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At least 289 records · Page 16Linked to original sources

PubMed1989

Correlation artifacts in speed of sound estimation in scattering media.

A recently described method for speed of sound estimation in tissues in pulse-echo mode involves reception of echoes generated by an ultrasonic pulse by means of a linearly tracking transducer. When the peaks of echo amplitudes are used as markers of arrival time, stairstep-like artifacts appear in the echo arrival time vs. transducer position plots. We postulate that these artifacts are a consequence of the speckle phenomenon commonly encountered in ultrasonic imaging. To test this hypothesis, we report computer simulations and water tank experiments which demonstrate similarities between the behavior of the stairsteps and the properties of ultrasonic speckle. Additionally, equations describing the precision of the speed of sound estimation in terms of the second order statistical properties of the stairstep artifact are derived.

Computer Simulation↗

PubMed1992

Processing images of helical structures: a new twist.

Helical macromolecular assemblies are particularly difficult to study by X-ray diffraction but are quite well suited to analysis by electron microscopy. Most of our information about helical macromolecular assemblies has come from the electron microscope but has been limited to about 25 A resolution. With the use of low-dose electron cryomicroscopy, one can obtain structural data to near atomic resolution on two-dimensional crystals, but the problem is to extract the information from the noise. In this paper we present methods to extract signal from low-dose electron cryomicrographs of helically symmetric structures. We apply these methods to extract 10 A data from the bacterial flagellar filament.

Algorithms↗

PubMedDate not supplied

Morphometric analysis of sonographic images by spatial geometric modeling.

A methodology able to derive spatial geometric models from input sequences of sonographic slices is proposed. The developed modeling procedure can be utilized to perform computer-assisted anatomic 3D analysis both on all echo space and selected subregions. The modeling procedure is mainly composed of three sequential phases: a) automatic acquisition and preprocessing of time sequences of 2D echotomograms; b) 3D reconstruction of images and computing of discrete distance maps of selected echoes according to predefined projective laws; and c) generation of a spatial geometric model of the examined object starting from the previously computed maps.

Algorithms↗

PubMed2002

The effects of parallax on geometric morphometric data.

This study questions the use of parallactic images in the field of geometric morphometrics. Landmark data from both standard and distorted images of grids were compared to determine the differences between the data sets. The distorted images resulted from placing the camera too close to the specimen, thereby creating a parallax. Although a statistical significant difference existed between the standard and distorted grids, it was shown that because the parallax was consistent (due to a standardization of the camera set-up), the variation was small enough and the error was constant so that the data could still be used in subsequent geometric morphometric analyses. This could be important in geometric morphometric analyses, particularly when parallaxes in images are detected after the data collection has already begun and it is not plausible to reacquire the specimens.

Animals↗

PubMed1997

Determination of mean particle volume, a Monte Carlo simulation.

Either length measurements or area measurements may be made on a sample of profiles for the purpose of estimating the mean volume of a population of convex particles. Diameters of spheres, caliper diameters of ellipsoids and intercept lengths are available length measurements. Profile areas can be evaluated by planimetry or point counting. Either all the available profiles in random sections or point sampled profiles can be utilized. We have applied a Monte Carlo simulation to compare several of the stereologic methods for the estimation of the mean volumes of spheres and ellipsoids. Populations of spherical, prolate ellipsoidal and oblate ellipsoidal particles were subjected to random sectioning and measurement. Diameter, point sampled intercept length, area and point sampled area were measured in the case of the spherical particles. With the ellipsoids, the same measurement excepting diameters were performed. The measurements were converted to volumes by the appropriate equations, and the means, the standard deviations of the means and the 95% confidence intervals were determined for increasing sample sizes. All the methods provide estimates that converge on their theoretical mean volumes. The area measurements and particularly the point sampled area measurement show some advantage over the length measurements, but differences among the methods are small, not entirely consistent over the different cases and unlikely to be significant in most real applications.

Algorithms↗

PubMed1991

Degenerate Hopf bifurcation and isolated periodic solutions of the Hodgkin-Huxley model with varying sodium ion concentration.

Points of degenerate Hopf bifurcation in the Hodgkin-Huxley model are found as parameters temperature T and voltage level of sodium VNa are varied. Local techniques of degenerate Hopf bifurcation analysis are used to show the existence of families of periodic solutions of the model: isolated branches of periodic solutions (i.e. branches not connected to the stationary branch) are found in addition to Hopf branches. Purely numerical techniques are used to show that the isolas persist for VNa up to a value slightly greater than 114 mV. Under some conditions there are multiple stable periodic solutions, so "jumping" between action potentials of different amplitudes might be observed.

Action Potentials↗

PubMed1990

Computerized morphonuclear cell image analyses of malignant disease in bladder tissues.

We analyzed the relationship between several morphonuclear parameters related to nuclear size, densitometry (deoxyribonucleic acid content and ploidy) and the chromatin pattern versus the histopathological grading of 46 bladder cancer samples graded according to the World Health Organization classification. We used a SAMBA 200 cell image processor with software allowing for the discrimination of 15 different parameters on Feulgen-stained imprint smears. In addition, we set up preliminary data banks that enable objective and reproducible grading of unknown cases. This approach must be validated in a large series of cases to create an expert system for bladder malignancy diagnosis.

Cell Division↗

PubMed2001

Parallel cascade identification and its application to protein family prediction.

Parallel cascade identification is a method for modeling dynamic systems with possibly high order nonlinearities and lengthy memory, given only input/output data for the system gathered in an experiment. While the method was originally proposed for nonlinear system identification, two recent papers have illustrated its utility for protein family prediction. One strength of this approach is the capability of training effective parallel cascade classifiers from very little training data. Indeed, when the amount of training exemplars is limited, and when distinctions between a small number of categories suffice, parallel cascade identification can outperform some state-of-the-art techniques. Moreover, the unusual approach taken by this method enables it to be effectively combined with other techniques to significantly improve accuracy. In this paper, parallel cascade identification is first reviewed, and its use in a variety of different fields is surveyed. Then protein family prediction via this method is considered in detail, and some particularly useful applications are pointed out.

Computational Biology↗

PubMed2001

A simple computerized program for the calculation of the required sample size necessary to ensure statistical accuracy in medical experiments.

We developed a sample size estimation program (SSEP) with which medical researchers can easily estimate the appropriate sample size for a specific significance level and statistical power using their favorite WWW browsers. SSEP can estimate the sample sizes for six statistical methods by Monte-Carlo simulation: Student's t-test, Welch's t-test, Analysis of variance, Wilcoxon's rank sum test, Kruskal-Wallis test, and the Cochran-Armitage test for linear trends. The SSEP simulation programs were created using the SAS software macro language. Medical researchers can interactively use this program and determine reliable sample sizes when planning new prospective clinical studies and animal experiments.

Computer Simulation↗

PubMed2002

Using snakes to detect the intimal and adventitial layers of the common carotid artery wall in sonographic images.

This study presents an innovative automatic system for detecting the intima-media complex of the far wall of the common carotid artery by applying the snake techniques. Cohen's snake was modified and some criteria were added for our applications. In addition, the oscillating problem of using snakes was solved by properly choosing the time step from analysis of the frequency response of the filters. A time-diminishing gravity window, external forces, and a cost function assist the snake in selecting the optimal shape of intimal and adventitia layers. We compared the proposed snake and ziplock snake with respect to the manual extraction contour. The results show that the system can automatically detect the intimal and adventitial layers without any manual correction.

Algorithms↗

PubMed2003

Improved prediction-based ovarian follicle detection from a sequence of ultrasound images.

A new algorithm is presented for ovarian follicle recognition from a sequence of ultrasound images. The basic version of the prediction-based algorithm is upgraded by means of two improvements. The negative influence brought by the gross measurement errors is suppressed, and the locality of the treated process is considered. The basis for both improvements is the Kalman filter. The proposed algorithm is a combination of three mutually dependent Kalman filters: a global one whose parameters are then modified by two additional ones, firstly detecting the gross measurement errors and secondly, regarding the recognised contour of the object. The obtained results show that the follicles recognised using the final prediction algorithm are about 2% more compact and about 6% more accurate, on average, when compared to the values obtained using the basic prediction-based algorithm.

Algorithms↗

PubMed2003

Token swap test revisited.

The token swap test measures the association between row and column variables of a 2 x 2 table in sample misclassification space, and makes no assumptions about repeated, random sampling from a source population. Despite its conceptual usefulness, the token swap test is not implemented by standard statistical software packages. Here the author describes 'tokenSwaps', a Mathematica program that performs a token swap test. The 'tokenSwaps' program also performs a one-tailed Fisher exact test, allowing results of the two methods to be compared. The program uses recursive functional programming and local rewrite rules to achieve substantial coding economy. Examples of the operation of the program are given, and its limitations are discussed.

Computational Biology↗

PubMed1998

NLMEM: a new SAS/IML macro for hierarchical nonlinear models.

Analysis of longitudinal data is one of the most challenging tasks in statistical modeling. In the analysis, it is often necessary to take into account nonlinear response to a set of parameters of interest and correlation between measurements taken from the same individual. In addition, between- and within-subject variation has to be handled properly. An example of addressing these issues is the hierarchical nonlinear model, where parameter estimation can be performed using linearization method. In this paper a new NLMEM SAS/IML macro for hierarchical nonlinear models is proposed. The program uses a portion of the code developed earlier in NLINMIX. NLMEM retains all the benefits of NLINMIX while allowing the systematic part of the model structure to be specified using IML syntax. Consequently, NLMEM allows estimation of models which are not tractable using NLINMIX. In particular, it allows us to address advanced population pharmacokinetics and pharmacodynamics models specified by ordinary differential equations.

Computer Simulation↗

PubMed2000

The biometrical comparison of cardiac imaging methods.

OBJECTIVES: Biometrical comparison procedures for cardiac imaging methods with continuous outcome are reviewed mainly concentrating on assessment and design adequate comparison of accuracy and precision. Univariate graphical and numerical representation of corresponding deviations is outlined to derive a 'check list' of minimum information necessary to compare the measurement methods. DATA: The methods reviewed here are illustrated by the comparison of standard 2DE bidimensional cardial volumetry versus assessment using TDE colour imaging in 28 normal probands. SOURCES: The paired t-test and the corresponding confidence interval approach are used to assess deviations in location of two imaging methods; the test procedures of Maloney and Rastogi Hahn and Nelson and Grubbs are surveyed as proposals for the comparison of precisions in paired data. The Krippendorff coefficient and the Bradley/Blackwood test are illustrated as surrogate measures for method concordance. CONCLUSIONS: Since these methods can be performed by simple modification of standard options available in most statistics software packages, this review intends to enable cardiologists to choose appropriate methods for statistical data analysis and representation on their own.

Biometry↗

PubMed2001

Fingerprints classification using artificial neural networks: a combined structural and statistical approach.

This paper describes a fingerprint classification algorithm using Artificial Neural Networks (ANN). Fingerprints are classified into six categories: arches, tented arches, left loops, right loops, whorls and twin loops. The algorithm extracts a string of symbols using the block directional image of a fingerprint, which represents the set of structural features for this image. The moment representing the statistical feature of the pattern is computed for this string and its Euclidean Distance Measures (EDM) are computed by using this moment. Our discrimination system uses a multilayer artificial neural network composed of six subnetworks one for each class. The classifier was tested on 1,500 images of good quality in the Egyptian Fingerprints database; images with poor quality were rejected. In the six-class problem the network achieved 95% classification accuracy. In the five-class problem when we place whorls and twin loops together in the same category the classification accuracy was around 99%. In the four-class problem when we place arches and tented arches in the same class the classification accuracy was 99%.

Algorithms↗

PubMed2001

Information visualisation in clinical Odontology: multidimensional analysis and interactive data exploration.

In 1995, the MedView project, based on a co-operation between computing science and clinical medicine was initiated. The overall goal of the project was to develop models, methods and tools to support clinicians in their daily diagnostic work. As part of MedView, two information visualisation tools were developed and tested as solutions to the problem of visualising clinical experience derived from large amounts of clinical data. The first tool (The Cube) was based on the idea of dynamic three-dimensional (3D) parallel diagrams, an idea similar to the notion of 3D parallel co-ordinates. The Cube was developed to enhance the clinician's ability to intelligibly analyse existing patient material and to allow for pattern recognition and statistical analysis. The second tool (SimVis) was based on a similarity assessment-based interaction model for exploring data, and was designed to help clinicians to classify and cluster clinical examination data. User interaction was supported by 3D visualisation of clusters and similarity measures. Both tools were tested on a knowledge base containing about 1500 examinations obtained from different clinics. Clinical practice indicated that the basic ideas are conceptually appealing to the involved clinicians as the tools can be used for generating and testing of hypotheses.

Humans↗

PubMed2003

A multiple classifier system for early melanoma diagnosis.

Melanoma is the most dangerous skin cancer and early diagnosis is the key factor in its successful treatment. Well-trained dermatologists reach a diagnosis via visual inspection, and reach sensitivity and specificity levels of about 80%. Several computerised diagnostic systems were reported in the literature using different classification algorithms. In this paper, we will illustrate a novel approach by which a suitable combination of different classifiers is used in order to improve the diagnostic performances of single classifiers. We used three different kinds of classifiers, namely linear discriminant analysis (LDA), k-nearest neighbour (k-NN) and a decision tree, the inputs of which are 38 geometric and colorimetric features automatically extracted from digital images of skin lesions. Multiple classifiers were generated by combining the diagnostic outputs of single classifiers with appropriate voting schemata. This approach was evaluated on a set of 152 digital skin images. We compared the performances of multiple classifiers (2- and 3-classifier groups) between them and with respect to single ones (1-classifier group). We further compared the classifiers' performances with those of eight dermatologists. Classifiers' performances were measured in terms of distance from the ideal classifier. Compared with 1- and 2-classifier groups, performances of 3-classifier systems were significantly higher (P<0.0005 and P<0.001, respectively). No statistically significant differences were found between the 1- and 2-classifier groups (P=0.352). While the dermatologists group showed a level of performances significantly higher than the 1-classifier systems (P<0.020), no differences were found between the multiple classifier groups and the dermatologists groups, indicating comparable performances. This work suggests that a suitable combination of different kinds of classifiers can improve the performances of an automatic diagnostic system.

Algorithms↗

PubMed2001

Quantitative analysis of errors in fractionated stereotactic radiotherapy.

Fractionated stereotactic radiotherapy (FSRT) offers a technique to minimize the absorbed dose to normal tissues; therefore, quality assurance is essential for these procedures. In this study, quality assurance for FSRT of 58 cases, between August 1995 and August 1997 are described, and the errors for each step and overall accuracy were estimated. Some of the important items for FSRT procedures are: accuracy in CT localization, transferred image distortion, laser alignment, isocentric accuracy of linear accelerator, head frame movement, portal verification, and various human errors. A geometric phantom, that has known coordinates was used to estimate the accuracy of CT localization. A treatment planning computer was used for checking the transferred image distortion. The mechanical isocenter standard (MIS), rectilinear phantom pointer: (RLPP), and laser target localizer frame (LTLF) were used for laser alignment and target coordinates setting. Head-frame stability check was performed by a depth confirmation helmet (DCH). A film test was done to check isocentric accuracy and portal verification. All measured data for the 58 patients were recorded and analyzed for each item. 4-MV x-rays from a linear accelerator, were used for FSRT, along with homemade circular cones with diameters from 20 to 70 mm (interval: 5 mm). The accuracy in CT localization was 1.2+/-0.5 mm. The isocentric accuracy of the linear accelerator, including laser alignment, was 0.5+/-0.2 mm. The reproducibility of the head frame was 1.1+/-0.6 mm. The overall accuracy was 1.7+/-0.7 mm, excluding human errors.

Brain Neoplasms↗