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Results for “Measuring algorithm”

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At least 271 records · Page 15Linked to original sources

PubMed1990

A method for measuring neuroretinal rim area.

A practical method for measuring the neuroretinal rim area (NRA) of the optic nervehead is described. Sequential stereo photographs are taken on 35 mm colour transparencies using a Zeiss fundus camera with Allen stereoseparator. While examining a stereo pair with a pocket viewer the disc and cup margins are traced against the stereo image with a Rotring pen (0.1 mm tip) on a clear transparency overlying one of the photographs. This tracing is digitised and analysed by an 'edge detection' algorithm which measures the area between the traced lines, i.e. NRA. The intraobserver intraphotograph coefficient of variation (standard deviation/mean) was calculated for measurements of disc area, cup area and NRA made on 10 stereo photographs of discs with various topographies. Coefficients for NRA ranged from 3.2% to 3.9% for discs with easily discernible cup margins and from 1.6% to 7.2% for discs with less obvious cups.

Glaucoma↗

PubMed2006

Pelvic tracker effects on hip center accuracy using imageless navigation.

OBJECTIVE: Imageless computer assisted total knee surgical systems have commonly relied on determination of the functional rotational center of the femoral head as a landmark for determining the lower extremity mechanical axis. This has been accomplished through range of motion and center of rotation calculations for the femur with respect to the pelvis as the lower extremity is taken through a range of motion. Our study evaluated the use of this algorithm with and without a pelvic tracker attached to the iliac crest. MATERIALS AND METHODS: The functional center of the hip joint was also compared to the true radiographic center as determined by spiral CT data. Evaluating the different methods on six lower extremities from three whole-body cadavers revealed significant differences in the location of the calculated hip joint center, but little difference in the resulting lower extremity mechanical axis determination. The functional hip joint centers measured with and without a pelvic tracker differed from one another and from the CT-determined hip center. RESULTS: No differences were found in the coronal plane measurements, but statistically significant differences were found in the sagittal plane measurements. CONCLUSION: Algorithms that reduce the noise generated by pelvic movement should be devised to eliminate the need for a pelvic tracker.

Algorithms↗

PubMed2005

An algorithm using reticulocyte hemoglobin content (CHr) measurement in screening adolescents for iron deficiency.

PURPOSE: To evaluate whether the use of an algorithm including reticulocyte hemoglobin content (CHr), a new hematologic parameter, in addition to the screening complete blood count (CBC), improves detection of iron deficiency and iron deficiency anemia in healthy adolescents. METHODS: After initiation of an algorithm using CHr in addition to CBC results for identifying iron-deficient patients in a primary care hospital-based adolescent clinic, we reviewed results of all hematological tests performed in the clinic during an 8-month period. Electronic medical records were screened for health status and inclusion criteria. We determined the number of patients with low hematocrit values, low mean cell volume (MCV), and low CHr. To evaluate the impact of the protocol, we calculated the percentage of cases in which the CHr results suggested a management plan different from that which would have been formulated using the CBC results only. RESULTS: A total of 381 patients (mean age 16.8 +/- 3.1 years) were included in the study. Anemia was diagnosed by the Centers for Disease Control (CDC) guidelines in 63 patients (16.5%), low MCV in 170 patients (44.6%), and a low CHr in 80 (21%) patients. In 68% of anemia cases, a normal CHr suggested that iron deficiency was not the cause of the anemia. Although low MCV values were found in 38 (60.4%) of all anemic cases, mean MCV was significantly (p < 0.001) lower in the 19 cases with a low CHr as well. In 19% of 318 patients with a normal hematocrit (HCT), a low CHr suggested the need for treatment of early iron deficiency. In 103 (27%) cases, CHr suggested a different treatment plan from that which would have been formulated using the screening CBC only. CONCLUSIONS: The use of an algorithm including CHr to screen for iron deficiency anemia may increase the accuracy of diagnosis, enabling early detection and treatment of iron deficiency in adolescents without the need for additional costly iron studies.

Adolescent↗

PubMed2003

DPX: for the analysis of the protein core.

SUMMARY: In order to obtain an accurate description of the protein interior, we describe a simple and fast algorithm that measures the depth of each atom in a protein (dpx), defined as its distance (A) from the closest solvent accessible atom. The program reads a PDB file containing the atomic solvent accessibility in the B-factor field, and writes a file in the same format, where the B-factor field now contains the dpx value. Output structure files can be thus directly displayed with molecular graphics programs like RASMOL, MOLMOL, Swiss-PDB View and colored according to dpx values. AVAILABILITY: The algorithm is implemented in a standalone program written in C and its source is freely available at ftp.icgeb.trieste.it/pub/DPX or on request from the authors.

Algorithms↗

PubMed2003

Evaluating image reconstruction methods for tumor detection in 3-dimensional whole-body PET oncology imaging.

UNLABELLED: We compare 3 image reconstruction algorithms for use in 3-dimensional (3D) whole-body PET oncology imaging. We have previously shown that combining Fourier rebinning (FORE) with 2-dimensional (2D) statistical image reconstruction via the ordered-subsets expectation-maximization (OSEM) and attenuation-weighted OSEM (AWOSEM) algorithms demonstrates improvements in image signal-to-noise ratios compared with the commonly used analytic 3D reprojection (3DRP) or FORE+FBP (2D filtered backprojection) reconstruction methods. To assess the impact of these reconstruction methods on detecting and localizing small lesions, we performed a human observer study comparing the different reconstruction methods. The observer study used the same volumetric visualization software tool that is used in clinical practice, instead of a planar viewing mode as is generally used with the standard receiver operating characteristic (ROC) methodology. This change in the human evaluation strategy disallowed the use of a ROC analysis, so instead we compared the fraction of actual targets found and reported (fraction-found) and also investigated the use of an alternative free-response operating characteristic (AFROC) analysis. METHODS: We used a non-Monte Carlo technique to generate 50 statistically accurate realizations of 3D whole-body PET data based on an extended mathematic cardiac torso (MCAT) phantom and with noise levels typical of clinical scans performed on a PET scanner. To each realization, we added 7 randomly located 1-cm-diameter lesions (targets) whose contrasts were varied to sample the range of detectability. These targets were inserted in 3 organs of interest: lungs, liver, and soft tissues. The images were reconstructed with 3 reconstruction strategies (FORE+OSEM, FORE+AWOSEM, and FORE+FBP). Five human observers reported (localized and rated) 7 targets within each volume image. An observer's performance accuracy with each algorithm was measured, as a function of the lesion contrast and organ type, by the fraction of those targets reported and by the area below the AFROC curve. This AFROC curve plots the fraction of reported targets at each rating threshold against the fraction of cases with (> or =1) similarly rated false reports. RESULTS: Images reconstructed with FORE+AWOSEM yielded the best overall target detection as compared with FORE+FBP and FORE+OSEM, although these differences in detectability were region specific. The FORE+FBP and FORE+AWOSEM algorithms had similar performances for liver targets. The FORE+OSEM algorithm performed significantly worse at target detection, especially in the liver. We speculate that this is the result of using an incorrect statistical model for OSEM and that the incorporation of attenuation weighting in AWOSEM largely compensates for this model inaccuracy. These results were consistent for both the fraction of actual targets found and the AFROC analysis. CONCLUSION: We demonstrated the efficacy of performing observer detection studies using the same visualization tools as those used in clinical PET oncology imaging. These studies demonstrated that the FORE+AWOSEM algorithm led to the best overall detection and localization performance for 1-cm-diameter targets compared with the FORE+OSEM and FORE+FBP algorithms.

Algorithms↗

PubMed2005

RSA wear measurements with or without markers in total hip arthroplasty.

Novel algorithms for radiostereometric (RSA) measurements of the femoral head and metal-backed, hemi-spherical cups of a total hip replacement are presented and evaluated on phantom images and clinical double examinations of 20 patients. The materials were analysed with classical RSA and three novel algorithms: (1) a dual-projection head algorithm using the outline of the femoral head together with markers in the cup; (2) a marker-less algorithm based on measurements of the outline of the femoral head, the cup shell and opening circle of the cup; and (3) a combination of both methods. The novel algorithms improve current, marker-based, RSA measurements, as well as allows studies without marked cups. This opens the possibility of performing wear measurements on larger group of patients, in clinical follow-ups, even retrospective studies. The novel algorithms may help to save patient data in current RSA studies lost due to insufficiently marked cups. Finally, the novel algorithms simplify the RSA procedure and allow new studies without markers, saving time, money, and reducing safety concerns. Other potential uses include migration measurements of re-surfacing heads and measuring spherical sections as implant landmarks instead of markers.

Algorithms↗

PubMed1994

Image analysis software for the detection of preneoplastic and early neoplastic lesions.

Preneoplastic lesions are usually small, and often appear as foci of atypical cells that blend into the surrounding normal tissue without producing a detectable tumor mass. Since these lesions seldom provide adequate tissue for biochemical studies, their detection often depends upon subtle distinctions in cytologic features. Image analysis permits pathologists to obtain quantitative measurements on cytologic and histologic preparations, so that visual impressions can be augmented by quantitative morphometry. Preneoplastic lesions have well-described morphometric features relating to nuclear area, texture, or shape. It is now feasible for every pathology department to capture images of pathologic material with equipment costing less than the price of a microscope. Captured image files can be analyzed using commercial software or software developed in several U.S. government agencies and made freely available to the public. Image analysis has been shown to improve the detection of preneoplastic cells. Recent improvements in the resolution of captured images, in the algorithms that measure preneoplastic descriptors, and in the ease and speed of transmission of images between laboratories, should increase our ability to detect and treat preneoplastic lesions.

Carcinoma in Situ↗

PubMed2002

Lateral diffusion coefficients in membranes measured by resonance energy transfer and a new algorithm for diffusion in two dimensions.

We describe measurements of lateral diffusion in membranes using resonance energy transfer. The donor was a rhenium (Re) metal-ligand complex lipid, which displays a donor decay time near 3 micros. The long donor lifetime resulted in an ability to measure lateral diffusion coefficient below 10(-8) cm(2)/s. The donor decay data were analyzed using a new numerical algorithm for calculation of resonance energy transfer for donors and acceptors randomly distributed in two dimensions. An analytical solution to the diffusion equation in two dimensions is not known, so the equation was solved by the relaxation method in Laplace space. This algorithm allows the donor decay in the absence of energy transfer to be multiexponential. The simulations show that mutual lateral diffusion coefficients of the donor and acceptor on the order of 10(-8) cm(2)/s are readily recovered from the frequency-domain data with donor decay times on the microsecond timescale. Importantly, the lateral diffusion coefficients and acceptor concentrations can be recovered independently despite correlation between these parameters. This algorithm was tested and verified using the donor decays of a long lifetime rhenium lipid donor and a Texas red-lipid acceptor. Lateral diffusion coefficients ranged from 4.4 x 10(-9) cm(2)/s in 1,2-dimyristoyl-sn-glycero-3-[phospho-rac-(1-glycerol)] (DMPG) at 10 degrees C to 1.7 x 10(-7) cm(2)/s in 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) at 35 degrees C. These results demonstrated the possibility of direct measurements of lateral diffusion coefficients using microsecond decay time luminophores.

Algorithms↗

PubMed1993

Non-invasive monitoring of the redox state of cytochrome oxidase in living tissue using near-infrared laser lights.

A triple wavelength spectrophotometric method was developed to monitor changes in the concentrations of oxygenated and deoxygenated hemoglobin, and in the redox state of cytochrome oxidase in living tissue. Three wavelengths of an NIR (near-infrared) laser beam were used to monitor hemoglobin (780, 805 and 830 nm) and cytochrome (cyt.) oxidase (780, 790 and 830 nm). Algorithms for calculating changes in the concentrations of oxidized cyt. oxidase (aa3), and oxygenated and deoxygenated hemoglobin were developed using NIR spectral analysis of these chromatophores. To assess the ability of these algorithms to measure independent changes in the concentration of oxy-, deoxyhemoglobin and oxidized cyt. oxidase in tissue, experiments involving a fluorocarbon (FC-43) exchange transfusion at very low hematocrits were conducted in anesthetized rats. The observed data indicate that FC-43 circulation at FiO2 1.0 can supply sufficient oxygen to the rat brain to maintain the oxidation state of mitochondrial oxidase (cyt.aa3) near pre-exchange levels. The relationships between changes in oxidized cyt. oxidase and oxyhemoglobin content in response to variations in FiO2 of inspired gas were then examined in the rat brain. These results also confirmed the ability of the triple wavelength algorithms to distinguish changes in the oxidized copper band of cyt.aa3 from those in absorption by oxy- and deoxyhemoglobin. NIR monitoring of skeletal muscle to determine the redox state of cyt. oxidase was performed in a few human cases and the results indicated that these observations can increase our understanding of the process of oxygen transport to tissues.

Algorithms↗

PubMed2004

Updating a 3-D vertebral body finite element model using 2-D images.

In osteoporotic patients, vertebral strength is often evaluated in the clinical setting using bone densitometry methods, such as dual energy X-ray absorptiometry. Finite element models based on computed tomography (CT) have been shown to outperform such methods in predicting fracture strength, but repetitive use of CT scans may be impractical due to cost, availability, and radiation exposure. We propose a method of generating a vertebral model at an initial time point which can subsequently be updated using several digital radiographs by using an algebraic reconstruction technique (ART) to find the three-dimensional density distribution. The effectiveness of the algorithm was measured by comparison of the error of the reconstructed model to the error incurred by using the outdated model. Application of the ART was able to reduce density errors from 30% to under 7% and to reduce errors in calculated vertebral stiffness from 125% to under 10%. This preliminary study demonstrates that the method is valid and could potentially improve fracture risk diagnostics drastically.

Absorptiometry, Photon↗

PubMed2002

Simulation of cDNA microarrays via a parameterized random signal model.

cDNA microarrays provide simultaneous expression measurements for thousands of genes that are the result of processing images to recover the average signal intensity from a spot composed of pixels covering the area upon which the cDNA detector has been put down. The accuracy of the signal measurement depends on using an appropriate algorithm to process the images. This includes determining spot locations and processing the data in such a way as to take into account spot geometry, background noise, and various kinds of noise that degrade the signal. This paper presents a stochastic model for microarray images. There are over 20 model parameters, each governed by a probability distribution, that control the signal intensity, spot geometry, spot drift, background effects, and the many kinds of noise that affect microarray images owing to the manner in which they are formed. The model can be used to analyze the performance of image algorithms designed to measure the true signal intensity because the ground truth (signal intensity) for each spot is known. The levels of foreground noise, background noise, and spot distortion can be set, and algorithms can be evaluated under varying conditions.

Algorithms↗

PubMed2000

ECG data compression using optimal non-orthogonal wavelet transform.

This paper introduces an effective technique for the compression of electrocardiogram (ECG) signals. The technique is based on a new class of non-orthogonal discrete wavelet transform (DWT). The performance of ECG compression algorithm is measured by its ability to minimize distortion while retaining all clinically significant features of the signal. The percent root-mean square difference (PRD) is used as an accepted standard for measuring the signal distortion. However, there is no standard for measuring the clinically significant features retained after signal reconstruction. The coefficients of the DWT are calculated such that the square of the difference between the original signal and the reconstructed one is minimum in least mean square sense. The resulting transforms deal with signals of arbitrary lengths; that means the signal length is not restricted to be a multiple of power of 2. Numerical results comparing the performance of the constructed non-orthogonal transform with that of W-transform and Daubechies D(4) orthogonal transform are given. These results show that, independent of signal length, the decomposition of the signal up to the fourth level is sufficient for getting minimum PRD. In addition, the proposed technique yields the lowest PRD compared to the other two algorithms and for a compression ratio less than 10 the optimal transform can be obtained for only one ECG period. However, for a higher compression ratio the PRD is smaller for long signals.

Algorithms↗

PubMed2005

Modularized learning of genetic interaction networks from biological annotations and mRNA expression data.

MOTIVATION: Inferring the genetic interaction mechanism using Bayesian networks has recently drawn increasing attention due to its well-established theoretical foundation and statistical robustness. However, the relative insufficiency of experiments with respect to the number of genes leads to many false positive inferences. RESULTS: We propose a novel method to infer genetic networks by alleviating the shortage of available mRNA expression data with prior knowledge. We call the proposed method 'modularized network learning' (MONET). Firstly, the proposed method divides a whole gene set to overlapped modules considering biological annotations and expression data together. Secondly, it infers a Bayesian network for each module, and integrates the learned subnetworks to a global network. An algorithm that measures a similarity between genes based on hierarchy, specificity and multiplicity of biological annotations is presented. The proposed method draws a global picture of inter-module relationships as well as a detailed look of intra-module interactions. We applied the proposed method to analyze Saccharomyces cerevisiae stress data, and found several hypotheses to suggest putative functions of unclassified genes. We also compared the proposed method with a whole-set-based approach and two expression-based clustering approaches.

Algorithms↗

PubMedDate not supplied

Characterization of small nodules by automatic segmentation of X-ray computed tomography images.

OBJECTIVE: To characterize the ability of an automatic lung nodule segmentation algorithm to measure small nodule dimensions and growth rates. METHODS: A phantom of 20 sets of 6 balls each (11 different nylon balls and 9 acrylic balls) of 1 to 9.5 mm in diameter, in foam, was imaged using x-ray computed tomography with slice thicknesses of 5, 2.5, and 1.25 mm, pitches of 3 and 6, and standard and lung resolution. Measurements consisted of volume and maximum in-plane cross-sectional areas and their derived maximum and effective diameters. Growth rates were simulated using pairs of groups of balls. RESULTS: Volume measurements overestimate volume, more so for thicker slices. For the largest balls, the error is 60% for 5-mm slices and 20% for 1.25-mm slices. Effective diameter calculated from volume better approximates actual diameter. For area measurements, errors are 0% to 5% for the largest balls, and the effective and actual diameters are closely matched. CONCLUSIONS: Below 5 mm in diameter, changes in volume should reach 100% for reliable indication of growth. Above 6 mm, the threshold for detecting change is on the order of 25% growth. Even under ideal conditions, results indicate the need for caution when making a diagnosis of malignancy on the basis of volume change.

Algorithms↗

PubMed2002

Voluntary control of static endpoint stiffness during force regulation tasks.

The goals of this study were to determine the degree to which subjects could voluntarily modulate static endpoint stiffness orientation and to quantify the effects of simultaneously generated voluntary endpoint forces on this ability. Static endpoint stiffness, which characterizes the relationship between externally imposed displacements of the hand and the elastic forces generated in response, was estimated in real time during the application of planar, stochastic perturbations of endpoint position. This estimation was accomplished using a real-time parametric identification algorithm on measured force and position data. Subjects were provided with real-time visual feedback of endpoint stiffness, and their ability to modulate the orientation of maximum static stiffness was measured for different endpoint force magnitudes and directions. We found that individuals can voluntarily change stiffness orientation but that the magnitude of these changes is small, the range of available stiffness orientations decreases as endpoint force exertion increases, and endpoint force direction significantly constrains direction and magnitude of the stiffness orientations that can be achieved. Given these findings it appears unlikely that static endpoint stiffness orientation is controlled independently of force by voluntary neural mechanisms during postural tasks.

Algorithms↗

PubMed2000

Fusion of body surface potential and body surface Laplacian signals for electrocardiographic imaging.

Various approaches to the solution to the inverse problem of electrocardiography have been proposed over the years. Recently, the use of inverse algorithms using measured body surface Laplacians has been proposed, and in various studies this technique has been shown to outperform the traditional use of body surface potentials in certain model problems. In this paper, we compare the use of body surface potentials and body surface Laplacians on two model problems with different assumed cardiac sources. For the spherical cap model problems with an anterior source, the epicardial estimates using body surface potentials had smaller average relative errors than when body surface Laplacians were used. For the spherical cap model problems with a posterior source, the epicardial estimates using body surface potential or body surface Laplacian sensors generally produced similar relative errors. For the radial dipole model, the epicardial estimates using body surface Laplacians had smaller errors than when body surface potentials were used. We introduce a fusion algorithm that combines the different types of signals and generally produces a good estimate for both model problems.

Algorithms↗

PubMed2005

Reproducible clusters from microarray research: whither?

MOTIVATION: In cluster analysis, the validity of specific solutions, algorithms, and procedures present significant challenges because there is no null hypothesis to test and no 'right answer'. It has been noted that a replicable classification is not necessarily a useful one, but a useful one that characterizes some aspect of the population must be replicable. By replicable we mean reproducible across multiple samplings from the same population. Methodologists have suggested that the validity of clustering methods should be based on classifications that yield reproducible findings beyond chance levels. We used this approach to determine the performance of commonly used clustering algorithms and the degree of replicability achieved using several microarray datasets. METHODS: We considered four commonly used iterative partitioning algorithms (Self Organizing Maps (SOM), K-means, Clutsering LARge Applications (CLARA), and Fuzzy C-means) and evaluated their performances on 37 microarray datasets, with sample sizes ranging from 12 to 172. We assessed reproducibility of the clustering algorithm by measuring the strength of relationship between clustering outputs of subsamples of 37 datasets. Cluster stability was quantified using Cramer's v2 from a kXk table. Cramer's v2 is equivalent to the squared canonical correlation coefficient between two sets of nominal variables. Potential scores range from 0 to 1, with 1 denoting perfect reproducibility. RESULTS: All four clustering routines show increased stability with larger sample sizes. K-means and SOM showed a gradual increase in stability with increasing sample size. CLARA and Fuzzy C-means, however, yielded low stability scores until sample sizes approached 30 and then gradually increased thereafter. Average stability never exceeded 0.55 for the four clustering routines, even at a sample size of 50. These findings suggest several plausible scenarios: (1) microarray datasets lack natural clustering structure thereby producing low stability scores on all four methods; (2) the algorithms studied do not produce reliable results and/or (3) sample sizes typically used in microarray research may be too small to support derivation of reliable clustering results. Further research should be directed towards evaluating stability performances of more clustering algorithms on more datasets specially having larger sample sizes with larger numbers of clusters considered.

Cluster Analysis↗

PubMed1997

Evaluation of algorithms used for cross-species proteome characterisation.

The ability to effectively search databases for the identification of protein spots from two-dimensional electrophoresis gels has become an essential step in the study of microbial proteomes. A variety of analytical techniques are currently being employed during protein characterisation. A number of algorithms used to search databases, accessible via the World Wide Web, depend upon information concerning N- and C-terminal microsequence, amino acid composition, and peptide-mass fingerprinting. The effectiveness of nine such algorithms, as well as COMBINED (software developed in this laboratory for identifying proteins across species boundaries) was examined. Fifty-four ribosomal proteins from the Mycoplasma genitalium genome, and 72 amino acyl tRNA synthetases from the Haemophilus influenzae, M. genitalium and Methanococcus jannaschii genomes were chosen for study. These proteins were selected because they represent a wide range of sequence identities across species boundaries (22.7-100% identity), as detected by standard sequence alignment tools. Such sequence variation allowed for a statistical comparison of algorithm success measured against published sequence identity. The ability of analytical techniques used in protein characterisation and associated database query programs to detect identity at the functional group level was examined for proteins with low levels of homology at the gene/protein sequence level. The significance of these theoretical data manipulations provided the means to predict the utility of data acquired experimentally for non-sequence-dependent software in proteome analysis. The data obtained also predicted that 'sequence tagging' of peptide fingerprints would need to be accompanied by at least 11-20 residues of amino acid sequence for it to be widely used for protein characterisation across species boundaries.

Algorithms↗