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Results for “Measuring algorithm”

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PubMed2000

An improved Morris water maze tracking algorithm for psychophysical studies.

We have developed an algorithm to track a rat swimming in a Morris Water Maze. It provides an update on rodent position 15 times per second. The tracking algorithm uses a rotation insensitive tracking template coupled with a limited exhaustive search technique to maintain lock on the moving rat. At the completion of the run, the relative time the rat spent in each quadrant is reported. The tracking algorithm was successfully used to evaluate the time course of memory loss and correlate that to tissue loss in the rat cortex following blunt trauma to the sensory cortex. Results of that study are reported in another paper. Our project budget did not allow for commercially available software to perform the tracking task which typically provide position updates 10 times per second. This paper focuses on the tracking algorithm and support equipment used to measure the rats' progress in the maze.

Algorithms↗

PubMed1997

Interactive automatic fetal head measurements from ultrasound images using multimedia computer technology.

We have developed a tool to automatically detect inner and outer skull boundaries of a fetal head in ultrasound images. These boundaries are used to measure biparietal diameter (BPD) and head circumference (HC). The algorithm is based on active contour models and takes 32 s on a Sun SparcStation 20/71. A high-performance desktop multimedia system called MediaStation 5000 (MS5000) is used as a model for our future ultrasound subsystem. On the MS5000, the optimized implementation of this algorithm takes 248 ms. The difference (between the computer-measured values on MS5000 and the gold standard) for BPD and HC was 1.43% (sigma = 1.00%) and 1.96% (sigma = 1.96%), respectively. According to our data analysis, no significant differences exist in the BPD and HC measurements made on the MS5000 and those measurements made on the Sun SparcStation 20/71. Reduction in the overall execution time from 32 s to 248 ms will help making this algorithm a practical ultrasound tool for sonographers.

Algorithms↗

PubMed2002

A dynamic programming algorithm for haplotype block partitioning.

We develop a dynamic programming algorithm for haplotype block partitioning to minimize the number of representative single nucleotide polymorphisms (SNPs) required to account for most of the common haplotypes in each block. Any measure of haplotype quality can be used in the algorithm and of course the measure should depend on the specific application. The dynamic programming algorithm is applied to analyze the chromosome 21 haplotype data of Patil et al. [Patil, N., Berno, A. J., Hinds, D. A., Barrett, W. A., Doshi, J. M., Hacker, C. R., Kautzer, C. R., Lee, D. H., Marjoribanks, C., McDonough, D. P., et al. (2001) Science 294, 1719-1723], who searched for blocks of limited haplotype diversity. Using the same criteria as in Patil et al., we identify a total of 3,582 representative SNPs and 2,575 blocks that are 21.5% and 37.7% smaller, respectively, than those identified using a greedy algorithm of Patil et al. We also apply the dynamic programming algorithm to the same data set based on haplotype diversity. A total of 3,982 representative SNPs and 1,884 blocks are identified to account for 95% of the haplotype diversity in each block.

Algorithms↗

PubMed1998

Extraction of the photon spectra from measured beam parameters.

Knowledge of the photon spectrum of a radiotherapy beam is often needed for three-dimensional (3-D) dose calculations using Monte Carlo methods and/or algorithms employing energy deposition kernels. Direct measurement of the x-ray energy fluence spectrum is not feasible for the high-energy photon beams used clinically. In this paper, the spectrum is extracted from basic beam data that are readily obtained for a clinical beam. We describe the photon spectrum using just two parameters. One parameter, which determines the high-energy part of the spectrum, is obtained using the measured dose in the buildup region for a small field, where electron contamination of the beam can be neglected. The other parameter is extracted from the photon beam attenuation in water. The results compare favorably to spectra generated from Monte Carlo simulations.

Algorithms↗

PubMed1996

Reproducibility and automatic measurement of QT dispersion.

This study investigated interobserver (two observers) and intrasubject (two measurements) reproducibility of QT dispersion from abnormal electrocardiograms in patients with previous myocardial infarction, and compared a user-interactive with an automatic measurement system. Standard 12-lead electrocardiograms, recorded at 25 mm.s-1, were randomly chosen from 70 patients following myocardial infarction. These were scanned into a personal computer, and specially designed software skeletonized and joined each image. The images were then available for user-interactive (mouse and computer screen), or automatic measurements using a specially designed algorithm. For all methods reproducibility of the RR interval was excellent (mean absolute errors 3-4 ms, relative errors 0.3-0.5%). Reproducibility of the mean QT interval was good; intrasubject error was 6 ms (relative error 1.4%), interobserver error was 7 ms (1.8%), and observers' vs automatic measurement errors were 10 and 11 ms (2.5, 2.8%). However QTc dispersion measurements had large errors for all methods; intrasubject error was 12 ms (17.3%), interobserver error was 15 ms (22.1%), and observers' vs automatic measurement were errors 30 and 28 ms (35.4, 31.9%). QT dispersion measurements rely on the most difficult to measure QT intervals, resulting in a problem of reproducibility. Any automatic system must not only recognize common T wave morphologies, but also these more difficult T waves, if it is to be useful for measuring QT dispersion. The poor reproducibility of QT dispersion limits its role as a useful clinical tool, particularly as a predictor of events.

Diagnosis, Computer-Assisted↗

PubMed2003

An information theoretic approach for analyzing temporal patterns of gene expression.

MOTIVATION: Arrays allow measurements of the expression levels of thousands of mRNAs to be made simultaneously. The resulting data sets are information rich but require extensive mining to enhance their usefulness. Information theoretic methods are capable of assessing similarities and dissimilarities between data distributions and may be suited to the analysis of gene expression experiments. The purpose of this study was to investigate information theoretic data mining approaches to discover temporal patterns of gene expression from array-derived gene expression data. RESULTS: The Kullback-Leibler divergence, an information-theoretic distance that measures the relative dissimilarity between two data distribution profiles, was used in conjunction with an unsupervised self-organizing map algorithm. Two published, array-derived gene expression data sets were analyzed. The patterns obtained with the KL clustering method were found to be superior to those obtained with the hierarchical clustering algorithm using the Pearson correlation distance measure. The biological significance of the results was also examined. AVAILABILITY: Software code is available by request from the authors. All programs were written in ANSI C and Matlab (Mathworks Inc., Natick, MA).

Algorithms↗

PubMedDate not supplied

Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images.

An algorithm and set of procedures for measuring volumes of cerebrospinal fluid (CSF), white matter, and gray matter from transaxial magnetic resonance images (MRI) of the brain are described. The algorithm is a variant of the fuzzy c-means clustering method for texture identification. This technique is used mainly to solve the problem of volume averaging of tissue compartments, but also has other advantages. It is fast, accurate, and relatively operator independent. Furthermore, it does not depend on statistical assumptions such as data normality, nor does it require any a priori heuristics. The procedure was tested successfully on imaged phantoms of known volume composition and compared with results achieved using a standard morphometric measurement approach. The procedure was also applied to brain MRIs of three clinically normal children and three age-matched children with hydrocephalus using both proton density and T2-weighted images. The algorithm was able to detect the expected increased amounts of CSF and decreased amounts of white matter characteristic of the hydrocephalic brain.

Algorithms↗

PubMed1997

Length and base composition of PCR-amplified nucleic acids using mass measurements from electrospray ionization mass spectrometry.

A generally applicable algorithm has been developed to allow base composition of polymerase chain reaction (PCR) products to be determined from mass spectrometrically measured molecular weights and the complementary nature of DNA. Mass measurements of arbitrary precision for single-stranded DNA species are compatible with an increasingly large number of possible base compositions as molecular weight increases. For example, the number of base compositions that are consistent with a molecular weight of 35,000 is approximately 6000, based on a mass measurement precision of 0.01%. However, given the low misincorporation rate of standard DNA polymerases, mass measurement of both of the complementary single strands produced in the PCR reduces the number of possibilities to less than 100 at 0.01% mass precision, and base composition is uniquely defined at 0.001% mass precision. Taking into account the low misincorporation rate of standard DNA polymerases and the fact that the final PCR product also contains primers of known sequence (generally 15-20-mer in size, which flank the targeted region), this reduces the number of possible base combinations to only approximately 3 at MW = 35,000. In addition, the number of base pairs (i.e., length of the DNA molecule) is uniquely defined. We show that the use of modified bases in PCR or post-PCR modification chemistry allows unique solutions for the base composition of the PCR product with only modest mass measurement precision.

Algorithms↗

PubMed2005

A linkable identity privacy algorithm for HealthGrid.

The issues of confidentiality and privacy have become increasingly important as Grid technology is being adopted in public sectors such as healthcare. This paper discusses the importance of protecting the confidentiality and privacy of patient health/medical records, and the challenges exhibited in enforcing this protection in a Grid environment. It proposes a novel algorithm to allow traceable/linkable identity privacy in dealing with de-identified medical records. Using the algorithm, de-identified health records associated to the same patient but generated by different healthcare providers are given different pseudonyms. However, these pseudonymised records of the same patient can still be linked by a trusted entity such as the NHS trust or HealthGrid manager. The paper has also recommended a security architecture that integrates the proposed algorithm with other data security measures needed to achieve the desired security and privacy in the HealthGrid context.

Algorithms↗

PubMed2000

A quality network model for the daily care of multiple sclerosis.

The urgent need to optimise treatment strategies for patients with Multiple Sclerosis (MS) was recognised by the participants at the 1998 European Charcot Foundation (ECF) symposium in Nice. The 'Nice Declaration' led to the formation of a Task Force Essentials Group charged with developing measures of the quality of MS care in Europe. Algorithms for nine critical domains (disability, spasticity, ataxia, pain, cognition, mood, fatigue, bladder function and sexual activity) and 'educated guesses' have been developed to measure interventions and outcomes which reflect the quality of clinical decision-making processes. A generic model called a 'quality network', consisting of a group of clinics connected to a central server, has been successfully applied to the care of diabetes across Europe. This model will now be developed and applied to MS management, to provide clinicians with longitudinal epidemiological data and, to evolve treatment algorithms and further quality measures. The ECF will next validate the system in a 1-year pilot study using a net of 10 clinics. Finally, an extended European network working in a learning environment will continuously assess, update and improve the quality of care of MS patients. Multiple Sclerosis (2000) 6 231 - 236

Algorithms↗

PubMed2005

A self-mixing laser-diode interferometer for measuring basilar membrane vibrations without opening the cochlea.

A laser-diode forms the basis of a displacement sensitive homodyne interferometer suitable for measurements from poorly reflective surfaces. The compact and cost-effective interferometer utilizes the self-mixing effect when laser light reflected from a moving target re-enters the laser cavity and causes phase dependent changes of the lasing intensity. A piezo positioner was used to displace the interferometer with known frequency and amplitude as a basis for real-time calibration of the interferometer's sensitivity. The signal-processing algorithm is described that allows measurements in presence of high amplitude noise leading to variation of the interferometer's operating point. Measurements of sound-induced basilar membrane displacements were made in the intact cochleae of rodents by focusing the laser beam of the interferometer through the transparent round window membrane. The interferometer provides a viable means for making subnanometre mechanical measurements from structures in the inner ears of small mammals, where opening of the cochlea is not practicable.

Algorithms↗

PubMed1996

Multiple source localization using genetic algorithms.

We present a new procedure for localizing simultaneously active multiple brain sources that overlap in both space and time on EEG recordings. The source localization technique was based on a spatio-temporal model and a genetic algorithm search routine. The method was successfully applied to the localization of two dipole sources from several sets of simulated potentials with various signal-to-noise ratios (SNR). The different SNR values resembled evoked responses and epileptic spikes as commonly seen in the laboratory. Results of the simulation studies yielded localization accuracy ranging from 0.01 to 0.07 cm with an SNR of 10; from 0.02 to 0.26 cm with an SNR of 5; and from 0.06 to 0.73 cm when the SNR was equal to 2. Additionally, two sets of simulations were based on the dipole arrangements and time activities of data obtained during electrical stimulation of the median nerve in human subjects. These studies yielded localization accuracy within 0.1 cm. We also studied the localization accuracy of the algorithm using a physical model incorporating potential measurements of two current dipoles embedded in a sphere. In this situation the algorithm was successful in localizing the two simultaneously active sources to within 0.07-0.15 cm.

Algorithms↗

PubMed2005

Finding local community structure in networks.

Although the inference of global community structure in networks has recently become a topic of great interest in the physics community, all such algorithms require that the graph be completely known. Here, we define both a measure of local community structure and an algorithm that infers the hierarchy of communities that enclose a given vertex by exploring the graph one vertex at a time. This algorithm runs in time O(k2d) for general graphs when d is the mean degree and k is the number of vertices to be explored. For graphs where exploring a new vertex is time consuming, the running time is linear, O(k). We show that on computer-generated graphs the average behavior of this technique approximates that of algorithms that require global knowledge. As an application, we use this algorithm to extract meaningful local clustering information in the large recommender network of an online retailer.

Journal Article↗

PubMed1997

A novel volumetric feature extraction technique with applications to MR images.

A semiautomated feature extraction algorithm is presented for the extraction and measurement of the hippocampus from volumetric magnetic resonance imaging (MRI) head scans. This algorithm makes use of elements of both deformable model and region growing techniques and allows incorporation of a priori operator knowledge of hippocampal location and shape. Experimental results indicate that the algorithm is able to estimate hippocampal volume and asymmetry with an accuracy which approaches that of laborious manual outlining techniques.

Algorithms↗

PubMed2003

ROC analysis for assessment of lesion detection performance in 3D PET: influence of reconstruction algorithms.

Image quality in positron emission tomography (PET) can be assessed with physical parameters, as spatial resolution and signal-to-noise ratio, or using psychophysical approaches, which include the observer performance and the considered task (ROC analysis). For PET in oncology, such a task is the detection of hot lesions. The aim of the present study was to assess the lesion detection performance due to adequate modeling of the scanner and the measurement process in the image reconstruction process. We compared the standard OSEM software of the manufacturer with a sophisticated fully 3D iterative reconstruction technique (USC MAP). A rectangular phantom with 6 oblique line sources in a homogeneous background (2.6 kBq/ml 18F) was imaged dynamically with an ECAT EXACT HR+ scanner in 3D mode. Reconstructed activity contrasts varied between 15 and 0, as the line sources were filled with 11C (3.2 MBq/ml). Measured attenuation and standard randoms, dead time, and scatter corrections of the manufacturer were employed. For the ROC analysis, a software tool presented a cut-out of the phantom (15 x 15 pixels) to two observers. These cut-outs were rated (5 classes) and the area Az under the ROC curve was determined as a measure of detection performance. The improvement for Az with USC MAP compared to the OSEM reconstructions ranged between 0.02 and 0.23 for signal-to-noise ratios of the background between 2.8 and 3.1 and lesion contrast between 2.1 and 4.2. This study demonstrates that adequate modeling of the measurement process in the reconstruction algorithm improves the detection of small hot lesions markedly.

Algorithms↗

PubMed1984

A comparison of the artificial pancreas (glucose controlled insulin infusion system) and a manual technique for assessing insulin sensitivity during euglycaemic clamping.

Two main methods are available for assessing insulin sensitivity with the hyperinsulinaemic euglycaemic clamp technique: one employs a glucose-controlled insulin infusion system (the Biostator) with automatic feedback control; the second depends on frequent glucose measurement and the use of an algorithm and a pocket calculator ('manual') to determine the glucose infusion rate. The amount of glucose infused is a measure of insulin sensitivity. The efficiency of the two methods was compared in nine normal subjects (seven lean, two obese). After an overnight fast subjects were infused with insulin at 50 mU X kg-1 X h-1 for 2 h; this rate was doubled during the first 10 min for the manual technique. Blood glucose averaged 4.7 +/- 0.1 and 4.8 +/- 0.1 mmol/l from 0 to 120 min for Biostator and manual techniques and did not deviate significantly from the desired level. Variability of the clamp was also similar over the same period (coefficient of variation 5.1 +/- 0.6% and 6.4 +/- 0.7%, Biostator and manual). Glucose infused to maintain steady state from 60 to 120 min was higher, however, with the manual than the Biostator method (5.7 +/- 0.6 versus 4.4 +/- 0.6 mg X kg-1 X min-1, p less than 0.01) even when the loading dose was omitted, although the two methods correlated closely (p less than 0.05). Glucose infusion rate varied more from minute to minute with the Biostator (coefficient of variation 28.8 +/- 3% versus 12.2 +/- 2.1%). Steady-state serum insulin levels (30-120 min) were the same during both methods.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed1998

Quantification of emotion by nonlinear analysis of the chaotic dynamics of electroencephalograms during perception of 1/f music.

The goal of this study is to quantify and determine the way in which the emotional response to music is reflected in the electrical activities of the brain. When the power spectrum of sequences of musical notes is inversely proportional to the frequency on a log-log plot, we call it 1/f music. According to previous research, most listeners agree that 1/f music is much more pleasing than white (1/f0) or brown (1/f2) music. Based on these studies, we used nonlinear methods to investigate the chaotic dynamics of electroencephalograms (EEGs) elicited by computer-generated 1/f music, white music, and brown music. In this analysis, we used the correlation dimension and the largest Lyapunov exponent as measures of complexity and chaos. We developed a new method that is strikingly faster and more accurate than other algorithms for calculating the nonlinear invariant measures from limited noisy data. At the right temporal lobe, 1/f music elicited lower values of both the correlation dimension and the largest Lyapunov exponent than white or brown music. We observed that brains which feel more pleased show decreased chaotic electrophysiological behavior. By observing that the nonlinear invariant measures for the 1/f distribution of the rhythm with the melody kept constant are lower than those for the 1/f distribution of melody with the rhythm kept constant, we could conclude that the rhythm variations contribute much more to a pleasing response to music than the melody variations do. These results support the assumption that chaos plays an important role in brain function, especially emotion.

Auditory Perception↗

PubMed1991

Classification of postoperative cardiac patients: comparative evaluation of four algorithms.

Four classification algorithms based on Bayes' rule for minimum error are compared by evaluating their ability to recognize high- and normal-risk cardio-surgical patients. These algorithms differ in the modelling of the probability density function (pdf) for each class and include: (a) two parametric algorithms based on the assumption of normal pdf; (b) two non-parametric algorithms using Parzen multidimensional approximation of pdf with normal kernels. In each case, classes with both equal and different covariance matrices were considered. A set of 200 patients in the 6 h immediately following cardiac surgery has been used to test the performance of the algorithms. For each patient the three measured variables most effective in representing the difference between the two classes were considered. We found that the two algorithms which explicitly incorporate the information on the different sample covariance between the physiological variables existing in the two classes generally provide better recognition of high- and normal-risk patients. Of these two algorithms the parametric one appears extremely attractive for practical applications, since it exhibits slightly better performance in spite of its great simplicity.

Algorithms↗