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PubMed2004

Intracranial vessel segmentation from time-of-flight MRA using pre-processing of the MIP Z-buffer: accuracy of the ZBS algorithm.

We evaluate the accuracy of a vascular segmentation algorithm which uses continuity in the maximum intensity projection (MIP) depth Z-buffer as a pre-processing step to generate a list of 3D seed points for further segmentation. We refer to the algorithm as Z-buffer segmentation (ZBS). The pre-processing of the MIP Z-buffer is based on smoothness measured using the minimum chi-square value of a least square fit. Points in the Z-buffer with chi-square values below a selected threshold are used as seed points for 3D region growing. The ZBS algorithm couples spatial continuity information with intensity information to create a simple yet accurate segmentation algorithm. We examine the dependence of the segmentation on various parameters of the algorithm. Performance is assessed in terms of the inclusion/exclusion of vessel/background voxels in the segmentation of intracranial time-of-flight MRA images. The evaluation is based on 490,256 voxels from 14 patients which were classified by an observer. ZBS performance was compared to simple thresholding and to segmentation based on vessel enhancement filtering. The ZBS segmentation was only weakly dependent on the parameters of the initial MIP image generation, indicating the robustness of this approach. Region growing based on Z-buffer generated seeds was advantageous compared to simple thresholding. The ZBS algorithm provided segmentation accuracies similar to that obtained with the vessel enhancement filter. The ZBS performance was notably better than the filter based segmentation for aneurysms where the assumptions of the filter were violated. As currently implemented the algorithm slightly under-segments the intracranial vasculature.

Algorithms↗

PubMed2003

A rapid algorithm for robust and automatic extraction of the midsagittal plane of the human cerebrum from neuroimages based on local symmetry and outlier removal.

A rapid algorithm for robust, accurate, and automatic extraction of the midsagittal plane (MSP) of the human cerebrum from normal and pathological neuroimages is proposed. The MSP is defined as a plane formed from the interhemispheric fissure line segments having the dominant orientation. The algorithm extracts the MSP in four steps: (1) determine suitable axial slices for processing, (2) localize the fissure line segments on them, (3) select inliers from the extracted fissure line segments through histogram-based outlier removal, and (4) calculate the equation of the MSP from the selected inliers. The fissure line segments are localized by minimizing the local symmetry index characterizing anatomical properties of images in the vicinity of the interhemispheric fissure. A two-stage angular and distance outlier removal is introduced to handle abnormalities. The algorithm has been validated quantitatively with 125 structural MRI and CT cases from 10 centers on three continents by studying its accuracy; tolerance to rotation, noise, asymmetry, and bias field; sensitivity to parameters; and performance. A statistical relationship between algorithm accuracy and the data's adherence to planarity is also determined. The algorithm extracts the MSP below 6 s on Pentium 4 (2.4 GHz) with the average angular and distance errors of (0.40 degrees; 0.63 mm) for normal and (0.59 degrees; 0.73 mm) for pathological cases. The robustness to noise, asymmetry, rotation, and bias field is achieved by extracting the MSP based on the dominant orientation and local symmetry index. A low computational cost results from applying simple operations capturing intrinsic anatomic features, constraining the searching space to the local vicinity of the interhemispheric fissure, and formulating a noniterative algorithm with a coarse and fine fixed-step searching. In comparison to the existing methods, our algorithm is much faster, performs accurately and robustly for a wide range of diversified data, and is fully automatic and thoroughly validated, which make it suitable for clinical applications.

Acoustic Stimulation↗

PubMed2006

High density dental materials and radiotherapy planning: comparison of the dose predictions using superposition algorithm and fluence map Monte Carlo method with radiochromic film measurements.

BACKGROUND AND PURPOSE: During radiotherapy planning high density dental materials create a major challenge in determining correct dose distribution inside patients with head-and-neck tumors. PATIENTS AND METHODS: In this work we investigated the absorbed dose distribution inside a solid water slab phantom with embedded high density material irradiated by a 6MV photon beam of field size 10x10cm. We evaluated the absorbed dose distribution with three different techniques: superposition algorithm, radiochromic film, and the fluence map Monte Carlo (FMMC) method. RESULTS: The results obtained with radiochromic film and FMMC were in good agreement (within +/-5% of the dose) with one another. The superposition algorithm, which is often considered superior to other commercially available dose calculation algorithms, produced appreciably less accurate results than FMMC. In particular, downstream from the high density cerrobend inhomogeneity the superposition algorithm predicts a higher dose than the measurement does by at least 10-16% depending upon the size of the inhomogeneity and the distance from it. Upstream of the high density inhomogeneities the superposition algorithm predicts a lower than measured dose due to its failure to predict the dose enhancement close to the inhomogeneity interface. CONCLUSIONS: The delivered dose downstream from a high density inhomogeneity would be significantly less than the prescribed dose calculated by the superposition algorithm. The FMMC method which is based on a hybrid of the superposition algorithm input fluence data and Monte Carlo can be a useful tool in predicting dose in the presence of high density (e.g. dental) materials.

Algorithms↗

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↗

PubMed1997

Clique-detection algorithms for matching three-dimensional molecular structures.

The representation of chemical and biological molecules by means of graphs permits the use of a maximum common subgraph (MCS) isomorphism algorithm to identify the structural relationships existing between pairs of such molecular graphs. Clique detection provides an efficient way of implementing MCS detection, and this article reports a comparison of several different clique-detection algorithms when used for this purpose. Experiments with both small molecules and proteins demonstrate that the most efficient of these particular applications, which typically involve correspondence graphs with low edge densities, is the algorithm described by Carraghan and Pardalos. This is shown to be two to three times faster than the Bron-Kerbosch algorithm that has been used previously for MCS applications in chemistry and biology. However, the latter algorithm enables all substructures common to a pair of molecules to be identified, and not just the largest ones, as with the other algorithms considered here. The two algorithms can usefully be combined to increase the efficiency of database-searching systems that use the MCS as a measure of structural similarity.

Algorithms↗

PubMed2003

Q9, a content-balancing accuracy index to evaluate algorithms of protein secondary structure prediction.

A content-balancing accuracy index, called Q(9), has been proposed to evaluate algorithms of protein secondary structure prediction. Here the content-balancing means that the evaluation is independent of the contents of helix, strand and coil in the protein being predicted. It is shown that Q(9) is much superior to the widely used index Q(3). Therefore, algorithms are more objectively evaluated by Q(9) than Q(3). Based on 396 non-homologous proteins, five algorithms of secondary structure prediction were evaluated and compared by the new index Q(9). Of the five algorithms, PHD turned out to be the unique algorithm with an average Q(9) better than 60%. Based on the new index, it is shown that the performance of the consensus method based on a jury-decision from several algorithms is even worse than that of the best individual method. Rather than Q(3), we believe that Q(9) should be used to evaluate algorithms of protein secondary structure prediction in future studies in order to improve prediction quality.

Algorithms↗

PubMedDate not supplied

A FAST pattern matching algorithm.

The advent of digital computers has made the routine use of pattern-matching possible in various applications. This has also stimulated the development of many algorithms. In this paper, we propose a new algorithm that offers improved performance compared to those reported in the literature so far. The new algorithm has been evolved after analyzing the well-known algorithms such as Boyer-Moore, Quick-search, Raita, and Horspool. The overall performance of the proposed algorithm has been improved using the shift provided by the Quick-search bad-character and by defining a fixed order of comparison. These result in the reduction of the character comparison effort at each attempt. The best- and the worst- case time complexities are also presented in this paper. Most importantly, the proposed method has been compared with the other widely used algorithms. It is interesting to note that the new algorithm works consistently better for any alphabet size.

Algorithms↗

PubMed2001

Volume learning algorithm artificial neural networks for 3D QSAR studies.

The current study introduces a new method, the volume learning algorithm (VLA), for the investigation of three-dimensional quantitative structure-activity relationships (QSAR) of chemical compounds. This method incorporates the advantages of comparative molecular field analysis (CoMFA) and artificial neural network approaches. VLA is a combination of supervised and unsupervised neural networks applied to solve the same problem. The supervised algorithm is a feed-forward neural network trained with a back-propagation algorithm while the unsupervised network is a self-organizing map of Kohonen. The use of both of these algorithms makes it possible to cluster the input CoMFA field variables and to use only a small number of the most relevant parameters to correlate spatial properties of the molecules with their activity. The statistical coefficients calculated by the proposed algorithm for cannabimimetic aminoalkyl indoles were comparable to, or improved, in comparison to the original study using the partial least squares algorithm. The results of the algorithm can be visualized and easily interpreted. Thus, VLA is a new convenient tool for three-dimensional QSAR studies.

Algorithms↗

PubMed1997

A comparison of heuristic search algorithms for molecular docking.

This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone.

Algorithms↗

PubMed2001

Clinical evaluation of morphology discrimination: an algorithm for rhythm discrimination in cardioverter defibrillators.

The aim of this study was to test the new morphology discrimination diagnostic algorithm for ICDs that differentiates supraventricular tachycardias (SVTs) from VTs by analysis of ventricular depolarization complexes morphology. Twenty-five patients implanted with a St. Jude Ventritex single chamber ICD were studied during electrophysiological evaluation at predischarge and were followed for 7 +/- 4 months. Sensitivity and specificity for VT detection and overall diagnostic accuracy of the morphology discrimination algorithm were calculated on 326 detected events. At electrophysiological evaluation, the algorithm was tested during 67 episodes of right atrial pacing, during 119 episodes of RV pacing (at basal interventricular septum and RV apex) and during 27 episodes of sustained AF: specificity was 98%, sensitivity was 66%, and diagnostic accuracy was 80%. All episodes of AF were correctly diagnosed as SVT. Exclusion of detections related to pacing at the basal interventricular septum, resulted in a specificity of 98%, a sensitivity of 85%, and a diagnostic accuracy of 93%. During follow-up, evaluation of the morphology discrimination algorithm on 113 spontaneous episodes (31 VTs, 31 AF, 7 SVTs, and 44 sinus tachycardias) exhibited a specificity of 89%, a sensitivity of 100%, and a diagnostic accuracy of 92%. In conclusion, the morphology discrimination algorithm exhibits a high specificity in discriminating VTs from SVTs, although with a corresponding reduction in sensitivity. The preliminary experience on spontaneous episodes is promising. To correct for the reduction in sensitivity, it is advisable to use this algorithm in parallel with other algorithms for rhythm discrimination (sudden onset, stability) coupled with extended high rate.

Adult↗

PubMed2000

Clinical experience of a new rate drop response algorithm in the treatment of vasovagal and carotid sinus syncope.

Dual chamber pacing has proven beneficial in patients with sudden drops in heart rate as seen in vasovagal syncope and carotid sinus syndrome. Newer algorithms for faster detection of an insidious drop in heart rate and short lasting intervention pacing at a high rate, as in the rate drop response algorithm in the Medtronic Kappa series of pacemakers, might improve the effect of pacing. Two case reports, that demonstrate the use of these rate drop response algorithms, are presented. A 24-year-old woman with recurrent episodes of syncope and repeated tilt-table tests with vasovagal cardioinhibitory outcomes had a Medtronic Kappa 400 pacemaker implanted. Syncope was abolished during repeat tilt-table testing following pacemaker implantation and proper functioning of the rate drop response algorithm. The patient has been free of syncope during follow-up apart from a single episode that occurred due to neglect of vasovagal warning symptoms. A 52-year-old man with coronary artery disease developed recurrent blackouts. Carotid sinus massage resulted in 5.5 s of asystole and presyncope. A Medtronic Kappa 700 pacemaker with a rate drop response algorithm was implanted and the patient became asymptomatic. The rate drop response algorithm is discussed in detail based upon the case reports, and recommendations are given for the use of this algorithm in patients with vasovagal syncope and carotid sinus syndrome.

Adult↗

PubMed2001

A real-time ST-segment monitoring algorithm for implantable devices.

Continuous ST-segment monitoring by implantable devices may lead to clarification of the substrate of arrhythmias, clarification of the origin of nonspecific chest pain, and titration or preventative application of established anti-ischemic therapies. Although ST-segment monitoring algorithms are available for surface electrocardiogram, the computational demand of algorithms for implantable devices must be minimized for considerations of device longevity. The new algorithm first locates a fiducial point (FPT) at the dominant peak of each QRS complex. The ST-segment deviation (measured at 2 rate-adaptive delays after FPT, eg, FPT + 96 ms and FPT + 152 ms at 60 BPM) with respect to the isoelectric level (measured at the minimum slope preceding the QRS) is then measured. The following features are also quantified by simple operations: R-R interval, R-wave slope, R-wave amplitude, ST-segment slope, and noise content during the isoelectric segment. Inconsistencies in these features relative to their adaptive normal ranges are used to reject noisy or ectopic beats and sudden morphology changes. Finally, the ST-segment deviation over time is filtered to reject rates of change that are not likely attributable to human ischemia. Performance of the algorithm was evaluated on the European Society of Cardiology ST-T Database, which contains 180 hours of ambulatory electrocardiogram with 250 expert-annotated ischemic episodes. The sensitivity was 79% [74% 84%] (mean [95% CI]) and positive predictivity was 81% [76% 86%]. This performance is statistically equivalent to that of published electrocardiogram algorithms that were validated on the same dataset. Estimates of computational burden suggest that the algorithm could process two channels of electrogram continuously for more than 5 years with current implanted device technology. In conclusion, we have developed an algorithm for ST-segment monitoring that can be implemented in current implantable devices with sensitivity and positive predictivity that are comparable with the state-of-the-art.

Algorithms↗