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PubMed1984

The inertial and geometrical properties of helmets.

The center of gravity (CG) and the principal mass moments of inertia about the CG of Army aviator, American football, and bicycle helmets were experimentally determined by a variation of the classic differential weighing and torsional pendulum techniques. In the course of these experiments, an innovative method for three-dimensional (3D) digitization was found. An electronic caliper, which measured length, was used with a computer algorithm to achieve 3D digitization. The results of the above measurements show that the weight of the helmet and the distances from the CG to the orthogonal coordinate axes intercepts with the outer shell surface were highly correlated with its principal mass moments of inertia. A set of regression equations was derived on theoretical considerations and served to unify the experimentally obtained data. Our results indicate that the principal mass moments of inertia of helmets vary linearly with its mass but nonlinearly with size and shape. For a helmet, given its weight and certain geometrical distances, the regression equations estimate the principal mass moments of inertia to within 5% of its experimentally-determined values. For the helmets studied in this series, a modified linear-regression relationship between the principal mass moments of inertia and its mass was found. This result is reasonable because the mass distribution of the current generation of helmets are set primarily by the head size and secondarily by helmet size, shape, and materials.

Aviation↗

PubMed2006

Quantitative myocardial infarction on delayed enhancement MRI. Part II: Clinical application of an automated feature analysis and combined thresholding infarct sizing algorithm.

PURPOSE: To compare global and regional myocardial infarction (MI) measurements on clinical gadolinium-enhanced magnetic resonance (MR) images using human manual contouring and a computer algorithm previously validated by histopathology, and to study the degree to which visual assessment and human contouring of infarct extent agreed with the computer algorithm. MATERIALS AND METHODS: Infarct size in 20 patients was measured by human manual contouring and with an automated feature analysis and combined thresholding (FACT) computer algorithm. Short-axis slices were divided into myocardial sectors for regional analysis. Extent of infarction was also graded visually by consensus of expert readers and compared to human and computer contouring. RESULTS: Despite good correlations (R = 0.93-0.95) between human contouring and the FACT algorithm, human contouring overestimated infarct size by 3.8% of the left ventricle (23.8% of the MI) area (P < 0.001). Human contouring also overestimated the circumferential extent, transmural extent, and extent of infarction within a sector by 7.1%, 18.2%, and 27.9%, respectively (all P < 0.001). Both consensus reading and human contouring overestimated infarct grades compared with the FACT algorithm (P = 0.002 and P < 0.001). CONCLUSION: Clinically relevant overestimation of MI can occur in visual interpretation and in human manual contouring, particularly with respect to extent of infarction on a regional basis.

Adult↗

PubMed1998

Spectral analysis methods for neurological signals.

This paper reviews some novel spectral analysis techniques that are useful for neurological signals in general and EEG signals in particular. First, some drawbacks and limitations of the commonly used Fast Fourier transforms (FFTs) are presented, and then alternative algorithms are outlined. An auto-regressive (AR) modeling based spectral estimation procedure is presented to overcome the problems of lower resolution and 'leakage' effects inherent in the FFT algorithm. For signals which are transient in nature or rapidly time-varying, two alternative algorithms are presented. The first is an adaptive AR parameter estimation algorithm and the second is a wavelet based time-frequency representation algorithm. Finally, a Spectral Distance measure and the Itakura distance measure are presented to quantify the differences between the spectra of two signals in a succinct manner. The application and performance of all the algorithms is illustrated using electroencephalograms (EEGs) recorded in animals during hypoxic asphyxic injury to brain.

Algorithms↗

PubMed1988

Three-dimensional reconstruction in electrical impedance tomography.

We have developed a three-dimensional, computer-simulated, electrical impedance tomographic imaging system using the four-electrode measurement technique. The reconstruction process finds the numerical solution of Laplace's equation by using the finite element method and the Newton-Raphson algorithm. A new diagonal electrodes measurement method provides lower error than the usual neighbouring electrodes measurement method. For a three-layer, 4 x 4 model, the number of iterations increased from 3 to 16 as the number of randomly placed, high-resistivity voxels increased from 3 to 18.

Electric Conductivity↗

PubMed1993

Genetic algorithms: principles of natural selection applied to computation.

A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function of determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.

Algorithms↗

PubMed1989

Nonparametric comparison of entire ROC curves for computerized ECG left ventricular hypertrophy algorithms using data from the Framingham Heart Study.

A computer program may be capable of several different statements for left ventricular hypertrophy (eg, possible LVH, probable LVH, consistent with LVH), but such statements resulting from discretized levels of sensitivity/specificity would represent only isolated points on a receiver-operating characteristic (ROC) curve, which is a plot of all levels of sensitivity versus specificity. Even if two algorithms use the same discrete scales, their performances may not readily be compared. The authors present a comparison methodology for ROC curves using ROC area as a nonparametric measure of the ability of the algorithm to separate the two populations; the ROC area ranges from 0.5 (no ability) to 1.0 (perfect separation) and is unbiased if the normal versus abnormal populations have no common values for the measurement. The methodology compares the performance of ECG algorithms on the same population of cases by testing for significant differences of ROC areas and incorporating correlation of the algorithms in a nonparametric way. To illustrate this methodology, they use ECG and echocardiographic data from the Framingham Heart Study.

Algorithms↗

PubMed2003

Brachial artery: measurement of flow-mediated dilatation with cross-sectional US--technical validation.

Ultrasonographic examination of flow phantoms and the brachial artery of a healthy volunteer undergoing reactive hyperemia was performed. Images were analyzed with a user-guided automated boundary detection (UGABD) algorithm to extract boundaries and measure cross-sectional area. UGABD correctly detected pulsatile vasomotion and measured area within 5% of the true value. A comparison of UGABD versus manual tracing yielded linear correlation of 0.81-0.91. Peak vasodilatation measured in response to reactive hyperemia was 150 times greater in pixel count than that measured with longitudinal imaging. Cross-sectional imaging is more sensitive than longitudinal imaging for measuring flow-mediated dilatation of the brachial artery.

Algorithms↗

PubMed1996

Unwrapping Cochlear implants by spiral CT.

Multielectrode, intracochlear implants were designed for individuals with profound sensorineural hearing loss who derive little or no benefit form acoustic hearing aids. Determination of each electrode's position in a patient's inner ear may improve speech processor programming to maximize speech recognition. In this paper, an approach is described to use as input a volumetric spiral computed tomography (CT) image of the Nucleus electrode array (Cochlear Pty. Ltd, Lane Cove, NSW, Australia) to unwrap it, and to measure its implanted length given starting and end points. Representative curvilinear structures were digitally synthesized in image volumes of isotropic 0.1-mm voxels. The electrode array was spirally CT-scanned in vitro and in vivo, and reconstructed on an isotropic grid in 0.1-mm steps. Two algorithms were constructed to track and measure these curvilinear structures. The first algorithm is Karhunen-Loeve (K-L)-transform based, in which the K-L transform is locally applied at a current main axis position to determine the eigenvectors of the main axis voxels, the next main axis position is estimated from the current position along the principal eigendirection, adjusted to the mass center of the orthogonal cross section passing through the estimated position, and then scaled to have a prespecified step. The second algorithm is similar to the first one but avoids use of the K-L transform. In the second algorithm, the next position is directly estimated along the local direction and then processed with the same correction and scaling operations. With user-specified starting and end points as well as a local direction at the starting point, a curvilinear structure can be automatically tracked using either of the algorithms. The first algorithm is more robust, while the second one is more efficient. In the numerical and in vitro studies, the lengths of the curvilinear structures were accurately measured. Given local directions determined in the tracking process, an electrode array image can be unwrapped into a linear array with the central electrode axis as the abscissa. The unwrapping approach allows longitudinally and cross-sectionally accurate measurement and better visualization of cochlear implant images. With preimplantation knowledge of length, width, and center electrode distance, the position of individual electrodes can be estimated after unwrapping.

Algorithms↗

PubMed1994

Maximum key-profile correlation (MKC) as a measure of tonal structure in music.

Tonal structure is musical organization on the basis of pitch, in which pitches vary in importance and rate of occurrence according to their relationship to a tonal center. Experiment 1 evaluated the maximum key-profile correlation (MKC), a product of Krumhansl and Schmuckler's key-finding algorithm (Krumhansl, 1990), as a measure of tonal structure. The MKC is the maximum correlation coefficient between the pitch class distribution in a musical sample and key profiles, which indicate the stability of pitches with respect to particular tonal centers. The MKC values of melodies correlated strongly with listeners' ratings of tonal structure. To measure the influence of the temporal order of pitches on perceived tonal structure, three measures (fifth span, semitone span, and pitch contour) taken from previous studies of melody perception were also correlated with tonal structure ratings. None of the temporal measures correlated as strongly or as consistently with tonal structure ratings as did the MKC, and nor did combining them with the MKC improve prediction of tonal structure ratings. In Experiment 2, the MKC did not correlate with recognition memory of melodies. However, melodies with very low MKC values were recognized less accurately than melodies with very high MKC values. Although it does not incorporate temporal, rhythmic, or harmonic factors that may influence perceived tonal structure, the MKC can be interpreted as a measure of tonal structure, at least for brief melodies.

Algorithms↗

PubMed2003

Velocity estimation in ultrasound images: a block matching approach.

In this paper, we focus on velocity estimation in ultrasound images sequences. Ultrasound images present many difficulties in image processing because of the typically high level of noise found in them. Recently, Cohen and Dinstein have derived a new similarity measure, according to a simplified image formation model of ultrasound images, optimal in the maximum likelihood sense. This similarity measure is better for ultrasound images than others such as the sum-of-square differences or normalised cross-correlation because it takes into account the fact that the noise in an ultrasound image is multiplicative Rayleigh noise, and that displayed ultrasound images are log-compressed. In this work we investigate the use of this similarity measure in a block matching method. The underlying framework of the method is Singh's algorithm. New improvements are made both on the similarity measure and the Singh algorithm to provide better velocity estimates. A global optimisation scheme for algorithm parameter estimation is also proposed. We show that this optimisation makes an improvement of approximately 35% in comparison to the result obtained with the worst parameter set. Results on clinically acquired cardiac and breast ultrasound sequences, demonstrate the robustness of the method.

Algorithms↗

PubMed2001

Structure determination at the atomic level from dynamical electron diffraction data under systematic row conditions.

We discuss a method to obtain structural information on crystals at the atomic level in high-resolution transmission electron microscopy from dynamical diffraction data under systematic row conditions. Working at a fixed incident energy and within an N-beam approximation, data is required at a well defined set of N incident beam orientations to determine the scattering matrix, one orientation for each column in the matrix. At each orientation the corresponding column of the scattering-matrix is obtained by Fourier transformation of the exit surface wave function. Thus, in addition to each exit surface image, we must recover the phase of the wave function for that orientation in the image plane. We show that retrieval of the phase using algorithms based on conservation of flux, which assume continuity of the phase, can yield incorrect solutions for the phase. This is because singularities can occur in the phase of the wave field at points where the intensity is zero, which can lead to edge dislocations in the phase. We demonstrate, using a model example, how these edge dislocations arise. We will show that phase retrieval from a through focal series of measurements or using the Gerchberg-Saxton algorithm (starting from measurements of an image and the corresponding diffraction pattern), correctly retrieves the phase and hence the exit surface wave function for all the orientations required to obtain the scattering-matrix. The dynamical (multiple) scattering can then be inverted to uniquely obtain the projected potential.

Journal Article↗

PubMed2006

Discrete cosine transform-based shift estimation for fringe pattern profilometry using a generalized analysis model.

What is believed to be a new analysis algorithm to carry out profile measurement with low computational complexity and less noise sensitivity is presented. First, a discrete cosine transform (DCT)-based representation method is introduced to express the height distribution of a 3D surface. Then a novel shift estimation algorithm, called the DCT-based shift estimation (DCT-SE), is presented to reconstruct 3D object surfaces by using the proposed expression and the generalized analysis model. The advantage of DCT-SE is that without loss of measurement precision it provides lower computational complexity to implement 3D reconstruction from nonlinearly distorted fringe patterns and, at the same time, survives the random noise. Simulations and experiments show that the proposed DCT-SE is a fast, accurate, and efficient reconstruction algorithm for digital projection- based fringe pattern profilometry techniques.

Journal Article↗

PubMed2002

[Integration of the Aasalid test in an online measurement system for evaluating cerebral autoregulation].

An important question during the intensive care of patients with subarachnoid hemorrhage and craniocerebral trauma is the evaluation of the cerebral autoregulation (CA). The so called Aaslid-Test is a standard method which allows the cerebral autoregulation to be classified. As the results under repetitive conditions show a high variation, it has not been yet possible to draw statistically proved conclusions concerning the performance of the CA. To improve the test results the measuring conditions are discussed and systematized. The algorithms of the Aaslid-Test have been implemented to an online measuring system. The error bandwidth has been estimated. To avoid systematically occurring errors an enhanced measuring protocol is provided.

Algorithms↗

PubMed2005

An automatic beat detection algorithm for pressure signals.

Beat detection algorithms have many clinical applications including pulse oximetry, cardiac arrhythmia detection, and cardiac output monitoring. Most of these algorithms have been developed by medical device companies and are proprietary. Thus, researchers who wish to investigate pulse contour analysis must rely on manual annotations or develop their own algorithms. We designed an automatic detection algorithm for pressure signals that locates the first peak following each heart beat. This is called the percussion peak in intracranial pressure (ICP) signals and the systolic peak in arterial blood pressure (ABP) and pulse oximetry (SpO2) signals. The algorithm incorporates a filter bank with variable cutoff frequencies, spectral estimates of the heart rate, rank-order nonlinear filters, and decision logic. We prospectively measured the performance of the algorithm compared to expert annotations of ICP, ABP, and SpO2 signals acquired from pediatric intensive care unit patients. The algorithm achieved a sensitivity of 99.36% and positive predictivity of 98.43% on a dataset consisting of 42,539 beats.

Algorithms↗

PubMed2005

Interpretation of butyltin mass spectra using isotope pattern reconstruction for the accurate measurement of isotope ratios from molecular clusters.

The fragmentation patterns of butyltin compounds (mono-, di-, and tributyltin) in an electron impact ion source were studied using an isotope pattern reconstruction algorithm with emphasis on isotope ratio measurements from molecular clusters. For this purpose, standards of natural tin isotope abundance and a (119)Sn-enriched mixture of the three compounds were both ethylated and propylated using sodium tetraalkylborates. The corresponding mass spectra of the various tetraalkyltin compounds prepared were obtained by GC/MS after their extraction with hexane. The results showed that pure interference-free molecular clusters were obtained only for certain R(3)Sn(+) ions where no isobaric overlap with R(2)SnH(+) ions occurred (e.g. BuEt(2)Sn(+) overlaps with Bu(2)SnH(+)). These ions are ideal candidates for accurate Sn isotope ratio measurements, while isotope pattern perturbing interferences are observed for other molecular fragments down to Sn(.)(+). Isotope pattern reconstruction algorithm thus can be used as an analytical tool to ensure the absence of molecular interferences--a requirement for accurate isotope ratio measurements from molecular clusters. The relevance of these studies for the determination of butyltin compounds in environmental samples by isotope dilution GC/MS is also discussed.

Environmental Monitoring↗

PubMed1996

A pencil beam algorithm for proton dose calculations.

The sharp lateral penumbra and the rapid fall-off of dose at the end of range of a proton beam are among the major advantages of proton radiation therapy. These beam characteristics depend on the position and characteristics of upstream beam-modifying devices such as apertures and compensating boluses. The extent of separation, if any, between these beam-modifying devices and the patient is particularly critical in this respect. We have developed a pencil beam algorithm for proton dose calculations which takes accurate account of the effects of materials upstream of the patient and of the air gap between them and the patient. The model includes a new approach to picking the locations of the pencil beams so as to more accurately model the penumbra and to more effectively account for the multiple-scattering effects of the media around the point of interest. We also present a faster broad-beam version of the algorithm which gives a reasonably accurate penumbra. Predictions of the algorithm and results from experiments performed in a large-field proton beam are presented. In general the algorithm agrees well with the measurements.

Algorithms↗

PubMed2004

LS Bound based gene selection for DNA microarray data.

MOTIVATION: One problem with discriminant analysis of DNA microarray data is that each sample is represented by quite a large number of genes, and many of them are irrelevant, insignificant or redundant to the discriminant problem at hand. Methods for selecting important genes are, therefore, of much significance in microarray data analysis. In the present study, a new criterion, called LS Bound measure, is proposed to address the gene selection problem. The LS Bound measure is derived from leave-one-out procedure of LS-SVMs (least squares support vector machines), and as the upper bound for leave-one-out classification results it reflects to some extent the generalization performance of gene subsets. RESULTS: We applied this LS Bound measure for gene selection on two benchmark microarray datasets: colon cancer and leukemia. We also compared the LS Bound measure with other evaluation criteria, including the well-known Fisher's ratio and Mahalanobis class separability measure, and other published gene selection algorithms, including Weighting factor and SVM Recursive Feature Elimination. The strength of the LS Bound measure is that it provides gene subsets leading to more accurate classification results than the filter method while its computational complexity is at the level of the filter method. AVAILABILITY: A companion website can be accessed at http://www.ntu.edu.sg/home5/pg02776030/lsbound/. The website contains: (1) the source code of the gene selection algorithm; (2) the complete set of tables and figures regarding the experimental study; (3) proof of the inequality (9). CONTACT: ekzmao@ntu.edu.sg.

Biomarkers, Tumor↗

PubMed2000

Reconstructing bifurcation diagrams of dynamical systems using measured time series.

We present an algorithm for reconstructing the bifurcation structure of a dynamical system from time series. The method consists in finding a parameterized predictor function whose bifurcation structure is similar to that of the given system. Nonlinear autoregressive (NAR) models with polynomial terms are employed as predictor functions. The appropriate terms in the NAR models are obtained using a fast orthogonal search scheme. This scheme eliminates the problem of multiparameter optimization and makes the approach robust to noise. The algorithm is applied to the reconstruction of the bifurcation diagram (BD) of a neuron model from the simulated membrane potential waveforms. The reconstructed BD captures the different behaviors of the given system. Moreover, the algorithm also works well even for a limited number of time series.

Algorithms↗