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PubMed2006

A faster converging snake algorithm to locate object boundaries.

A different contour search algorithm is presented in this paper that provides a faster convergence to the object contours than both the greedy snake algorithm (GSA) and the fast greedy snake (FGSA) algorithm. This new algorithm performs the search in an alternate skipping way between the even and odd nodes (snaxels) of a snake with different step sizes such that the snake moves to a likely local minimum in a twisting way. The alternative step sizes are adjusted so that the snake is less likely to be trapped at a pseudo-local minimum. The iteration process is based on a coarse-to-fine approach to improve the convergence. The proposed algorithm is compared with the FGSA algorithm that employs two alternating search patterns without altering the search step size. The algorithm is also applied in conjunction with the subband decomposition to extract face profiles in a hierarchical way.

Algorithms↗

PubMed2004

Regularized image reconstruction algorithms for positron emission tomography.

We develop algorithms for obtaining regularized estimates of emission means in positron emission tomography. The first algorithm iteratively minimizes a penalized maximum-likelihood (PML) objective function. It is based on standard de-coupled surrogate functions for the ML objective function and de-coupled surrogate functions for a certain class of penalty functions. As desired, the PML algorithm guarantees nonnegative estimates and monotonically decreases the PML objective function with increasing iterations. The second algorithm is based on an iteration dependent, de-coupled penalty function that introduces smoothing while preserving edges. For the purpose of making comparisons, the MLEM algorithm and a penalized weighted least-squares algorithm were implemented. In experiments using synthetic data and real phantom data, it was found that, for a fixed level of background noise, the contrast in the images produced by the proposed algorithms was the most accurate.

Algorithms↗

PubMed2006

Convergent incremental optimization transfer algorithms: application to tomography.

No convergent ordered subsets (OS) type image reconstruction algorithms for transmission tomography have been proposed to date. In contrast, in emission tomography, there are two known families of convergent OS algorithms: methods that use relaxation parameters, and methods based on the incremental expectation-maximization (EM) approach. This paper generalizes the incremental EM approach by introducing a general framework, "incremental optimization transfer." The proposed algorithms accelerate convergence speeds and ensure global convergence without requiring relaxation parameters. The general optimization transfer framework allows the use of a very broad family of surrogate functions, enabling the development of new algorithms. This paper provides the first convergent OS-type algorithm for (nonconcave) penalized-likelihood (PL) transmission image reconstruction by using separable paraboloidal surrogates (SPS) which yield closed-form maximization steps. We found it is very effective to achieve fast convergence rates by starting with an OS algorithm with a large number of subsets and switching to the new "transmission incremental optimization transfer (TRIOT)" algorithm. Results show that TRIOT is faster in increasing the PL objective than nonincremental ordinary SPS and even OS-SPS yet is convergent.

Algorithms↗

PubMed2005

Efficient training algorithms for a class of shunting inhibitory convolutional neural networks.

This article presents some efficient training algorithms, based on first-order, second-order, and conjugate gradient optimization methods, for a class of convolutional neural networks (CoNNs), known as shunting inhibitory convolution neural networks. Furthermore, a new hybrid method is proposed, which is derived from the principles of Quickprop, Rprop, SuperSAB, and least squares (LS). Experimental results show that the new hybrid method can perform as well as the Levenberg-Marquardt (LM) algorithm, but at a much lower computational cost and less memory storage. For comparison sake, the visual pattern recognition task of face/nonface discrimination is chosen as a classification problem to evaluate the performance of the training algorithms. Sixteen training algorithms are implemented for the three different variants of the proposed CoNN architecture: binary-, Toeplitz- and fully connected architectures. All implemented algorithms can train the three network architectures successfully, but their convergence speed vary markedly. In particular, the combination of LS with the new hybrid method and LS with the LM method achieve the best convergence rates in terms of number of training epochs. In addition, the classification accuracies of all three architectures are assessed using ten-fold cross validation. The results show that the binary- and Toeplitz-connected architectures outperform slightly the fully connected architecture: the lowest error rates across all training algorithms are 1.95% for Toeplitz-connected, 2.10% for the binary-connected, and 2.20% for the fully connected network. In general, the modified Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods, the three variants of LM algorithm, and the new hybrid/LS method perform consistently well, achieving error rates of less than 3% averaged across all three architectures.

Algorithms↗

PubMed2006

On algorithmic rate-coded AER generation.

This paper addresses the problem of converting a conventional video stream based on sequences of frames into the spike event-based representation known as the address-event-representation (AER). In this paper we concentrate on rate-coded AER. The problem is addressed as an algorithmic problem, in which different methods are proposed, implemented and tested through software algorithms. The proposed algorithms are comparatively evaluated according to different criteria. Emphasis is put on the potential of such algorithms for a) doing the frame-based to event-based representation in real time, and b) that the resulting event streams ressemble as much as possible those generated naturally by rate-coded address-event VLSI chips, such as silicon AER retinae. It is found that simple and straightforward algorithms tend to have high potential for real time but produce event distributions that differ considerably from those obtained in AER VLSI chips. On the other hand, sophisticated algorithms that yield better event distributions are not efficient for real time operations. The methods based on linear-feedback-shift-register (LFSR) pseudorandom number generation is a good compromise, which is feasible for real time and yield reasonably well distributed events in time. Our software experiments, on a 1.6-GHz Pentium IV, show that at 50% AER bus load the proposed algorithms require between 0.011 and 1.14 ms per 8 bit-pixel per frame. One of the proposed LFSR methods is implemented in real time hardware using a prototyping board that includes a VirtexE 300 FPGA. The demonstration hardware is capable of transforming frames of 64 x 64 pixels of 8-bit depth at a frame rate of 25 frames per second, producing spike events at a peak rate of 10(7) events per second.

Algorithms↗

PubMed2006

Study of a fast discriminative training algorithm for pattern recognition.

Discriminative training refers to an approach to pattern recognition based on direct minimization of a cost function commensurate with the performance of the recognition system. This is in contrast to the procedure of probability distribution estimation as conventionally required in Bayes' formulation of the statistical pattern recognition problem. Currently, most discriminative training algorithms for nonlinear classifier designs are based on gradient-descent (GD) methods for cost minimization. These algorithms are easy to derive and effective in practice, but are slow in training speed and have difficulty selecting the learning rates. To address the problem, we present our study on a fast discriminative training algorithm. The algorithm initializes the parameters by the expectation-maximization (EM) algorithm, and then uses a set of closed-form formulas derived in this paper to further optimize a proposed objective of minimizing error rate. Experiments in speech applications show that the algorithm provides better recognition accuracy in a fewer iterations than the EM algorithm and a neural network trained by hundreds of GD iterations. Although some convergent properties need further research, the proposed objective and derived formulas can benefit further study of the problem.

Algorithms↗

PubMed2006

The "invaders" algorithm: range of values modulation for accelerated correlation.

In this paper, we present an algorithm that allows the simultaneous calculation of several cross correlations. The algorithm works by shifting the range of values of different images/signals to occupy different orders of magnitude and then combining them to form a single composite image/signal. Because additional signals are placed in the space usually occupied by a single signal, we call this the "invaders algorithm," to imply that extra signals invade the space that normally belongs to a single signal. After correlation is performed, the individual results are recovered by performing the inverse operation. The limitations of the algorithm are imposed by the finite length of the mantissa of the hardware used, the precision of the algorithm that performs the cross correlation (e.g., the precision of the fast Fourier transform (FFT)) and by the actual values of the images/signals that are to be combined. The algorithm does not require any special hardware or special FFT algorithm. For typical 256 x 256 images, an acceleration by a factor of at least two in the calculation of their cross correlations is guaranteed using an ordinary PC or a laptop. As for smaller sized templates, tenfold accelerations may be achieved.

Algorithms↗

PubMed2005

Pose estimation for augmented reality applications using genetic algorithm.

This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.

Algorithms↗

PubMed2006

Variations over the message computation algorithm of lazy propagation.

Improving the performance of belief updating becomes increasingly important as real-world Bayesian networks continue to grow larger and more complex. In this paper, an investigation is done on how variations over the message-computation algorithm of lazy propagation may impact its performance. Lazy propagation is a junction-tree-based inference algorithm for belief updating in Bayesian networks. Lazy propagation combines variable elimination (VE) with a Shenoy-Shafer message-passing scheme in an attempt to exploit the independence properties induced by evidence in a junction-tree-based algorithm. The authors investigate, the use of arc reversal (AR) and symbolic probabilistic inference (SPI) as alternative algorithms for computing clique-to-clique messages in lazy propagation. The paper presents the results of an empirical evaluation of the performance of lazy propagation using AR, SPI, and VE as the message-computation algorithm. The results of the empirical evaluation show that no single algorithm outperforms or is outperformed by the other two alternatives. In many cases, there is no significant difference in the performance of the three algorithms.

Algorithms↗

PubMed2006

A relative reward-strength algorithm for the hierarchical structure learning automata operating in the general nonstationary multiteacher environment.

A new learning algorithm for the hierarchical structure learning automata (HSLA) operating in the nonstationary multiteacher environment (NME) is proposed. The proposed algorithm is derived by extending the original relative reward-strength algorithm to be utilized in the HSLA operating in the general NME. It is shown that the proposed algorithm ensures convergence with probability 1 to the optimal path under a certain type of the NME. Several computer-simulation results, which have been carried out in order to compare the relative performance of the proposed algorithm in some NMEs against those of the two of the fastest algorithms today, confirm the effectiveness of the proposed algorithm.

Algorithms↗

PubMed2006

Nutrition of the critically ill patient and effects of implementing a nutritional support algorithm in ICU.

AIM: To test whether a feeding algorithm could improve the nutritional support of intensive care patients. BACKGROUND: Numerous factors may impede delivery of both enteral and parenteral nutrition to patients in the intensive care unit. Often there is a discrepancy between what is prescribed and actual delivery of nutrients. The purpose of this study was to test the effect of a nutritional support algorithm in an intensive care unit mainly by using the enteral route and if necessary by combining enteral and parenteral nutrition. METHODS: In this prospective study, nutritional data were collected from routinely fed critically ill patients (controls, n=21) during the first three days following admission to the intensive care unit. A nutritional support algorithm was then implemented and nutritional data were collected from critically ill patients who participated in this intervention (intervention group, n=21). Data collected included the total amount of calories prescribed vs. received, onset of delivery of enteral nutrition, enteral vs. parenteral nutrition, and the use and size of enteral feeding tubes. RESULTS: Patients in the intervention group were both prescribed and actually received significantly larger amounts of nutrients than patients in the control group. They also received a larger proportion of their nutrients in the form of enteral nutrition. In addition, the nutritional support algorithm led to greater consistency in nursing practices with respect to aspiration of gastric content and rate of increment in enteral feeding. CONCLUSION: The study confirms that a nutritional support algorithm improved the delivery of nutrients to critically ill patients. The algorithm was most effective with respect to the delivery of enteral nutrition. The effect was primarily because of early and more rapid increment in the delivery of enteral nutrition administered by nurses based on improved physician orders. The combination of enteral and parenteral nutrition may contribute to meeting adequate nutritional requirements. RELEVANCE TO CLINICAL PRACTICE: By using a nutritional algorithm focused on enteral nutrition, but including parenteral nutrition as a supplement, it is possible to improve the delivery of clinical nutrition in the intensive care unit patients.

Algorithms↗

PubMed1994

A new pacing algorithm for overdrive suppression of atrial fibrillation. Chorus Multicentre Study Group.

Constant rapid pacing may suppress arrhythmias, but it is usually poorly tolerated in the long term. We report a pilot study of a new pacing algorithm for overdrive suppression of atrial premature complexes (APCs) and atrial fibrillation (AF), which prevents postextrasystolic pauses and varies the pacing rate in response to the frequency of APCs. The algorithm was tested in a multiple crossover study for 24 hours in dual chamber pacemakers implanted in 70 patients. Comparison was made on ambulatory recordings between the number of atrial arrhythmias commencing with the algorithm active and inactive. In all cases, the algorithm functioned as designed. No patient was aware of its operation, and no malignant arrhythmias were induced. The 36 recordings that showed atrial arrhythmia were included for analysis. The effects of the algorithm were: APCs (estimated from pacemaker statistics) reduced in 18 patients, increased in 8 (P = 0.02); atrial salvos reduced in 12, increased in 4 (P = 0.041); and AF reduced in 11, increased in 8 (P = NS). In all patients with frequent AF (> 5 episodes in total), fewer episodes occurred when the algorithm was active. We conclude that the algorithm is safe and well tolerated, reduces atrial ectopic activity, and may reduce the frequency of sustained atrial fibrillation.

Adult↗

PubMed1996

Limitations of tachycardia confirmation and rate classification algorithms in a third-generation implantable cardioverter defibrillator.

Newer ICDs provide antitachycardia (ATP) and bradycardia pacing and cardioversion and defibrillation shocks based on sensed interval criteria. The objectives of this investigation were to determine the algorithm related errors in tachycardia confirmation and rate classification that occurred in patients with a third-generation, noncommitted, tiered ICD therapy. Forty-three consecutive patients with the Guardian ATP 4210 ICD, which uses an X out of Y sensed interval counting algorithm for tachycardia detection, confirmation, and classification were studied. Surface ECGs, intracardiac electrograms, stored data logs, and sense histories were reviewed to diagnose errors due to these algorithms that resulted in delivery of inappropriate therapy or inhibition of appropriate therapy. Sixty-eight classification or confirmation algorithm errors from 7,610 tachycardia detections (< 1%) were diagnosed in 23 (53%) of 43 patients. Three types of errors not related to device or sensing lead malfunction or programming mistakes were seen. In 26 episodes, the confirmation algorithm failed to detect late tachycardia reversion of nonsustained tachyarrhythmias, on the last or next to last sensed interval, and did not inhibit ATP (n = 17) or shocks (n = 9). In 28 episodes, inaccurate classification of tachycardia rate resulted in inappropriate ATP (n = 23) or shock (n = 5) therapy. In 14 episodes, the posttherapy reconformation algorithm produced inhibition of VVI pacing and prolonged asystole following shock therapy. These errors in tachycardia confirmation and rate classification were due to the inherent limitations of the X out of Y counting algorithm.

Adult↗

PubMed1998

First experience with an automatic sensing algorithm in single-lead VDD stimulation.

UNLABELLED: An "Autosensing" algorithm available in SSI(R) and DDR(R) pacemakers automatically adapts the device's sensitivity to changing intracardiac signals. The atrial sensing function of this algorithm was tested for the first time with a VDD pacing system in which large variations of the atrial signal may occur because the atrial electrodes float in the atrial blood pool. METHODS: 15 patients with a VDD pacing system were studied (Unity 292-07, lead 425; Sulzer Intermedics). The atrial sensing threshold was measured, and the atrial sensitivity was programmed with a 2:1 safety margin. The autosensing algorithm and sensitivity profile were temporarily activated, and an ambulatory ECG with continuous marker annotation was recorded. All patients underwent a 30-minute daily life activities protocol. A beat-to-beat analysis of the ambulatory ECG was correlated with the changes in atrial sensitivity. RESULTS: The algorithm changed the baseline sensitivity from 0.57 +/- 0.23 mV during the test to 0.39 +/- 0.20 mV after the final rest period (P < 0.05). During the test 12.6 +/- 10.2 adaptations of the sensitivity occurred (range 0-33). In eight patients atrial undersensing occurred in 4.4% +/- 7.5% of the cycles (4-458 unsensed P waves). In these patients, the algorithm continuously adjusted the sensitivity towards more sensitive values, operating 19.1 +/- 18.3 changes compared with 5.4 +/- 7.3 changes in patients without undersensing (P = 0.009). Oversensing did not occur. CONCLUSION: The autosensing algorithm effectively optimized atrial sensitivity in VDD pacing. In patients with atrial undersensing the algorithm continuously remained near the most sensitive settings, thus reacting as intended. A faster sensitivity adjustment of the system would be desirable.

Activities of Daily Living↗

PubMed2005

A new simple iterative reconstruction algorithm for SPECT transmission measurement.

This paper proposes a new iterative reconstruction algorithm for transmission tomography and compares this algorithm with several other methods. The new algorithm is simple and resembles the emission ML-EM algorithm in form. Due to its simplicity, it is easy to implement and fast to compute a new update at each iteration. The algorithm also always guarantees non-negative solutions. Evaluations are performed using simulation studies and real phantom data. Comparisons with other algorithms such as convex, gradient, and logMLEM show that the proposed algorithm is as good as others and performs better in some cases.

Algorithms↗

PubMed2005

A three-dimensional reconstruction algorithm for an inverse-geometry volumetric CT system.

An inverse-geometry volumetric computed tomography (IGCT) system has been proposed capable of rapidly acquiring sufficient data to reconstruct a thick volume in one circular scan. The system uses a large-area scanned source opposite a smaller detector. The source and detector have the same extent in the axial, or slice, direction, thus providing sufficient volumetric sampling and avoiding cone-beam artifacts. This paper describes a reconstruction algorithm for the IGCT system. The algorithm first rebins the acquired data into two-dimensional (2D) parallel-ray projections at multiple tilt and azimuthal angles, followed by a 3D filtered backprojection. The rebinning step is performed by gridding the data onto a Cartesian grid in a 4D projection space. We present a new method for correcting the gridding error caused by the finite and asymmetric sampling in the neighborhood of each output grid point in the projection space. The reconstruction algorithm was implemented and tested on simulated IGCT data. Results show that the gridding correction reduces the gridding errors to below one Hounsfield unit. With this correction, the reconstruction algorithm does not introduce significant artifacts or blurring when compared to images reconstructed from simulated 2D parallel-ray projections. We also present an investigation of the noise behavior of the method which verifies that the proposed reconstruction algorithm utilizes cross-plane rays as efficiently as in-plane rays and can provide noise comparable to an in-plane parallel-ray geometry for the same number of photons. Simulations of a resolution test pattern and the modulation transfer function demonstrate that the IGCT system, using the proposed algorithm, is capable of 0.4 mm isotropic resolution. The successful implementation of the reconstruction algorithm is an important step in establishing feasibility of the IGCT system.

Algorithms↗

PubMed2005

Exact fan-beam and 4pi-acquisition cone-beam SPECT algorithms with uniform attenuation correction.

This paper presents analytical fan-beam and cone-beam reconstruction algorithms that compensate for uniform attenuation in single photon emission computed tomography. First, a fan-beam algorithm is developed by obtaining a relationship between the two-dimensional (2D) Fourier transform of parallel-beam projections and fan-beam projections. Using this relationship, 2D Fourier transforms of equivalent parallel-beam projection data are obtained from the fan-beam projection data. Then a quasioptimal analytical reconstruction algorithm for uniformly attenuated Radon data, developed by Metz and Pan, is used to reconstruct the image. A cone-beam algorithm is developed by extending the fan-beam algorithm to 4pi solid angle geometry. The cone-beam algorithm is also an exact algorithm.

Algorithms↗

PubMed2006

A topographic leaf-sequencing algorithm for delivering intensity modulated radiation therapy.

Topographic treatment is a radiation therapy delivery technique for fixed-gantry (nonrotational) treatments on a helical tomotherapy system. The intensity-modulated fields are created by moving the treatment couch relative to a fan-beam positioned at fixed gantry angles. The delivered dose distribution is controlled by moving multileaf collimator (MLC) leaves into and out of the fan beam. The purpose of this work was to develop a leaf-sequencing algorithm for creating topographic MLC sequences. Topographic delivery was modeled using the analogy of a water faucet moving over a collection of bottles. The flow rate per unit length of the water from the faucet represented the photon fluence per unit length along the width of the fan beam, the collection of bottles represented the pixels in the treatment planning fluence map, and the volume of water collected in each bottle represented the delivered fluence. The radiation fluence per unit length delivered to the target at a given position is given by the convolution of the intensity distribution per unit length over the width of the beam and the time per unit distance along the direction of travel that an MLC leaf is open. The MLC opening times for the desired dose profiles were determined using a technique based on deconvolution using a genetic algorithm. The MLC opening times were expanded in terms of a Fourier series, and a genetic algorithm was used to find the best expansion coefficients for a given dose distribution. A series of wedge shapes (15, 30, 45, and 60 deg) and "dose well" test fluence maps were created to test the algorithm's ability to generate topographic leaf sequences. The accuracy of the leaf-sequencing algorithm was measured on a helical tomotherapy system using radiographic film placed at depth in water equivalent material. The measured dose profiles were compared with the desired dose distributions. The agreement was within +/- 2% or 2 mm distance-to-agreement (DTA) in the high dose gradient regions for all test cases. The central axis measured dose was between 3.6% and 4.2% higher than the expected dose for the wedge cases. For the "dose well" test cases, the calculated and measured doses agreed to within +/- 0.5% at the peak and within +/- 1.6% in the "dose well." The topographic leaf-sequencing algorithm produced deliverable dose distributions that agreed well with the calculated dose distributions. This delivery technique could be used for treatment of whole intact breast. However, additional work is needed to further improve the algorithm in order to get better agreement between the calculated, deliverable, and measured dose distributions.

Algorithms↗