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PubMed2000

Implementation of pencil kernel and depth penetration algorithms for treatment planning of proton beams.

The implementation of two algorithms for calculating dose distributions for radiation therapy treatment planning of intermediate energy proton beams is described. A pencil kernel algorithm and a depth penetration algorithm have been incorporated into a commercial three dimensional treatment planning system (Helax-TMS, Helax AB, Sweden) to allow conformal planning techniques using irregularly shaped fields, proton range modulation, range modification and dose calculation for non-coplanar beams. The pencil kernel algorithm is developed from the Fermi Eyges formalism and Molière multiple-scattering theory with range straggling corrections applied. The depth penetration algorithm is based on the energy loss in the continuous slowing down approximation with simple correction factors applied to the beam penumbra region and has been implemented for fast, interactive treatment planning. Modelling of the effects of air gaps and range modifying device thickness and position are implicit to both algorithms. Measured and calculated dose values are compared for a therapeutic proton beam in both homogeneous and heterogeneous phantoms of varying complexity. Both algorithms model the beam penumbra as a function of depth in a homogeneous phantom with acceptable accuracy. Results show that the pencil kernel algorithm is required for modelling the dose perturbation effects from scattering in heterogeneous media.

Algorithms↗
PubMed2006

A BPF-type algorithm for CT with a curved PI detector.

Helical cone-beam CT is used widely nowadays because of its rapid scan speed and efficient utilization of x-ray dose. Recently, an exact reconstruction algorithm for helical cone-beam CT was proposed (Zou and Pan 2004a Phys. Med. Biol. 49 941-59). The algorithm is referred to as a backprojection-filtering (BPF) algorithm. This BPF algorithm for a helical cone-beam CT with a flat-panel detector (FPD-HCBCT) requires minimum data within the Tam-Danielsson window and can naturally address the problem of ROI reconstruction from data truncated in both longitudinal and transversal directions. In practical CT systems, detectors are expensive and always take a very important position in the total cost. Hence, we work on an exact reconstruction algorithm for a CT system with a detector of the smallest size, i.e., a curved PI detector fitting the Tam-Danielsson window. The reconstruction algorithm is derived following the framework of the BPF algorithm. Numerical simulations are done to validate our algorithm in this study.

Algorithms↗
PubMed2006

BEAM: a beam search algorithm for the identification of cis-regulatory elements in groups of genes.

The identification of potential protein binding sites (cis-regulatory elements) in the upstream regions of genes is key to understanding the mechanisms that regulate gene expression. To this end, we present a simple, efficient algorithm, BEAM (beam-search enumerative algorithm for motif finding), aimed at the discovery of cis-regulatory elements in the DNA sequences upstream of a related group of genes. This algorithm dramatically limits the search space of expanded sequences, converting the problem from one that is exponential in the length of motifs sought to one that is linear. Unlike sampling algorithms, our algorithm converges and is capable of finding statistically overrepresented motifs with a low failure rate. Further, our algorithm is not dependent on the objective function or the organism used. Limiting the space of candidate motifs enables the algorithm to focus only on those motifs that are most likely to be biologically relevant and enables the algorithm to use direct evaluations of background frequencies instead of resorting to probabilistic estimates. In addition, limiting the space of candidate motifs makes it possible to use computationally expensive objective functions that are able to correctly identify biologically relevant motifs.

Algorithms↗
PubMed1999

A simple algorithm for detecting circular permutations in proteins.

MOTIVATION: Circular permutation of a protein is a genetic operation in which part of the C-terminal of the protein is moved to its N-terminal. Recently, it has been shown that proteins that undergo engineered circular permutations generally maintain their three dimensional structure and biological function. This observation raises the possibility that circular permutation has occurred in Nature during evolution. In this scenario a protein underwent circular permutation into another protein, thereafter both proteins further diverged by standard genetic operations. To study this possibility one needs an efficient algorithm that for a given pair of proteins can detect the underlying event of circular permutations. A possible formal description of the question is: given two sequences, find a circular permutation of one of them under which the edit distance between the proteins is minimal. A naive algorithm might take time proportional to N3 or even N4, which is prohibitively slow for a large-scale survey. A sophisticated algorithm that runs in asymptotic time of N2 was recently suggested, but it is not practical for a large-scale survey. RESULTS: A simple and efficient algorithm that runs in time N2 is presented. The algorithm is based on duplicating one of the two sequences, and then performing a modified version of the standard dynamic programming algorithm. While the algorithm is not guaranteed to find the optimal results, we present data that indicate that in practice the algorithm performs very well. AVAILABILITY: A Fortran program that calculates the optimal edit distance under circular permutation is available upon request from the authors. CONTACT: ron@biocom1.ls.biu.ac.il.

Algorithms↗
PubMed2005

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm.

MOTIVATION: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods give results which are dependent on the initialization of the algorithm. Therefore, it is difficult to assess the significance of the results. We have developed a consensus clustering algorithm, where the final result is averaged over multiple clustering runs, giving a robust and reproducible clustering, capable of capturing small signal variations. The algorithm preserves valuable properties of hierarchical clustering, which is useful for visualization and interpretation of the results. RESULTS: We show for the first time that one can take advantage of multiple clustering runs in DNA microarray analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset. The method is flexible and it is possible to find consensus clusters from different clustering algorithms. Thus, the algorithm can be used as a framework to test in a quantitative manner the homogeneity of different clustering algorithms. We compare the method with a number of state-of-the-art clustering methods. It is shown that the method is robust and gives low classification error rates for a realistic, simulated dataset. The algorithm is also demonstrated for real datasets. It is shown that more biological meaningful transcriptional patterns can be found without conservative statistical or fold-change exclusion of data. AVAILABILITY: Matlab source code for the clustering algorithm ClusterLustre, and the simulated dataset for testing are available upon request from T.G. and O.W.

Algorithms↗
PubMed2000

A note on algorithms for genotype and allele elimination in complex pedigrees with incomplete genotype data.

Elimination of genotypes or alleles for each individual or meiosis, which are inconsistent with observed genotypes, is a component of various genetic analyses of complex pedigrees. Computational efficiency of the elimination algorithm is critical in some applications such as genotype sampling via descent graph Markov chains. We present an allele elimination algorithm and two genotype elimination algorithms for complex pedigrees with incomplete genotype data. We modify all three algorithms to incorporate inheritance restrictions imposed by a complete or incomplete descent graph such that every inconsistent complete descent graph is detected in any pedigree, and every inconsistent incomplete descent graph is detected in any pedigree without loops with the genotype elimination algorithms. Allele elimination requires less CPU time and memory, but does not always eliminate all inconsistent alleles, even in pedigrees without loops. The first genotype algorithm produces genotype lists for each individual, which are identical to those obtained from the Lange-Goradia algorithm, but exploits the half-sib structure of some populations and reduces CPU time. The second genotype elimination algorithm deletes more inconsistent genotypes in pedigrees with loops and detects more illegal, incomplete descent graphs in such pedigrees.

Adult↗
PubMed2002

Genetic algorithms and parallel processing in maximum-likelihood phylogeny inference.

We investigated the usefulness of a parallel genetic algorithm for phylogenetic inference under the maximum-likelihood (ML) optimality criterion. Parallelization was accomplished by assigning each "individual" in the genetic algorithm "population" to a separate processor so that the number of processors used was equal to the size of the evolving population (plus one additional processor for the control of operations). The genetic algorithm incorporated branch-length and topological mutation, recombination, selection on the ML score, and (in some cases) migration and recombination among subpopulations. We tested this parallel genetic algorithm with large (228 taxa) data sets of both empirically observed DNA sequence data (for angiosperms) as well as simulated DNA sequence data. For both observed and simulated data, search-time improvement was nearly linear with respect to the number of processors, so the parallelization strategy appears to be highly effective at improving computation time for large phylogenetic problems using the genetic algorithm. We also explored various ways of optimizing and tuning the parameters of the genetic algorithm. Under the conditions of our analyses, we did not find the best-known solution using the genetic algorithm approach before terminating each run. We discuss some possible limitations of the current implementation of this genetic algorithm as well as of avenues for its future improvement.

Algorithms↗
PubMed1990

A single TLD dose algorithm to satisfy federal standards and typical field conditions.

Modern whole-body dosimeters are often required to accurately measure the absorbed dose in a wide range of radiation fields. While programs are commonly developed around the fields tested as part of the National Voluntary Accreditation Program (NVLAP), the actual fields of application may be significantly different. Dose algorithms designed to meet the NVLAP standard, which emphasizes photons and high-energy beta radiation, may not be capable of the beta-energy discrimination necessary for accurate assessment of absorbed dose in the work environment. To address this problem, some processors use one algorithm for NVLAP testing and one or more different algorithms for the work environments. After several years of experience with a multiple algorithm approach, the Dosimetry Services Group of Yankee Atomic Electric Company (YAEC) developed a one-algorithm system for use with a four-element TLD badge using Li2B4O7 and CaSO4 phosphors. The design of the dosimeter allows the measurement of the effective energies of both photon and beta components of the radiation field, resulting in excellent mixed-field capability. The algorithm was successfully tested in all of the NVLAP photon and beta fields, as well as several non-NVLAP fields representative of the work environment. The work environment fields, including low- and medium-energy beta radiation and mixed fields of low-energy photons and beta particles, are often more demanding than the NVLAP fields. This paper discusses the development of the algorithm as well as some results of the system testing including: mixed-field irradiations, angular response, and a unique test to demonstrate the stability of the algorithm. An analysis of the uncertainty of the reported doses under various irradiation conditions is also presented.

Algorithms↗
PubMed1997

Corneal topography reconstruction algorithm that avoids the skew ray ambiguity and the skew ray error.

BACKGROUND: Because corneal shape is typically measured with Placido ring targets, there is an ambiguity in determining which point on the ring corresponds to which point on the image. This ambiguity is expected to lead to errors (which we call the skew ray error) in reconstructing the corneal shape from Placido ring videokeratoscope (VKS) images. METHODS: A coordinate system based on cylindrical coordinates is developed for handling the case when the corneal normal does not lie in the meridional plane. A simple solution is found for the forward problem of locating the Placido ring object given the VKS image and the corneal slope. RESULTS: Algorithms for solving two inverse problems are developed: (1) the inverse problem of determining the Placido image given the Placido ring object and the corneal shape, and (2) the inverse problem of reconstructing the corneal shape based on knowledge of the Placido ring object and image. The algorithm compensates for the skew ray error and does not assume the cornea to be small. Both inverse algorithms are applied to a corneal shape with eight-fold corrugations similar to what might occur in radial keratotomy (RK). The reconstruction algorithm assumes sufficient smoothness for an arc-step algorithm to be possible. We find that the reconstruction algorithm does an excellent job of obtaining the correct corneal shape without the skew ray error. CONCLUSIONS: The concrete reconstruction algorithm demonstrates that one can recover the correct corneal shape just from the reflection of the Placido rings. A dart board pattern is not necessary for removing the skew ray ambiguity, as long as the cornea has sufficient smoothness in the radial direction, an assumption common to all reconstruction algorithms.

Algorithms↗
PubMed1999

A pacemaker working status telemonitoring algorithm.

To extend the application of a previously developed home ECG and blood pressure telemonitoring system for pacemaker users, a specially designed pacemaker working status analysis algorithm is developed in this paper. This paper includes four sections. First, a pacing beat and spontaneous beat recognition algorithm are established in which a FIR filter and three threshold methods are used to pick up the pacing spikes and a dynamic threshold modification method is proposed for error elimination. Second, a beat classification algorithm is developed based on decision rules for six commonly used pacemaker types. Third, a pacemaker malfunction recognition algorithm is established to evaluate the pacemaker working status. Fourth, the statistics of the analysis and the report are also provided. To validate the algorithm, clinical data were collected and manually classified by specialists. Then, the classification and recognition results were obtained with the clinical data. Results show that the algorithm can achieve a recognition rate of 98.4%. Results also indicate that the algorithm is capable of working in real-time speed. The algorithm has been incorporated into the telemonitoring system, and trial application cases are also reported.

Algorithms↗
PubMed2005

Improved K-means clustering algorithm for exploring local protein sequence motifs representing common structural property.

Information about local protein sequence motifs is very important to the analysis of biologically significant conserved regions of protein sequences. These conserved regions can potentially determine the diverse conformation and activities of proteins. In this work, recurring sequence motifs of proteins are explored with an improved K-means clustering algorithm on a new dataset. The structural similarity of these recurring sequence clusters to produce sequence motifs is studied in order to evaluate the relationship between sequence motifs and their structures. To the best of our knowledge, the dataset used by our research is the most updated dataset among similar studies for sequence motifs. A new greedy initialization method for the K-means algorithm is proposed to improve traditional K-means clustering techniques. The new initialization method tries to choose suitable initial points, which are well separated and have the potential to form high-quality clusters. Our experiments indicate that the improved K-means algorithm satisfactorily increases the percentage of sequence segments belonging to clusters with high structural similarity. Careful comparison of sequence motifs obtained by the improved and traditional algorithms also suggests that the improved K-means clustering algorithm may discover some relatively weak and subtle sequence motifs, which are undetectable by the traditional K-means algorithms. Many biochemical tests reported in the literature show that these sequence motifs are biologically meaningful. Experimental results also indicate that the improved K-means algorithm generates more detailed sequence motifs representing common structures than previous research. Furthermore, these motifs are universally conserved sequence patterns across protein families, overcoming some weak points of other popular sequence motifs. The satisfactory result of the experiment suggests that this new K-means algorithm may be applied to other areas of bioinformatics research in order to explore the underlying relationships between data samples more effectively.

Algorithms↗
PubMed2005

A noniterative greedy algorithm for multiframe point correspondence.

This paper presents a framework for finding point correspondences in monocular image sequences over multiple frames. The general problem of multiframe point correspondence is NP-hard for three or more frames. A polynomial time algorithm for a restriction of this problem is presented and is used as the basis of the proposed greedy algorithm for the general problem. The greedy nature of the proposed algorithm allows it to be used in real-time systems for tracking and surveillance, etc. In addition, the proposed algorithm deals with the problems of occlusion, missed detections, and false positives by using a single noniterative greedy optimization scheme and, hence, reduces the complexity of the overall algorithm as compared to most existing approaches where multiple heuristics are used for the same purpose. While most greedy algorithms for point tracking do not allow for entry and exit of the points from the scene, this is not a limitation for the proposed algorithm. Experiments with real and synthetic data over a wide range of scenarios and system parameters are presented to validate the claims about the performance of the proposed algorithm.

Algorithms↗
PubMed2005

Dynamic algorithms for the shortest path routing problem: learning automata-based solutions.

This paper presents the first Learning Automaton-based solution to the dynamic single source shortest path problem. It involves finding the shortest path in a single-source stochastic graph topology where there are continuous probabilistic updates in the edge-weights. The algorithm is significantly more efficient than the existing solutions, and can be used to find the "statistical" shortest path tree in the "average" graph topology. It converges to this solution irrespective of whether there are new changes in edge-weights taking place or not. In such random settings, the proposed learning automata solution converges to the set of shortest paths. On the other hand, the existing algorithms will fail to exhibit such a behavior, and would recalculate the affected shortest paths after each weight-change. The important contribution of the proposed algorithm is that all the edges in a stochastic graph are not probed, and even if they are, they are not all probed equally often. Indeed, the algorithm attempts to almost always probe only those edges that will be included in the shortest path graph, while probing the other edges minimally. This increases the performance of the proposed algorithm. All the algorithms were tested in environments where edge-weights change stochastically, and where the graph topologies undergo multiple simultaneous edge-weight updates. Its superiority in terms of the average number of processed nodes, scanned edges and the time per update operation, when compared with the existing algorithms, was experimentally established. The algorithm can be applicable in domains ranging from ground transportation to aerospace, from civilian applications to military, from spatial database applications to telecommunications networking.

Algorithms↗
PubMed2004

An algorithm for the use of Medicare claims data to identify women with incident breast cancer.

OBJECTIVE: To develop and validate a clinically informed algorithm that uses solely Medicare claims to identify, with a high positive predictive value, incident breast cancer cases. DATA SOURCE: Population-based Surveillance, Epidemiology, and End Results (SEER) Tumor Registry data linked to Medicare claims, and Medicare claims from a 5 percent random sample of beneficiaries in SEER areas. STUDY DESIGN: An algorithm was developed using claims from 1995 breast cancer patients from the SEER-Medicare database, as well as 1995 claims from Medicare control subjects. The algorithm was validated on claims from breast cancer subjects and controls from 1994. The algorithm development process used both clinical insight and logistic regression methods. DATA EXTRACTION: Training set: Claims from 7,700 SEER-Medicare breast cancer subjects diagnosed in 1995, and 124,884 controls. Validation set: Claims from 7,607 SEER-Medicare breast cancer subjects diagnosed in 1994, and 120,317 controls. PRINCIPAL FINDINGS: A four-step prediction algorithm was developed and validated. It has a positive predictive value of 89 to 93 percent, and a sensitivity of 80 percent for identifying incident breast cancer. The sensitivity is 82-87 percent for stage I or II, and lower for other stages. The sensitivity is 82-83 percent for women who underwent either breast-conserving surgery or mastectomy, and is similar across geographic sites. A cohort identified with this algorithm will have 89-93 percent incident breast cancer cases, 1.5-6 percent cancer-free cases, and 4-5 percent prevalent breast cancer cases. CONCLUSIONS: This algorithm has better performance characteristics than previously proposed algorithms. The ability to examine national patterns of breast cancer care using Medicare claims data would open new avenues for the assessment of quality of care.

Aged↗
PubMed2004

Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions.

OBJECTIVE: To examine the effects of varying diagnostic and pharmaceutical criteria on the performance of claims-based algorithms for identifying beneficiaries with hypertension, heart failure, chronic lung disease, arthritis, glaucoma, and diabetes. STUDY SETTING: Secondary 1999-2000 data from two Medicare+Choice health plans. STUDY DESIGN: Retrospective analysis of algorithm specificity and sensitivity. DATA COLLECTION: Physician, facility, and pharmacy claims data were extracted from electronic records for a sample of 3,633 continuously enrolled beneficiaries who responded to an independent survey that included questions about chronic diseases. PRINCIPAL FINDINGS: Compared to an algorithm that required a single medical claim in a one-year period that listed the diagnosis, either requiring that the diagnosis be listed on two separate claims or that the diagnosis to be listed on one claim for a face-to-face encounter with a health care provider significantly increased specificity for the conditions studied by 0.03 to 0.11. Specificity of algorithms was significantly improved by 0.03 to 0.17 when both a medical claim with a diagnosis and a pharmacy claim for a medication commonly used to treat the condition were required. Sensitivity improved significantly by 0.01 to 0.20 when the algorithm relied on a medical claim with a diagnosis or a pharmacy claim, and by 0.05 to 0.17 when two years rather than one year of claims data were analyzed. Algorithms that had specificity more than 0.95 were found for all six conditions. Sensitivity above 0.90 was not achieved all conditions. CONCLUSIONS: Varying claims criteria improved the performance of case-finding algorithms for six chronic conditions. Highly specific, and sometimes sensitive, algorithms for identifying members of health plans with several chronic conditions can be developed using claims data.

Algorithms↗
PubMed1990

A randomized double-blind, cross-over study of the linear and nonlinear algorithms for the QT sensing rate adaptive pacemaker.

We have compared the pacing rate responses during cardiopulmonary exercise testing in 11 patients (mean 59 years, six female) with implanted QT sensing rate adaptive pacemakers who were randomly programmed to 1-month periods in the linear and nonlinear algorithms using a double-blind, cross-over design. Exercise testing was performed at the end of each month block and symptoms were scored with the MacMaster questionnaire. With exercise, the time to a 10 beats/min increment in rate was significantly less with the nonlinear compared to the linear algorithm (126 sec vs 255 sec, P = 0.02) but there were no significant differences in exercise duration, the peak pacing rate, the peak VO2, the VO2 at the anaerobic threshold or the mean correlation coefficients of the pacing rate VO2 relationship. Rate oscillation occurred in seven patients in the linear algorithm and in two patients in the nonlinear setting. Initial deceleration of the pacing rate at the onset of exercise occurred in seven patients in the linear algorithm and in four patients in the nonlinear setting. The nonlinear algorithm is associated with a faster response time during exercise and fewer instances of rate instability. However, it has not overcome the problem of a dip in the pacing rate at the beginning of exercise. The major difference in the function of the two algorithms is faster initial acceleration with the nonlinear algorithm. This is explained by the significantly higher values of the slope setting at the lower rate limit for the nonlinear versus the linear algorithm (6.3 ms/ms vs 5.1 ms/ms).

Adult↗
PubMed1997

A new generation of algorithms for computerized threshold perimetry, SITA.

PURPOSE: The purpose of this work was to develop a new family of test algorithms for computerized static threshold perimetry which significantly reduces test time without any reduction of data quality. METHODS: A comprehensive visual field model constructed from available knowledge of normal and glaucomatous visual fields is continuously updated during testing. The model produces threshold estimates and also estimates of the certainty to which the threshold is known at each point. Testing is interrupted at each test location at predetermined levels of threshold certainty. New time-saving methods are employed for estimation of false answers, and test pacing is optimized. After completion of the test, all threshold estimates are re-computed, taking into account the complete body of patient responses. Computer simulations were used to optimize the different parameters of the new algorithms, to evaluate the relative importance of those parameters, and to evaluate the performance of the algorithm as a whole in comparison with a standard algorithm. RESULTS: Simulated test results obtained with this algorithm were slightly more accurate than those of the Humphrey Full Threshold test algorithm. The number of simulated stimuli presented was reduced by an average of 29% in normal fields and 26% in glaucomatous fields. Actual clinical test time should be further reduced, since the influence of the improved timing algorithm was not included in the simulations. CONCLUSIONS: We applied new methods which take available knowledge of visual field physiology and pathophysiology into account, and employ modern computer-intensive mathematical methods for real time estimates of threshold values and threshold error estimates. In this way it was possible to design a family of testing algorithms which significantly reduced perimetric test time without any loss of quality in results.

Algorithms↗
PubMed2004

Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium.

An extensive set of benchmark measurement of PDDs and beam profiles was performed in a heterogeneous layer phantom, including a lung equivalent heterogeneity, by means of several detectors and compared against the predicted dose values by different calculation algorithms in two treatment planning systems. PDDs were measured with TLDs, plane parallel and cylindrical ionization chambers and beam profiles with films. Additionally, Monte Carlo simulations by means of the PENELOPE code were performed. Four different field sizes (10 x 10, 5 x 5, 2 x 2, and 1 x 1 cm2) and two lung equivalent materials (CIRS, p(w)e=0.195 and St. Bartholomew Hospital, London, p(w)e=0.244-0.322) were studied. The performance of four correction-based algorithms and one based on convolution-superposition was analyzed. The correction-based algorithms were the Batho, the Modified Batho, and the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system and the TMS Pencil Beam from the Helax-TMS (Nucletron) treatment planning system. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. The only studied calculation methods that correlated successfully with the measured values with a 2% average inside all media were the Collapsed Cone and the Monte Carlo simulation. The biggest difference between the predicted and the delivered dose in the beam axis was found for the EqTAR algorithm inside the CIRS lung equivalent material in a 2 x 2 cm2 18 MV x-ray beam. In these conditions, average and maximum difference against the TLD measurements were 32% and 39%, respectively. In the water equivalent part of the phantom every algorithm correctly predicted the dose (within 2%) everywhere except very close to the interfaces where differences up to 24% were found for 2 x 2 cm2 18 MV photon beams. Consistent values were found between the reference detector (ionization chamber in water and TLD in lung) and Monte Carlo simulations, yielding minimal differences (0.4%+/-1.2%). The penumbra broadening effect in low density media was not predicted by any of the correction-based algorithms, and the only one that matched the experimental values and the Monte Carlo simulations within the estimated uncertainties was the Collapsed Cone Algorithm.

Algorithms↗