the noise such as generally in vivo spectra. In this paper, a time-domain normalization algorithm is presented. Specifically, it consists in minimizing the rank of a Hankel matrix constructed with the difference of the two free induction decay signals. The algorithm, denoted MiRaNAl (minimum rank normalization algorithm), was tested by Monte Carlo simulations as well as experimentally by comparing two samples of known contents both with the new algorithms and with an older method using a standard. Finally, the algorithm was applied to real spectra of cell samples showing how it can be used to obtain qualitative and quantitative biological information.

Algorithms↗

PubMedDate not supplied

The contour-buildup algorithm to calculate the analytical molecular surface.

A new algorithm is presented to calculate the analytical molecular surface defined as a smooth envelope traced out by the surface of a probe sphere rolled over the molecule. The core of the algorithm is the sequential build up of multi-arc contours on the van der Waals spheres. This algorithm yields substantial reduction in both memory and time requirements of surface calculations. Further, the contour-buildup principle is intrinsically "local", which makes calculations of the partial molecular surfaces even more efficient. Additionally, the algorithm is equally applicable not only to convex patches, but also to concave triangular patches which may have complex multiple intersections. The algorithm permits the rigorous calculation of the full analytical molecular surface for a 100-residue protein in about 2 seconds on an SGI indigo with R4400++ processor at 150 Mhz, with the performance scaling almost linearly with the protein size. The contour-buildup algorithm is faster than the original Connolly algorithm an order of magnitude.

Algorithms↗

PubMed2001

Measurement of cortical thickness using an automated 3-D algorithm: a validation study.

A validation study was conducted to assess the accuracy of the algorithm developed by MacDonald et al. (1999) for measuring cortical thickness. This algorithm automatically determines the cortical thickness by 3-D extraction of the inner and outer surfaces of the cerebral cortex from an MRI scan. A manual method of tagging the grey-csf and grey-white interface was used on 20 regions (10 cortical areas found in each hemisphere) in 40 MRIs of the brain to validate the algorithm. The regions were chosen throughout the cortex to get broad assessment of the algorithm's performance. Accuracy was determined by an anatomist tagging the csf-grey and grey-white borders of selected gyri and by allowing the algorithm to determine the csf-grey and grey-white borders and the corresponding cortical thickness of the same region. Results from the manual and automatic methods were statistically compared using overall ANOVA and paired t tests for each region. The manual and automatic methods were in agreement for all but 4 of the 20 regions tested. The four regions where there were significant differences between the two methods were the insula left and right, the right cuneus, and the right parahippocampus. We conclude that the automatic algorithm is valid for most of the cortex and provides a viable alternative to manual methods of determining cortical thickness in vivo. However, caution should be taken when measuring the regions mentioned previously where the results of the algorithm can be biased by surrounding grey structures.

Adult↗

PubMed2003

Do segmented reconstruction algorithms for cardiac multi-slice computed tomography improve image quality?

PURPOSE: To evaluate segmented reconstruction algorithms for spiral multi-slice computed tomography (MSCT) that use data from two cardiac cycles to improve temporal resolution (tau) for imaging of the heart. MATERIALS AND METHODS: An initial group of 78 cardiac patients (heart rates [HR] = 63-167 beats per minute [bpm]) were imaged on a 4-slice, 500 ms gantry rotation time scanner (scanner 1). Images were reconstructed with a single-segment algorithm using data from one cardiac cycle with a reconstruction window of fixed length (tau = 250 ms). Images were also reconstructed with two variants of a multi-segment algorithm using data from two cardiac cycles where only one end of the reconstruction window was fixed and the other end was freely moveable to allow adjustment of tau according to HR: (1) "2-segment fixed start" with fixed start of reconstruction, (2) "2-segment fixed end" with fixed end of reconstruction (for both, tau = 125-250 ms). The resulting image sets were ranked from best to worst (1-3, respectively) in a side-by-side, blinded comparison by two independent readers. A second group of 26 patients (HR = 74-90 bpm) were imaged on a 12-slice, 420 ms gantry rotation time scanner (scanner 2). Data were reconstructed with a single-segment algorithm (tau = 210 ms) and a "2-segment fixed start" algorithm (tau = 105-210 ms) and image sets were ranked from best to worst (1-2, respectively). RESULTS: There was no clear evidence that any one technique is superior for imaging on scanner 1. Reader 1 ranked single-segment images the highest for all HRs, but statistically significant differences among the three algorithms were only found for the lowest HRs (< 80 bpm), where reader 1 preferred single-segment over "2-segment fixed end" techniques (p = 0.048). The highest rankings given by reader 2 varied according to HR: single-segment images were superior for lowest HRs, while "2-segment fixed start" images were superior for HRs > 80 bpm; none of these comparisons reached statistical significance. Improved performance of 2-segment reconstruction was found with scanner 2. Both readers ranked "2-segment fixed start" images the highest (p < 0.01). CONCLUSIONS: The added value of 2-segment cardiac reconstruction algorithms for spiral MSCT was not demonstrated for a 4-slice, 500 ms gantry rotation time scanner but shown to be beneficial for a 12-slice, 420 ms gantry rotation time scanner in the crucial HR range of 74-90 bpm.

Adolescent↗

PubMed2001

Implementation and evaluation of a 3D one-step late reconstruction algorithm for 3D positron emission tomography brain studies using median root prior.

A fully three-dimensional (3D) one-step late (OSL), maximum a posteriori (MAP) reconstruction algorithm based on the median root prior (MRP) was implemented and evaluated for the reconstruction of 3D positron emission tomography (PET) studies. The algorithm uses the ordered subsets (OS) scheme for convergence acceleration and data update during iterations. The algorithm was implemented using the software package developed within the EU project PARAPET (www.brunel.ac.uk/~masrppet). The MRP algorithm was evaluated using experimental phantom and real 3D PET brain studies. Various experimental set-ups in terms of activity distribution and counting statistics were considered. The performance of the algorithm was assessed by calculating figures of merit such as: contrast, coefficient of variation, activity ratio between two regions and full width at half of maximum for resolution measurements. The performance of MRP was compared with that of 3D ordered subsets-expectation maximisation (OSEM) and 3D re-projection (3DRP) algorithms. In all the experimental situations considered, MRP showed: (1) convergence to a stable solution, (2) effectiveness in noise reduction, particularly for low statistics data, (3) good preservation of spatial details. Compared with the OSEM and 3DRP algorithms, MRP provides comparable or better results depending on the parameters used for the reconstruction of the images.

Algorithms↗

PubMed1991

Classification of postoperative cardiac patients: comparative evaluation of four algorithms.

Four classification algorithms based on Bayes' rule for minimum error are compared by evaluating their ability to recognize high- and normal-risk cardio-surgical patients. These algorithms differ in the modelling of the probability density function (pdf) for each class and include: (a) two parametric algorithms based on the assumption of normal pdf; (b) two non-parametric algorithms using Parzen multidimensional approximation of pdf with normal kernels. In each case, classes with both equal and different covariance matrices were considered. A set of 200 patients in the 6 h immediately following cardiac surgery has been used to test the performance of the algorithms. For each patient the three measured variables most effective in representing the difference between the two classes were considered. We found that the two algorithms which explicitly incorporate the information on the different sample covariance between the physiological variables existing in the two classes generally provide better recognition of high- and normal-risk patients. Of these two algorithms the parametric one appears extremely attractive for practical applications, since it exhibits slightly better performance in spite of its great simplicity.

Algorithms↗

PubMed1992

Fast ECG data compression algorithms suitable for microprocessor systems.

ECG data compression techniques have received extensive attention in ECG analysis. Numerous data compression algorithms for ECG signals have been proposed during the last three decades. We describe two algorithms based on the scan-along polygonal approximation algorithm (SAPA) that are suitable for multichannel ECG data reduction on a microprocessor-based system. One represents a modification of SAPA (MSAPA) which adopts the method of integer division table searching to speed up data reduction; the other (CSAPA) combines MSAPA and TP, a turning-point algorithm, to preserve ST segment signals. Results show that our algorithms achieve a compression ratio of more than 5:1 and a percent rms difference (PRD) to the original signal of less than 3.5%. In addition, the maximum execution time of MSAPA for processing one data point is about 50 microseconds. Moreover, the CSAPA algorithm retains all of the details of the ST segment, which are important in ischaemia diagnosis, by employing the TP algorithm.

Algorithms↗

PubMed1995

Comparison of simulated annealing algorithms for conformal therapy treatment planning.

PURPOSE: The efficiency of four fast simulated annealing algorithms for optimizing conformal radiation therapy treatment plans was studied and the resulting plans were compared with each other and to optimized conventional plans. METHODS AND MATERIALS: Four algorithms were selected on the basis of their reported successes in solving other minimization problems: fast simulated annealing with a Cauchy generating function, fast simulated annealing with a Lorentzian generating function, variable step size generalized simulated annealing (VSGSA), and very fast simulated reannealing (VFSR). They were tested on six clinical cases using a multiple beam coplanar conformal treatment technique. Relative beam weights were computed that maximized the minimum tumor dose subject to dose-volume constraints on normal organ doses. Following some initial tuning of the annealing parameters, each algorithm was applied identically to each test case. Optimization tests were run using different random number sequences and different numbers of iterations. RESULTS: The VSGSA algorithm consistently produced the best results. Using long run times, it generated plans with the highest minimum tumor dose in five of the six cases. For the short run times, the VSGSA solutions averaged larger minimum tumor doses than those of the other algorithms for all six patients, with increases ranging from 0.4 to 5.9 Gy. For three of the patients, the conformal plan gave a clinically significant increase in the minimum tumor dose over the conventional plan, ranging from 8.2 to 13.0 Gy. In two other cases, there was little difference between the two treatment approaches. For one case, the optimized conventional plan was much better than the conformal plan because the conventional beam arrangement included wedges, which offset the multiple beam advantage of the conformal plans. CONCLUSIONS: For equal computing times of both long and short duration, the VSGSA algorithm consistently produced conformal plans that were superior to those produced by the other algorithms. The simple conformal technique used in this study showed a significant potential advantage in the treatment of abdominal tumors. In three of the cases, the conformal plans showed clinically important increases in tumor dose over optimized conventional plans.

Abdominal Neoplasms↗

PubMed2003

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis.

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.

Algorithms↗

PubMed2002

An algorithm for assessing the risk of traffic accident.

INTRODUCTION: This study is aimed at developing an algorithm to estimate the number of traffic accidents and assess the risk of traffic accidents in a study area. METHOD: The algorithm involves a combination of mapping technique (Geographical Information System (GIS) techniques) and statistical methods (cluster analysis and regression analysis). Geographical Information System is used to locate accidents on a digital map and realize their distribution. Cluster analysis is used to group the homogeneous data together. Regression analysis is performed to realize the relation between the number of accident events and the potential causal factors. Negative binomial regression model is found to be an appropriate mathematical form to mimic this relation. Accident risk of the area, derived from historical accident records and causal factors, is also determined in the algorithm. The risk is computed using the Empirical Bayes (EB) approach. A case study of Hong Kong is presented to illustrate the effectiveness of the proposed algorithm. RESULTS: The results show that the algorithm improves accident risk estimation when comparing to the estimated risk based on only the historical accident records. The algorithm is found to be more efficient, especially in the case of fatality and pedestrian-related accident analysis. IMPACT ON INDUSTRY: The output of the proposed algorithm can help authorities effectively identify areas with high accident risk. In addition, it can serve as a reference for town planners considering road safety.

Accidents, Traffic↗

PubMed1998

Planning of beam intensity modulation using an advanced 3D dose calculation algorithm and a simulated annealing method.

PURPOSE: The aim of this work was to develop a fast inverse planning algorithm that will calculate optimum beam intensity distributions and beam shapes, and to incorporate the algorithm into a three-dimensional CT planning system. METHOD: The algorithm is based on the technique of simulated annealing and produces beam intensity distributions that could in principle be implemented clinically, either by the use of compensators or dynamic multileaf collimation. Dose distributions are calculated using a voxel beam model based on a spherical co-ordinate system, and transformations are given allowing the dose to be determined at any point within the patient. The dose calculation algorithm calculates primary and scattered dose separately from a knowledge of tissue/air ratios and differential scatter/air ratios, and both are corrected for the presence of heterogeneities in three dimensions. Specific attention is given to the execution time of the algorithm, and the methods developed allow satisfactory results to be achieved in calculation times which are sufficiently fast to be used interactively in the planning system. Several objective functions have been developed and can be selected in a simple manner by the user. In general, these attempt to achieve a uniform dose within the target while limiting the dose to organs at risk, either by upper dose limits or by specifying constraints on their dose volume histograms. RESULTS: The beam intensity distributions produced from the optimization have been used automatically by the forward planning system to produce three-dimensional dose distributions, and the results obtained in a number of clinical situations are presented. CONCLUSIONS: The inverse planning algorithm developed has been successfully incorporated into a three-dimensional planning system and is capable of producing beam intensity modulated distributions for clinical implementation. The execution time of the algorithm is sufficiently fast to be used as an optimization tool in an interactive forward planning system.

Algorithms↗

PubMed1997

A structure-based algorithm to predict potential binding peptides to MHC molecules with hydrophobic binding pockets.

Binding of peptides to MHC class I molecules is a prerequisite for their recognition by cytotoxic T cells. Consequently, identification of peptides that will bind to a given MHC molecule must constitute a central part of any algorithm for prediction of T-cell antigenic peptides based on the amino acid sequence of the protein. Binding motifs, defined by anchor positions only, have proven to be insufficient to ensure binding, suggesting that other positions along the peptide sequence also affect peptide-MHC interaction. The second phase of prediction schemes therefore take into account the effect of all positions along the peptide sequence, and are based on position-dependent-coefficients that are used in the calculation of a peptide score. These coefficients can be extracted from a large ensemble of binding sequences that were tested experimentally, or derived from structural considerations, as in the algorithm developed by us recently. This algorithm uses the coordinates of solved complexes to evaluate the interactions of peptide amino acids with MHC contact residues, and results in a peptide score that reflects its binding energy. Here we present our analysis for peptide binding to four MHC alleles (HLA-A2, HLA-A68, HLA-B27 and H-2Kb), and compare the predictions of the algorithm to experimental binding data. The algorithm performs successfully in predicting peptide binding to MHC molecules with hydrophobic binding pockets but not when MHC molecules with hydrophilic, charged pockets are considered. For MHC molecules with hydrophobic pockets it is demonstrated how the algorithm succeeds in distinguishing binding from non-binding peptides, and in high ranking of immunogenic peptides within all overlapping same-length peptides spanning their respective protein sequences. The latter property of the algorithm makes it a useful tool in the rational design of peptide vaccines aimed at T-cell immunity.

Algorithms↗

PubMed1998

Prospective evaluation of an anemia treatment algorithm in hemodialysis patients.

Current guidelines recommend maintaining the hematocrits of chronic hemodialysis patients in the low to mid-30s. Maintaining patients' hematocrits within a narrow range requires frequent monitoring of their hematocrits and iron studies and periodic adjustment of erythropoietin doses and administration of intravenous iron. We designed a simple anemia treatment algorithm to streamline the management of anemia in hemodialysis patients. The protocol required formal monthly decisions about the administration of intravenous iron or changes in erythropoietin dose. This algorithm was implemented by dialysis nurses and evaluated prospectively for 6 months in a single dialysis unit (30 patients). The proportion of patients whose hematocrits were within the desired target (31% to 35%) increased from 27% at baseline to 61% during months 4 through 6 of the algorithm. Conversely, the proportion of patients whose hematocrit values were below the target decreased from 46% at baseline to 18% during months 4 through 6 of the algorithm (P=0.004). The percentage of patients whose hematocrit values were above the target did not increase. The proportion of patients whose transferrin saturation was less than 18% decreased from 47% at baseline to 20% during months 4 through 6 of the algorithm (P=0.04). The weekly erythropoietin dose administered decreased from 11,200+/-1,400 units at baseline to 9,400+/-1,200 units in month 6 of the algorithm (P=0.06). We conclude that a simple anemia treatment algorithm implemented by dialysis nurses is feasible and efficacious and may increase the proportion of hemodialysis patients whose hematocrit values are within the target range, without increasing erythropoietin requirements.

Adult↗

PubMedDate not supplied

Growing-cube isosurface extraction algorithm for medical volume data.

In medical applications, three-dimensional volume data such as CT and MRI are gathered from medical-imaging devices. Marching cube (MC) algorithm is a common routine to extract isosurfaces from volume data. The MC algorithm generates the massive number of triangles to represent an isosurface. It is difficult to render this amount of triangles in real-time on general workstations. In this paper, we present a growing-cube algorithm to reduce the number of triangles generated by the MC algorithm. Growing-cube algorithm uses a surface tracker to avoid exhaustive searching isosurfaces cell-by-cell and, therefore, it saves computation time. During surface tracking, the growing-cube algorithm adaptively merges surfaces contained in the tracked cells to reduce the number of triangles. Surfaces are merged as long as the error is within user-specified error thresholds. Therefore, the proposed algorithm can generate a variable resolution of isosurfaces according to these error parameters.

Algorithms↗

PubMed2000

Fast iterative algorithm for metal artifact reduction in X-ray CT.

RATIONALE AND OBJECTIVES: The reduction of metal artifacts in x-ray computed tomography (CT) has important clinical applications. An iterative method adapted from the expectation maximization (EM) formula for emission CT was shown to be effective for metal artifact reduction, but its computational speed is slow. The goal of this project was to accelerate that iterative method for metal artifact reduction. MATERIALS AND METHODS: Using the row-action/ordered-subset (EM) formula for emission CT as a basis, the authors developed a fast iterative algorithm for metal artifact reduction. In each iteration of this algorithm, both reprojection from an intermediate image and backprojection from discrepancy data are performed. RESULTS: The feasibility of the fast iterative algorithm was demonstrated in numerical and phantom experiments. In comparison with the nonaccelerated iterative algorithm, the speed of iterative metal artifact reduction is improved by an order of magnitude given image quality in terms of visual inspection, I-divergence in the projection domain, and the euclidean distance in the image domain. CONCLUSION: The fast iterative algorithm corrects intermediate reconstruction according to subsets of projections and produces satisfactory image quality at a much faster speed than the previously published iterative algorithm. This algorithm has important potential in clinical applications, such as orthopedic, oncologic, and dental imaging.

Algorithms↗