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PubMed2004

A new algorithm for determining collimator angles that favor efficiency in MLC based IMRT delivery.

A new algorithm to determine collimator angles that favor delivery efficiency of intensity modulated radiotherapy plans was developed. It was found that the number of segments and monitor units (MUs) were largely reduced with the set of collimator angles determined with the new algorithm without compromising plan quality. The improvement of delivery efficiency using the new algorithm depends on the size and shape of the target(s), the number of modulation levels, and the type of leaf-sequencing algorithm. In a typical prostate case, when a sweeping leaf-sequencer is used for Varian 120 leaf (0.5 x 0.5 cm2 beamlet), 80 leaf (1 x 1 cm2 beamlet) and Elekta 40 leaf (1 x 1 cm2 beamlet), the number of segments was reduced by 42%, 29%, and 5%, respectively. The number of MUs was reduced by 41%, 35%, and 10%. For the Siemens MLC (IMFAST leaf sequencer, 1 x 1 cm2 beamlet) the segment reduction was 32% and the MU reduction was 14%. Comparison of the plans using the new and Brahme algorithms, in terms of target conformity index and dose volume histogram of the organs at risk, showed that the quality of the plans using the new algorithm was uncompromised. Similar results were obtained for a set of head and neck treatment plans.

Algorithms↗

PubMed2004

Modifications to the IMFAST leaf sequencing optimization algorithm.

The optimizing leaf sequencer IMFAST minimizes intensity modulated treatment times. However, algorithm modifications can yield improved results. Currently, during segment extraction, the largest extract for a given number of levels is chosen. The modification chooses an extract that yields the fewest segments and levels when the rod-pushing algorithm is applied to the difference between the original map and the extract. Also, successive optimization parameter values are now allowed to increase. These modifications reduced the number of segments and the relative fluence from the original algorithm by an average of 7%-11% and 8%-17%, respectively, depending on whether interdigitation and/or tongue-and-groove constraints were considered. The tests were done on two clinical head and neck intensity modulated radiation therapy cases. Compared to the sweeping window algorithm, a reduction of 35%-55% of the number of segments is possible with a change in the relative fluence of -9% - 16%, depending on the constraints. Compared to other previously published algorithms that deal with the constraints tested here, the modified IMFAST algorithm provides the greatest reduction in the number of segments with the minimum increase in the relative fluence.

Algorithms↗

PubMed2005

Tilted plane Feldkamp type reconstruction algorithm for spiral cone beam CT.

An approximate image reconstruction method for spiral cone beam computed tomography (CT), called tilted plane Feldkamp type reconstruction algorithm (TPFR), is presented in this paper, which extends Feldkamp cone beam reconstruction algorithm to deal with its inaccuracy and artifact problems caused by large cone angle. This is done by tilting the reconstructing planes to minimize the cone angle and optimally fit the spiral segment of the source. The tilted plane image reconstruction requires reforming the three-dimensional projection data set for the tilted plane and application of Feldkamp algorithm to the reformed data set. Analytical and computational results can show that the image reconstruction performance of the proposed TPFR algorithm is superior to that of the Feldkamp reconstruction algorithm in the image quality, volume coverage speed, maximum achievable pitch value, and slice sensitivity profiles. Moreover, it provides more accurate image reconstruction than the existing two-dimensional reconstruction algorithms.

Algorithms↗

PubMed2005

Matching and reconstruction of brachytherapy seeds using the Hungarian algorithm (MARSHAL).

Intraoperative dosimetric quality assurance in prostate brachytherapy critically depends on discerning the three-dimensional (3D) locations of implanted seeds. The ability to reconstruct the implanted seeds intraoperatively will allow us to make immediate provisions for dosimetric deviations from the optimal implant plan. A method for seed reconstruction from segmented C-arm fluoroscopy images is proposed. The 3D coordinates of the implanted seeds can be calculated upon resolving the correspondence of seeds in multiple x-ray images. We formalize seed-matching as a combinatorial optimization problem, which has salient features: (a) extensively studied solutions by the computer science community; (b) proof for the nonexistence of any polynomial time exact algorithm; and (c) a practical pseudo-polynomial algorithm that mostly runs in O(N3) time using any number of images. We prove that two images are insufficient to correctly match the seeds, while a third image renders the matching problem to be of nonpolynomial complexity. We utilize the special structure of the problem and propose a pseudopolynomial time algorithm. Using three presegmented images, matching and reconstruction of brachytherapy seeds using the Hungarian algorithm achieved complete matching in simulation experiments; and 98.5% in phantom experiments. 3D reconstruction error for correctly matched seeds has a mean of 0.63 mm, and 0.9 mm for incorrectly matched seeds. The maximum seed reconstruction error in each implant was typically around 1.32 mm. Both on synthetic data and in phantom experiments, matching rate and reconstruction error achieved using presegmented images was found to be sufficient for prostate brachytherapy. The algorithm is extendable to deal with arbitrary number of images without any loss in speed or accuracy. The algorithm is sufficiently generic to provide a practical solution to any correspondence problem, across different imaging modalities and features.

Algorithms↗

PubMedDate not supplied

A comparison of the speeds of three convolution algorithms.

The speeds of three computer algorithms suitable for use in three-dimensional radiotherapy planning codes were compared. Two of the algorithms are based on ray-tracing methods, the first algorithm uses a fast ray-tracing procedure directly and the second employs a table lookup procedure; the table was originally calculated by ray tracing. The third algorithm was a convolution procedure using the fast Fourier transform. Benchmark programs were written to compare the fundamental running speeds of the three algorithms operating on three-dimensional arrays of various sizes. The convolution procedure employing the three-dimensional fast Fourier transform had the shortest running times on a VAX/750 (Digital Equipment Corp.) computer. We concluded that this algorithm holds significant potential for practical three-dimensional dose calculations.

Algorithms↗

PubMed1994

A cone beam SPECT reconstruction algorithm with a displaced center of rotation.

A filtered backprojection (FBP) algorithm is derived based on Feldkamp's FBP algorithm for a cone beam geometry that has a displaced center of rotation. In cone beam single photon emission computed tomography (CB-SPECT) the center of rotation displacement can degrade the reconstructed images. The center of rotation displacement of interest is mechanical shift, which is the displacement of the midplane of the cone beam collimator off the rotation center. Mechanical shift is characterized by two orthogonal components: the shift of the midplane of the cone beam collimator along the direction of the axis of rotation, and the distance between the midline of the cone beam collimator and the axis of rotation. This new algorithm corrects mechanical shift directly by incorporating mechanical shift into the algorithm. This new algorithm is evaluated using both Monte Carlo simulated data and experimentally acquired data. The results demonstrate that this algorithm is able to correct for blurring and the "doughnut" type artifacts caused by system mechanical shift and improve the image resolution.

Algorithms↗

PubMed1998

Multileaf collimator leaf sequencing algorithm for intensity modulated beams with multiple static segments.

The "stop and shoot" method of producing intensity modulation using combinations of static multileaf collimator (MLC) segments has a number of advantages including precise dose delivery, easy verification, and general availability. However, due to the potential limitation of prolonged treatment time, it is essential to keep the number of required segments to a reasonable number. We propose an algorithm to minimize the number of segments for an intensity modulated field. In this algorithm, the sequence of delivery intensity is proposed to be a series of powers of 2, depending on the maximum intensity level in the matrix. The MLC leaf position sequence is designed directly on the two-dimensional intensity matrix to irradiate the largest possible area in each segment. The algorithm can be applied directly to MLC systems with different motion constraints. This algorithm has been evaluated by generating 1000 random 15 x 15 cm intensity matrices, each having from 3 to 16 intensity levels. Five clinical intensity modulated fields generated from the NOMOS CORVUS planning system for a complex clinical head and neck case were also tested with this and two other algorithms. The results of both the statistical and clinical studies showed that for all the intensity matrices tested, the proposed algorithm results in the smallest number of segments with a moderately increased monitor units. Thus it is well-suited for use in static MLC intensity modulation beam delivery. For MLC systems with interleaf motion constraint, we prove mathematically that this constraint reduces the tongue and groove effect at the expense of an increase of 25% in the number of segments.

Algorithms↗

PubMed1998

New classes of helical weighting algorithms with applications to fast CT reconstruction.

The focus of this paper is on CT helical weighting algorithms using one source rotation, or 2 pi, worth of projection data. Currently known 2 pi helical weighting algorithms include a fan-angle dependency, and do not lend themselves to fast reconstruction, for two reasons. First, it can be shown that the weight distributions present a line of discontinuity across the sinogram (projection space), which defines two separate sinogram regions. Second, the expressions for the weighting functions differ for those two regions. Accordingly, reconstruction of P different image planes (all using a given projection) requires P weightings and filterings of that projection. In this paper, it is shown that, by first generalizing the concept of the interpolation/extrapolation function used in the weighting, to the concept of distance function, and second by selecting particular classes of such distance functions, the discontinuity across the sinogram can be eliminated. By imposing specific sufficient conditions on such distance functions, single analytical expressions across the entire 2 pi sinogram are obtained. Decomposition of these particular "single" distance functions leads to two-filtering reconstruction algorithms, for which a given projection needs to be filtered only two times for an arbitrary number P of reconstruction planes. Finally, another generalization of the concept of helical weighting leads to one-filtering weight functions that depend only on the sum of the projection--and fan angles. Accordingly, after rebinning the fan-beam projections to parallel projections, the corresponding 2 pi helical weighting algorithms do not include a dependency over the ray parameter. Equivalently, for these algorithms, weighting commutes with filtering, and reconstruction of an arbitrary number P of image planes requires only one filtering per projection. These algorithms are shown to be consistent with the hypothesis of a linear z variation of the projections.

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PubMed2000

Photon scatter in portal images: accuracy of a fluence based pencil beam superposition algorithm.

The accuracy of a pencil beam algorithm to predict scattered photon fluence into portal imaging systems was studied. A data base of pencil beam kernels describing scattered photon fluence behind homogeneous water slabs (1-50 cm thick) at various air gap distances (0-100 cm) was generated using the EGS Monte Carlo code. Scatter kernels were partitioned according to particle history: singly-scattered, multiply-scattered, and bremsstrahlung and positron annihilation photons. Mean energy and mean angle with respect to the incident photon pencil beam were also scored. This data allows fluence, mean energy, and mean angular data for each history type to be predicted using the pencil beam algorithm. Pencil beam algorithm predictions for 6 and 24 MV incident photon beams were compared against full Monte Carlo simulations for several inhomogeneous phantoms, including approximations to a lateral neck, and a mediastinum treatment. The accuracy of predicted scattered photon fluence, mean energy, and mean angle was investigated as a function of air gap, field size, photon history, incident beam resolution, and phantom geometry. Maximum errors in mean energies were 0.65 and 0.25 MeV for the higher and lower energy spectra, respectively, and 15 degrees for mean angles. The ability of the pencil beam algorithm to predict scatter fluence decreases with decreasing air gap, with the largest error for each phantom occurring at the exit surface. The maximum predictive error was found to be 6.9% with respect to the total fluence on the central axis. By maintaining even a small air gap (approximately 10 cm), the error in predicted scatter fluence may be kept under 3% for the phantoms and beam energies studied here. It is concluded that this pencil beam algorithm is sufficiently accurate (using International Commission on Radiation Units and Measurements Report No. 24 guidelines for absorbed dose) over the majority of clinically relevant air gaps, for further investigation in a portal dose prediction algorithm.

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PubMed2004

Experimental verification of an interpolation algorithm for improved estimates of animal position.

This article presents experimental verification of an interpolation algorithm that was previously proposed in Jaffe [J. Acoust. Soc. Am. 105, 3168-3175 (1999)]. The goal of the algorithm is to improve estimates of both target position and target strength by minimizing a least-squares residual between noise-corrupted target measurement data and the output of a model of the sonar's amplitude response to a target at a set of known locations. Although this positional estimator was shown to be a maximum likelihood estimator, in principle, experimental verification was desired because of interest in understanding its true performance. Here, the accuracy of the algorithm is investigated by analyzing the correspondence between a target's true position and the algorithm's estimate. True target position was measured by precise translation of a small test target (bead) or from the analysis of images of fish from a coregistered optical imaging system. Results with the stationary spherical test bead in a high signal-to-noise environment indicate that a large increase in resolution is possible, while results with commercial aquarium fish indicate a smaller increase is obtainable. However, in both experiments the algorithm provides improved estimates of target position over those obtained by simply accepting the angular positions of the sonar beam with maximum output as target position. In addition, increased accuracy in target strength estimation is possible by considering the effects of the sonar beam patterns relative to the interpolated position. A benefit of the algorithm is that it can be applied "ex post facto" to existing data sets from commercial multibeam sonar systems when only the beam intensities have been stored after suitable calibration.

Acoustics↗

PubMed1988

Synthesizing a color algorithm from examples.

A lightness algorithm that separates surface reflectance from illumination in a Mondrian world is synthesized automatically from a set of examples, which consist of pairs of input (intensity signal) and desired output (surface reflectance) images. The algorithm, which resembles a new lightness algorithm recently proposed by Land, is approximately equivalent to filtering the image through a center-surround receptive field in individual chromatic channels. The synthesizing technique, optimal linear estimation, requires only one assumption, that the operator that transforms input into output is linear. This assumption is true for a certain class of early vision algorithms that may therefore be synthesized in a similar way from examples. Other methods of synthesizing algorithms from examples, or "learning," such as back-propagation, do not yield a significantly better lightness algorithm.

Algorithms↗

PubMed1996

Clinical algorithms for the screening of Chlamydia trachomatis in Turkish women.

OBJECTIVE: To test the diagnostic validity of clinical algorithms for the detection of Chlamydia trachomatis in an urban population of married women in Turkey. DESIGN: Cross-sectional population-based survey. SUBJECTS: A systematic sample of 867 women who reported the use of contraceptive methods. MAIN OUTCOME MEASURES: Sensitivity, specificity and positive predictive value of clinical algorithms for the diagnosis of C trachomatis. RESULTS: C trachomatis was diagnosed in 4.89% of the women. The WHO algorithm for use in settings where no vaginal examination could be performed had a sensitivity of 9% and a specificity of 96%. The corresponding figures for the WHO algorithm incorporating the findings of a speculum examination were 47% and 56% respectively. Algorithms incorporating symptoms or signs other than those suggested by the WHO did not yield satisfactory standards of validity. CONCLUSIONS: The findings of this study do not support the widespread introduction of the use of clinical decision models for screening of women for chlamydia infection in primary health care settings such as family planning or antenatal clinics. The large number of false positive results with the use of the clinical algorithms tested in this study would cause unnecessary costs to the health system and unnecessary interventions to the women treated.

Adult↗

PubMed2000

Validity of the vaginal discharge algorithm among pregnant and non-pregnant women in Nairobi, Kenya.

OBJECTIVE: To evaluate the validity of different algorithms for the diagnosis of gonococcal and chlamydial infections among pregnant and non-pregnant women consulting health services for vaginal discharge in Nairobi, Kenya. METHODS: Cross sectional study among 621 women with complaints of vaginal discharge in three city council clinics between April and August 1997. Women were interviewed and examined for symptoms and signs of sexually transmitted infections (STIs). Specimens were obtained for laboratory diagnosis of genital infections, HIV, and syphilis. The data were used to evaluate the Kenyan flow chart as well as several other generated algorithms. RESULTS: The mean age was 24 years and 334 (54%) were pregnant. The overall prevalence rates were: 50% candidiasis, 23% trichomoniasis, 9% bacterial vaginosis, 7% gonorrhoea, 9% chlamydia, 7% syphilis, and 22% HIV. In non-pregnant women, gonococcal and chlamydial infection was significantly associated with (1) demographic and behavioural risk markers such as being single, younger than 20 years, multiple sex partners in the previous 3 months; (2) symptom fever; and (3) signs including presence of yellow or bloody vaginal discharge, cervical mucopus, cervical erythema, and friability. Among pregnant women only young age, dysuria, and fever were significantly associated with cervical infection. However, none of these variables was either sensitive or specific enough for the diagnosis of cervical infection. Several algorithms were generated and applied to the study data. The algorithm including risk markers performed slightly better than the current Kenyan algorithm. CONCLUSION: STIs form a major problem in the Nairobi area and should be addressed accordingly. None of the tested algorithms for the treatment of vaginal discharge would constitute a marked improvement of the existing flow chart. Hence, better detection tools for the specific aetiology of vaginal discharge are urgently needed.

Adult↗

PubMed2000

Automating parallel implementation of neural learning algorithms.

Neural learning algorithms generally involve a number of identical processing units, which are fully or partially connected, and involve an update function, such as a ramp, a sigmoid or a Gaussian function for instance. Some variations also exist, where units can be heterogeneous, or where an alternative update technique is employed, such as a pulse stream generator. Associated with connections are numerical values that must be adjusted using a learning rule, and and dictated by parameters that are learning rule specific, such as momentum, a learning rate, a temperature, amongst others. Usually, neural learning algorithms involve local updates, and a global interaction between units is often discouraged, except in instances where units are fully connected, or involve synchronous updates. In all of these instances, concurrency within a neural algorithm cannot be fully exploited without a suitable implementation strategy. A design scheme is described for translating a neural learning algorithm from inception to implementation on a parallel machine using PVM or MPI libraries, or onto programmable logic such as FPGAs. A designer must first describe the algorithm using a specialised Neural Language, from which a Petri net (PN) model is constructed automatically for verification, and building a performance model. The PN model can be used to study issues such as synchronisation points, resource sharing and concurrency within a learning rule. Specialised constructs are provided to enable a designer to express various aspects of a learning rule, such as the number and connectivity of neural nodes, the interconnection strategies, and information flows required by the learning algorithm. A scheduling and mapping strategy is then used to translate this PN model onto a multiprocessor template. We demonstrate our technique using a Kohonen and backpropagation learning rules, implemented on a loosely coupled workstation cluster, and a dedicated parallel machine, with PVM libraries.

Algorithms↗

PubMed1995

Training neural networks by means of genetic algorithms working on very long chromosomes.

In the neural network/genetic algorithm community, rather limited success in the training of neural networks by genetic algorithms has been reported. In a paper by Whitley et al. (1991), he claims that, due to "the multiple representations problem", genetic algorithms will not effectively be able to train multilayer perceptrons, whose chromosomal representation of its weights exceeds 300 bits. In the following paper, by use of a "real-life problem", known to be non-trivial, and by a comparison with "classic" neural net training methods, I will try to show, that the modest success of applying genetic algorithms to the training of perceptrons, is caused not so much by the "multiple representations problems" as by the fact that problem-specific knowledge available is often ignored, thus making the problem unnecessarily tough for the genetic algorithm to solve. Special success is obtained by the use of a new fitness function, which takes into account the fact that the search performed by a genetic algorithm is holistic, and not local as is usually the case when perceptrons are trained by traditional methods.

Algorithms↗

PubMed1999

An experimental comparison of neural algorithms for independent component analysis and blind separation.

In this paper, we compare the performance of five prominent neural or adaptive algorithms designed for Independent Component Analysis (ICA) and blind source separation (BSS). In the first part of the study, we use artificial data for comparing the accuracy, convergence speed, computational load, and other relevant properties of the algorithms. In the second part, the algorithms are applied to three different real-world data sets. The task is either blind source separation or finding interesting directions in the data for visualisation purposes. We develop criteria for selecting the most meaningful basis vectors of ICA and measuring the quality of the results. The comparison reveals characteristic differences between the studied ICA algorithms. The most important conclusions of our comparison are robustness of the ICA algorithms with respect to modest modeling imperfections, and the superiority of fixed-point algorithms with respect to the computational load.

Algorithms↗

PubMed1999

A self-organizing algorithm for vector quantizer design applied to signal processing.

Vector quantization plays an important role in many signal processing problems, such as speech/speaker recognition and signal compression. This paper presents an unsupervised algorithm for vector quantizer design. Although the proposed method is inspired in Kohonen learning, it does not incorporate the classical definition of topological neighborhood as an array of nodes. Simulations are carried out to compare the performance of the proposed algorithm, named SOA (self-organizing algorithm), to that of the traditional LBG (Linde-Buzo-Gray) algorithm. The authors present an evaluation concerning the codebook design for Gauss-Markov and Gaussian sources, since the theoretic optimal performance bounds for these sources, as described by Shannon's Rate-Distortion Theory, are known. In speech and image compression, SOA codebooks lead to reconstructed (vector-quantized) signals with better quality as compared to the ones obtained by using LBG codebooks. Additionally, the influence of the initial codebook in the algorithm performance is investigated and the algorithm ability to learn representative patterns is evaluated. In a speaker identification system, it is shown that the the codebooks designed by SOA lead to higher identification rates when compared to the ones designed by LBG.

Algorithms↗

PubMed2004

cWINNOWER algorithm for finding fuzzy dna motifs.

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if a clique consisting of a sufficiently large number of mutated copies of the motif (i.e., the signals) is present in the DNA sequence. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum detectable clique size qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12,000 for (l, d) = (15, 4).

Algorithms↗