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Results for “Measuring algorithm”

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PubMed2001

A numerical method to predict the effects of frequency-dependent attenuation and dispersion on speed of sound estimates in cancellous bone.

Many studies have demonstrated that time-domain speed-of-sound (SOS) measurements in calcaneus are predictive of osteoporotic fracture risk. However, there is a lack of standardization for this measurement. Consequently, different investigators using different measurement systems and analysis algorithms obtain disparate quantitative values for calcaneal SOS, impairing and often precluding meaningful comparison and/or pooling of measurements. A numerical method has been developed to model the effects of frequency-dependent attenuation and dispersion on transit-time-based SOS estimates. The numerical technique is based on a previously developed linear system analytic model for Gaussian pulses propagating through linearly attenuating, weakly dispersive media. The numerical approach is somewhat more general in that it can be used to predict the effects of arbitrary pulse shapes and dispersion relationships. The numerical technique, however, utilizes several additional assumptions (compared with the analytic model) which would be required for the practical task of correcting existing clinical databases. These include a single dispersion relationship for all calcaneus samples, a simple linear model relating phase velocity to broadband ultrasonic attenuation, and a constant calcaneal thickness. Measurements on a polycarbonate plate and 30 human calcaneus samples were in good quantitative agreement with numerical predictions. In addition, the numerical approach predicts that in cancellous bone, frequency-dependent attenuation tends to be a greater contributor to variations in transit-time-based SOS estimates than dispersion. This approach may be used to adjust previously acquired individual measurements so that SOS data recorded with different devices using different algorithms may be compared in a meaningful fashion.

Calcaneus↗

PubMed1997

Computerized ventilator data selection: artifact rejection and data reduction.

OBJECTIVE: To determine acceptable strategies for automated data acquisition and artifact rejection from computerized ventilators using the Medical Information Bus. DESIGN: Medical practitioners were surveyed to establish 'clinically important' ventilator events. A prospective study involving frequent data collection from ventilators was also conducted. SUBJECTS: Data from 10 adult patients were collected every 10 seconds from a Puritan Bennett 7200A ventilator for a total of 617.1 hours. INTERVENTIONS: Twelve different computerized data selection and artifact algorithms were tested and evaluated. MEASUREMENTS AND MAIN RESULTS: Data derived from 12 data selection algorithms were compared with each other and with data manually charted by respiratory therapists into a computerized charting system. Ventilator setting data collected by the algorithms, such as FIO2, reduced the amount of data collected to about 25% compared to manually charted data. The amount of data collected for measured parameters, such as tidal volume, from the ventilator had large variability and many artifacts. Automated data capture and selection generally increased the amount of data collected compared to manual charting, for example for the 3 minute median the increase was a modest 1.2 times. CONCLUSION: Computerized methods for collecting ventilator setting data were relatively straightforward and more-efficient than manual methods. However, the method for automated selection and presentation of observed measured parameters is much more difficult. Based on the findings and analysis presented here, the authors recommend recording ventilator setting data after they have existed for three minutes and measured parameters using a three minute median data selection strategy. Such an algorithm rejected most artifacts, required minimal computational time, had minimal time-delay, and provided clinically acceptable data acquisition. The results presented here are but a starting point in developing automated ventilator data selection strategies.

Adult↗

PubMed2006

The dosimetric effects of tissue heterogeneities in intensity-modulated radiation therapy (IMRT) of the head and neck.

The dosimetric effects of bone and air heterogeneities in head and neck IMRT treatments were quantified. An anthropomorphic RANDO phantom was CT-scanned with 16 thermoluminescent dosimeter (TLD) chips placed in and around the target volume. A standard IMRT plan generated with CORVUS was used to irradiate the phantom five times. On average, measured dose was 5.1% higher than calculated dose. Measurements were higher by 7.1% near the heterogeneities and by 2.6% in tissue. The dose difference between measurement and calculation was outside the 95% measurement confidence interval for six TLDs. Using CORVUS' heterogeneity correction algorithm, the average difference between measured and calculated doses decreased by 1.8% near the heterogeneities and by 0.7% in tissue. Furthermore, dose differences lying outside the 95% confidence interval were eliminated for five of the six TLDs. TLD doses recalculated by Pinnacle3's convolution/superposition algorithm were consistently higher than CORVUS doses, a trend that matched our measured results. These results indicate that the dosimetric effects of air cavities are larger than those of bone heterogeneities, thereby leading to a higher delivered dose compared to CORVUS calculations. More sophisticated algorithms such as convolution/superposition or Monte Carlo should be used for accurate tailoring of IMRT dose in head and neck tumours.

Air↗

PubMed1997

Assessing compliance to antihypertensive medications using computer-based pharmacy records.

Systematic approaches for compliance problem detection and intervention are needed if the benefits of prescribed drug therapy in chronic disease management are to be optimized. As with all measures of compliance, computer algorithms based on refill patterns have advantages and disadvantages. They are unobtrusive and easily determined, but they measure the timeliness of prescription refills, not actual drug-taking. Computer-generated algorithms for assessing compliance based on refill patterns should be used by practitioners with caution, because they are not only markers for potential drug taking compliance problems, but also for discrepancies between the medical chart, pharmacy records and verbal advice given to the patient. Because patients may obtain refills before depleting their supply, compliance rates using this methodology are best determined across several refills. In particular, we urge caution in applying them over time periods of less than 60 days. Longer minimum time periods further decrease the likelihood of "false positives" but limit the number of patients for whom a compliance measure can be computed. For the health professional (eg, the pharmacist) responsible for monitoring drug-taking compliance of patients, the message seems clear: when reviewing computer-generated noncompliance "flags," the first task is to fully explore the possibility of discrepancies in drug records before initiating compliance-related interventions.

Algorithms↗

PubMed1991

Structural interpretation of fluorescence resonance-energy transfer measurements.

Fluorescence resonance-energy transfer (FRET) has been widely used to determine distance information in macromolecular systems. However, little has been written about methods for combining FRET distances into coherent structural models. I argue that the methods used so far are inappropriate. This paper describes an algorithm specifically tailored for finding structures from FRET measurements. This algorithm finds structures which fit the experimentally measured parameter, the efficiency of energy transfer, rather than derived distances. The algorithm was implemented in Mathematica and applied to FRET distances obtained for the contractile protein actin. The approach used is applicable to other experimental techniques which measure distances between a relatively small number of loci.

Energy Transfer↗

PubMed2003

Algorithmic scalability in globally constrained conservative parallel discrete event simulations of asynchronous systems.

We consider parallel simulations for asynchronous systems employing L processing elements that are arranged on a ring. Processors communicate only among the nearest neighbors and advance their local simulated time only if it is guaranteed that this does not violate causality. In simulations with no constraints, in the infinite L limit the utilization scales [Korniss et al., Phys. Rev. Lett. 84, 1351 (2000)]; but, the width of the virtual time horizon diverges (i.e., the measurement phase of the algorithm does not scale). In this work, we introduce a moving Delta-window global constraint, which modifies the algorithm so that the measurement phase scales as well. We present results of systematic studies in which the system size (i.e., L and the volume load per processor) as well as the constraint are varied. The Delta constraint eliminates the extreme fluctuations in the virtual time horizon, provides a bound on its width, and controls the average progress rate. The width of the Delta window can serve as a tuning parameter that, for a given volume load per processor, could be adjusted to optimize the utilization, so as to maximize the efficiency. This result may find numerous applications in modeling the evolution of general spatially extended short-range interacting systems with asynchronous dynamics, including dynamic Monte Carlo studies.

Journal Article↗

PubMed2003

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis.

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.

Algorithms↗

PubMed2004

[Development of automated measurement method for medial temporal lobe on CT images].

Recent research has suggested that the measurement of regional atrophy in the structure of the medial temporal lobe is a promising way to discriminate Alzheimer-type dementia patients from healthy control subjects. The purpose of this study was to develop a technique to measure the medial temporal lobe automatically in axial CT images. Linear measurements of width of the inferior horns of the lateral ventricles, width of the medial temporal lobe, and the interuncal distance were performed. Area measurements of the inferior horns of the lateral ventricles were also performed. In the algorithm for the automatic measurement of the medial temporal lobe, brain contour, and sagittal plane were detected first, and the inferior horns of the lateral ventricles. Our method was applied to ten patients clearly without cerebral hemorrhage or infarct. The rates of accuracy of automated detection were 93% with the linear measurements and 75% with the area of the inferior horns. The rates were improved to 100% with the variable function of the threshold value. We suggest that this automated measurement method is both objective and simple enough to be used in routine clinical applications.

Adolescent↗

PubMed1997

Ploidy determination on histologic sections of breast cancer specimens by image analysis using mathematical correction algorithms.

Several mathematical correction algorithms were developed to solve the problem of the unavoidable measurement of fragmented nuclei when determining DNA ploidy on thin histologic slides. These algorithms were designed for model tissue and until now had not been tested thoroughly on malignant human tissue. We evaluated the use of mathematical correction algorithms applied to measurements on thin histologic sections of breast cancer specimens, with strict control of the section thickness. Fifteen cases of breast carcinoma with known ploidy (5 diploid, 5 tetraploid, and 5 aneuploid breast cancer samples) were included. From each tissue block, we made a single-cell preparation and cut a thin histologic section. We evaluated the thickness of each of these sections according to a recently developed protocol and included only sections with a thickness between 5 and 6 microns. We performed DNA measurements with a custom-made image analyzing system equipped with a 100x oil immersion objective. Histograms of tissue section measurements were corrected according to the algorithms of McCready and Papadimitriou and of Haroske et al. We compared these results with the uncorrected histograms and with the histograms of the single-cell preparations. We also measured the single-cell preparations with a commercially available high-resolution image cytometer. The correlation between both image cytometers used was high (r = 0.99). Histogram correction improved results of tissue section measurements in all of the nondiploid tumors when compared with the uncorrected histograms. There were no significant differences between the correction algorithms used (correlation to the single-cell measurements determined by a linear regression; r = 0.98 for both algorithms). No overcorrection of the histograms occurred. We conclude that reliable DNA tissue section measurements are possible on breast cancer specimens and that such measurements will contribute to our understanding of tumor cell kinetics in small tumor cell populations not detected in single-cell measurements.

Aneuploidy↗

PubMed2003

A spirometry-based algorithm to direct lung function testing in the pulmonary function laboratory.

OBJECTIVE: To design a spirometry-based algorithm to predict pulmonary restrictive impairment and reduce the number of patients undergoing unnecessary lung volume testing. DESIGN: Two prospective studies of 259 consecutive patients and 265 consecutive patients used to derive and validate the algorithm, respectively. SETTING: A pulmonary function laboratory of a tertiary care hospital. PATIENTS: Consecutive adults referred to the laboratory for lung volume measurements and spirometry. MEASUREMENTS: The sensitivity of the algorithm for predicting pulmonary restriction and the cost savings associated with its use. RESULTS: Total lung capacity correlated strongly with FVC (r = 0.66) and showed an inverse correlation with the FEV(1)/FVC ratio (r = - 0.41). According to the algorithm, only patients with an FVC < 85% of predicted and an FEV(1)/FVC ratio >or= 55% required lung volume measurements following spirometry. The algorithm had a high sensitivity for predicting restriction and a high negative predictive value (NPV) for excluding restriction (sensitivity, 96%; NPV, 98%). The diagnostic properties of the algorithm were reproducible in the validation study. Application of the algorithm would eliminate the need for lung volume testing in 48 to 49% of patients referred to the pulmonary function test (PFT) laboratory, reducing costs by 33%. CONCLUSIONS: A spirometry-based algorithm accurately excludes pulmonary restriction and reduces unnecessary lung volume testing in the PFT laboratory almost in half.

Algorithms↗

PubMed2003

The algorithmic complexity of multichannel EEGs is sensitive to changes in behavior.

Symbolic measures of complexity provide a quantitative characterization of the sequential structure of symbol sequences. Promising results from the application of these methods to the analysis of electroencephalographic (EEG) and event-related brain potential (ERP) activity have been reported. Symbolic measures used thus far have two limitations, however. First, because the value of complexity increases with the length of the message, it is difficult to compare signals of different epoch lengths. Second, these symbolic measures do not generalize easily to the multichannel case. We address these issues in studies in which both single and multichannel EEGs were analyzed using measures of signal complexity and algorithmic redundancy, the latter being defined as a sequence-sensitive generalization of Shannon's redundancy. Using a binary partition of EEG activity about the median, redundancy was shown to be insensitive to the size of the data set while being sensitive to changes in the subject's behavioral state (eyes open vs. eyes closed). The covariance complexity, calculated from the singular value spectrum of a multichannel signal, was also found to be sensitive to changes in behavioral state. Statistical separations between the eyes open and eyes closed conditions were found to decrease following removal of the 8- to 12-Hz content in the EEG, but still remained statistically significant. Use of symbolic measures in multivariate signal classification is described.

Algorithms↗

PubMed2001

Spatial normalization of brain images with focal lesions using cost function masking.

In studies of patients with focal brain lesions, it is often useful to coregister an image of the patient's brain to that of another subject or a standard template. We refer to this process as spatial normalization. Spatial normalization can improve the presentation and analysis of lesion location in neuropsychological studies; it can also allow other data, for example from functional imaging, to be compared to data from other patients or normal controls. In functional imaging, the standard procedure for spatial normalization is to use an automated algorithm, which minimizes a measure of difference between image and template, based on image intensity values. These algorithms usually optimize both linear (translations, rotations, zooms, and shears) and nonlinear transforms. In the presence of a focal lesion, automated algorithms attempt to reduce image mismatch between template and image at the site of the lesion. This can lead to significant inappropriate image distortion, especially when nonlinear transforms are used. One solution is to use cost-function masking-masking the areas used in the calculation of image difference-to exclude the area of the lesion, so that the lesion does not bias the transformations. We introduce and evaluate this technique using normalizations of a selection of brains with focal lesions and normal brains with simulated lesions. Our results suggest that cost-function masking is superior to the standard approach to this problem, which is affine-only normalization; we propose that cost-function masking should be used routinely for normalizations of brains with focal lesions.

Adult↗

PubMed2000

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction.

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

Algorithms↗

PubMed2002

Estimation of kinetic parameters without input functions: analysis of three methods for multichannel blind identification.

Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by multichannel blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. Three blind identification algorithms are analyzed here to assess their utility in medical imaging: eigenvector-based algorithm for multichannel blind deconvolution; cross relations; and iterative quadratic maximum-likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. Tissue responses corresponding to a physiological two-compartment model are primarily considered. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that IQML gives more accurate estimates than the other two blind identification methods.

Algorithms↗

PubMed1988

Heart rate correlation, response time and effect of previous exercise using an advanced pacing rate algorithm for temperature-based rate modulation.

A temperature-based algorithm to produce pacing rate that resembles chronotropic response to activity was developed. Measurement criteria for the algorithm included workload dependent rate increases with activity and response time within 60 seconds of exercise onset. To evaluate the algorithm, right ventricular blood temperature was recorded during rest and treadmill exercise in 25 patients with implanted Kelvin 500 pacemakers (Cook Pacemaker). Patients included 16 males and nine females, ages 44-81 (mean 72). Indications for pacing were sinus node disease, atrioventricular block and atrial fibrillation with slow ventricular response. Temperature changes reflected physical activity as well as emotional stress. The algorithm was based on the rate of change (dT/dt), the relative change (delta T) and the baseline history (T) of temperature. At exercise onset, a rapid, brief drop in temperature (dT/dt) typically occurred due to peripheral vasodilation, causing prompt increase in pacing rate. As exercise continued, the increase in metabolic rate caused dT/dt as well as delta T to increase, further increasing pacing rate. After exercise, temperature returned to resting level which correspondingly decreased the pacing rate. Sensitivity of the algorithm to temperature variations, and the upper and lower pacing rate limits were programmable to adapt to individual patient needs. The rates produced by the algorithm mimicked intrinsic rate response for various activity levels and produced a mean response time of 16 seconds from exercise onset. Previous exercise had no significant effect on response time. Correlation between normal chronotropic response and simulated pacing rate from five exercise tests was 0.92. These results show good specificity and refute the statement that blood temperature yields a slow response.

Adult↗

PubMed2001

Using a compact airborne spectrographic imager to monitor phytoplankton biomass in a series of lakes in north Wales.

Three lakes in Snowdonia and two on the island of Anglesey were surveyed using a Compact Airborne Spectrographic Imager (casi). Water samples for chlorophyll measurements and phytoplankton counts were collected at the time of the overflight and the optical characteristics of the lakes recorded by a scanning spectroradiometer. Spectral measurements in the five lakes showed that their optical characteristics were primarily determined by the concentration of phytoplankton in suspension. All the lakes were relatively clear, but the more productive waters contained small amounts of dissolved organic carbon of autochthonous origin. The airborne imaging spectrometer was programmed to measure upwelling radiance in eight narrow bands and linear regressions used to compare the performance of a selected range of chlorophyll retrieval algorithms. The results showed that the most effective algorithms were those based on measurements in the blue and green portions of the spectrum. The best single band algorithm was centred on 440 nm and explained 75% of the measured variation in the concentration of chlorophyll. The best multi-band algorithm was based on measurements taken at 560 and 440 nm and accounted for 94% of the recorded variation. Chlorophyll maps produced by this algorithm showed that the phytoplankton in most of the lakes was homogeneously distributed but surface patches of cyanobacteria were detected at one location.

Algorithms↗

PubMed2005

Quantification of biopolymer filament structure.

The quantitative analysis of a polymer network is important for understanding its role in biological function. We developed a Matlab program to recognize and segment filaments in a 2-D image, and measure and describe the structure. Our algorithm improved the speed of the Lichtenstein Fiberscore segmentation algorithm by using matrix convolutions, compared filament length by the algorithms of Kulpa, Lichtenstein, and Kimura, and measured the number of branchpoints and Euler number. A user interface was added to easily manipulate algorithm parameters, select images, and visualize results. We used the program to compare the DNA biopolymer network of cystic fibrosis (CF) sputum with mucus from patients without respiratory problems. We also examined an image of fibrin. The images were taken with a laser scanning confocal microscope after staining the specimens with Yo-Yo-1. Computation using matrix convolutions reduced the execution time (Pentium III) of a 512 x 512 TIF image from 18 min to 15s. The Kimura length estimation appeared best at describing filament length because it varied least with filament orientation. The image of CF sputum showed increased filament length, more branchpoints, and more negative Euler number compared to the normal sample. These quantitative descriptions of the network can be correlated to material, mechanical, diffusion, or flow properties, physiological processes, or therapy.

Actins↗

PubMed2004

Appearance-based face recognition and light-fields.

Arguably the most important decision to be made when developing an object recognition algorithm is selecting the scene measurements or features on which to base the algorithm. In appearance-based object recognition, the features are chosen to be the pixel intensity values in an image of the object. These pixel intensities correspond directly to the radiance of light emitted from the object along certain rays in space. The set of all such radiance values over all possible rays is known as the plenoptic function or light-field. In this paper, we develop a theory of appearance-based object recognition from light-fields. This theory leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards. All of the pixels, whichever image they come from, are treated equally and used to estimate the (eigen) light-field of the object. The eigen light-field is then used as the set of features on which to base recognition, analogously to how the pixel intensities are used in appearance-based face and object recognition.

Algorithms↗