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O Nevalainen

Publications and source records attributed to O Nevalainen.

14 recordsLinked to original sources
PubMed2003

Electrophoretic signal comparison applied to mRNA differential display analysis.

Gene expression analysis by electrophoretic methods is currently limited by the labor-intensive visual evaluation of the electrophoretic signal profiles. For this purpose, we present a flexible approach to computer-assisted comparison of quantitative electrophoretic patterns between multiple expression signals. Gaussian curves are first fitted to the complex peak mixtures, and the resulting approximate signals are then aligned and compared on a peak-by-peak basis with respect to specific patterns defined by the investigator. The rationale of the method is to produce a compressed list of exceptional expression patterns quantified by a set of associated numeric features. A score value is attached to each pattern in such a way that large values identify the most potential findings to be focused on in visual analysis instead of the vast amount of original electrophoretic results. The validity of the method is demonstrated by analyzing a large set of electrophoretic data from mRNA differential display experiments monitoring changes in gene expression patterns in human colonic carcinoma. The automated identification of variously defined gene expression patterns agrees well with the visual evaluation of the same electropherograms. The general comparison approach may also be found useful with other gene expression profiling instruments.

Adenocarcinoma↗
PubMed2001

Automated detection of differently expressed fragments in mRNA differential display.

We present a novel method for the automated detection of fragments showing dissimilar expression in mRNA differential display. The analysis is based on aligning the numerical electrophoretic lane data in respect of a given distance function defined on a set of fragments, or signal peaks in general. We presume that significant dissimilarities between peaks result in extreme score values computed for aligned peak pairs. Whereas in sequence comparison, an overall sequence similarity score is conventionally used, the current method defines a special dissimilarity score for searching the peak pairs showing the largest relative differences between the lanes. The output of the analysis is a highly reduced list of peak pairs, along with a set of associated features extracted from the lanes. Only the peaks of this list need to be visually confirmed instead of the vast amount of peaks in the original electrophoretic results. The results obtained by the algorithm correlate well with results of visual evaluation of the same electropherograms. The current algorithm may be applied to the study of complex expression patterns in multiple lanes and, in general, to automated recognition of variously defined patterns of quantitative electrophoretic data.

Acute-Phase Proteins↗
PubMed2001

Algorithmic 3D simulation of breast calcifications for digital mammography.

We present a framework for algorithmic three-dimensional simulation of breast calcifications. The simulated calcifications can be viewed from any angle at a higher spatial resolution than currently available for digital mammography, and they can be placed onto a simulated or real mammographic background to provide example cases for computers and radiologists. In order to simulate calcification clusters, we also show how to simulate duct networks and terminal ductal lobular units. We evaluated the model with a double-blind evaluation of 60 cases with four experienced radiologists by mixing 30 cases of simulated calcification clusters on a real or simulated mammographic background with 30 cases of real breast calcification clusters digitized at a spatial resolution of 15 microm from high-resolution radiographs of 5 mm slices of breast specimens. The results indicate that the majority of the 2D projections of the 3D simulated calcifications compare favorably with the radiographic images of real breast calcifications.

Algorithms↗
PubMed2001

Analysis of inspiratory flow shapes in patients with partial upper-airway obstruction during sleep.

STUDY OBJECTIVE: To study the spectrum of inspiratory flow signal shapes in patients with partial upper airway obstruction during sleep. DESIGN: We identified seven different inspiratory flow shapes and determined their frequencies in two groups of patients (10 postmenopausal women and 19 men after surgical treatment for sleep apnea) and in 9 control subjects. SETTING: Sleep research unit, Department of Physiology, University of Turku, Finland. MEASUREMENTS AND RESULTS: Nasal flow was recorded with nasal prongs. The shape analyses were performed with an automated attribute grammar recognizer. The inspiratory flow-shape distributions differed significantly between patients and control subjects. The flow shapes were also different between postmenopausal women and men after uvulopalatopharyngoplasty. CONCLUSIONS: The differences in the inspiratory flow-shape distributions between the control subjects and the two patient groups suggest that the upper airways behave differently in the three study groups. Automated inspiratory flow-shape analysis seems to be a promising tool to distinguish patient groups with different upper airway function to be treated with different treatment alternatives. The physiologic correlates of each flow-shape class remain to be elucidated.

Adult↗
PubMed2000

Analysis of similarity of electrophoretic patterns in mRNA differential display.

We present a novel method of statistical analysis for the comparison of electrophoretic data. The method is based on the squared Euclidian distance of normalized signal data vectors of electrophoretic lanes. The differences in the electrophoretic patterns are evaluated by a statistical test based on Hubert's statistics which measures the significance of the signal grouping. We demonstrate the validity and applicability of the method in a large data set derived from automated fluorescent mRNA differential display analysis of the expression of acute-phase proteins during experimental Escherichia coli infection in mice. The current testing method is capable of finding theoretically similar natural groupings to be similar in a statistically significant way whereas theoretically dissimilar or random groupings can be recognized to be artifactual. We also show how the calculated pairwise signal distances can be utilized in methodological problem solving. These analytical methods can be applied to the study of other related problems of similarity analysis of electrophoretic patterns, and also provide useful tools for the development of automated recognition of differentially expressed mRNAs.

Animals↗
PubMed2000

Detection of high-frequency respiratory movements during sleep.

Sleep-related breathing disorders are common in adults and they have a significant impact on vigilance and quality of life. Previous studies have shown the validity of the static-charge-sensitive bed (SCSB) in monitoring breathing abnormalities during sleep. A whole nights sleep study produces a signal with considerable length, and therefore an automated analysis system would be of great need. In this work we focus on detection of high-frequency respiratory movement (HFRM) patterns which are related to increased respiratory efforts. The paper documents four methods to automatically detect these patterns. The first two are based on classical statistical tests applied to the SCSB signal, and the other two use spectral characteristics in order to adaptively segment the SCSB signal. Finally we adjust each method to detect patterns that coincide with the HFRMs determined by an expert, and evaluate the performance of the methods using independent test data.

Algorithms↗
PubMed2000

Minimizing stochastic complexity using local search and GLA with applications to classification of bacteria.

In this paper, we compare the performance of two iterative clustering methods when applied to an extensive data set describing strains of the bacterial family Enterobacteriaceae. In both methods, the classification (i.e. the number of classes and the partitioning) is determined by minimizing stochastic complexity. The first method performs the minimization by repeated application of the generalized Lloyd algorithm (GLA). The second method uses an optimization technique known as local search (LS). The method modifies the current solution by making global changes to the class structure and it, then, performs local fine-tuning to find a local optimum. It is observed that if we fix the number of classes, the LS finds a classification with a lower stochastic complexity value than GLA. In addition, the variance of the solutions is much smaller for the LS due to its more systematic method of searching. Overall, the two algorithms produce similar classifications but they merge certain natural classes with microbiological relevance in different ways.

Algorithms↗
PubMed1999

Classification of nasal inspiratory flow shapes by attributed finite automata.

In a significant proportion of individuals, the physiologic decrease of muscle tone during sleep results in increased collapsibility of the upper respiratory airway. At peak inspiratory flow, the pharyngeal soft tissues may collapse and cause airflow limitation or even complete occlusion of the upper airway (sleep apnea). While there are plenty of methods to detect sleep apnea, only a few can be used to monitor flow limitation in sleeping individuals. Nasal prongs connected to pressure sensor provide information of the nasal airflow over time. This paper documents a method to automatically classify each nasal inspiratory pressure profile into one without flow limitation or six flow-limited ones. The recognition of the sample signals consists of three phases: preprocessing, primitive extraction, and word parsing phases. In the last one, a sequence of signal primitives is treated as a word and we test its membership in the attribute grammars constructed to the signal categories. The method gave in practical tests surprisingly high performance. Classifying 94;pc of the inspiratory profiles in agreement with the visual judgment of an expert physician, the performance of the method was considered good enough to warrant further testing in well-defined patient populations to determine the pressure profile distributions of different subject classes.

Algorithms↗
PubMed1999

The Kautsky curve is a built-in barcode.

We identify objects from their visually observable morphological features. Automatic methods for identifying living objects are often needed in new technology, and these methods try to utilize shapes. When it comes to identifying plant species automatically, machine vision is difficult to implement because the shapes of different plants overlap and vary greatly because of different viewing angles in field conditions. In the present study we show that chlorophyll a fluorescence, emitted by plant leaves, carries information that can be used for the identification of plant species. Transient changes in fluorescence intensity when a light is turned on were parameterized and then subjected to a variety of pattern recognition procedures. A Self-Organizing Map constructed from the fluorescence signals was found to group the signals according to the phylogenetic origins of the plants. We then used three different methods of pattern recognition, of which the Bayesian Minimum Distance classifier is a parametric technique, whereas the Multilayer Perceptron neural network and k-Nearest Neighbor techniques are nonparametric. Of these techniques, the neural network turned out to be the most powerful one for identifying individual species or groups of species from their fluorescence transients. The excellent recognition accuracy, generally over 95%, allows us to speculate that the method can be further developed into an application in precision agriculture as a means of automatically identifying plant species in the field.

Biophysical Phenomena↗
PubMed1997

Computer analysis of living cells: movements of the chromatoid body in early spermatids compared with its ultrastructure in snap-frozen preparations.

Quantitative analyses of cytoplasmic and nuclear organelle movements in living interphase cells at defined stages of differentiation are few. By phase contrast videomicroscopy and digital imaging techniques, we have traced the path of the chromatoid body (CB) and analysed its rapidly changing positions in relation to the nuclear envelope, Golgi complex and nuclear pale chromatin areas in living early spermatids of the rat. The CB had intimate interactions with the nuclear envelope and moved both in parallel and perpendicular fashion in relation to it. It had successive short contacts with the Golgi complex and nuclear pale chromatin areas. It was also seen to scan between two pale chromatin areas and it had pinocytosis-like transient engulfments during interactions with the pale chromatin. In ultrastructural analysis of snap-frozen preparations, the CB had a large contact area with the nuclear envelope with several intermediate organelles that may be involved in nucleocytoplasmic material transport. It is evident that quantitative image analysis of living cells is a powerful guide for ultrastructural analyses. The snap-freezing technique gives new possibilities for studies of structures that are sensitive to conventional fixation procedures.

Animals↗
PubMed1992

MULTICOMP: a program package for multiple sequence comparison.

An algorithm for multiple sequence comparison was implemented in FORTRAN 77 for VAX/VMS in GCG-compatible format. The MULTICOMP program package includes several procedures with which one query sequence can be compared simultaneously to several DNA, RNA or amino acid sequences. The same technique was also introduced for comparing propensities of secondary structural features, which can be predicted on the basis of amino acid sequences. The technique has been applied to a wide range of sequence and structural analyses.

Algorithms↗
PubMedDate not supplied

Accurate segmentation of the breast region from digitized mammograms.

The segmentation of a digital mammogram into the breast region and the background is a necessary prerequisite in computer-assisted diagnosis of mammograms. By the exclusion of the background region, the accuracy of the analysis is increased and the running-time is decreased. The algorithm which segments the breast region from the background should be fully automated and give correct results for all kinds of digitized mammograms, including low-quality images. In this paper we present such an algorithm based on histogram thresholding, morphological filtering and contour modeling. Quantitative test results indicate that the computed boundary follows the estimated boundary accurately.

Algorithms↗
PubMedDate not supplied

A comparison of lossless compression methods for medical images.

In this work, lossless grayscale image compression methods are compared on a medical image database. The database contains 10 different types of images with bit rates varying from 8 to 16 bits per pixel. The total number of test images was about 3000, originating from 125 different patient studies. Methods used for compressing the images include seven methods designed for grayscale images and 18 ordinary general-purpose compression programs. Furthermore, four compressed image file formats were used. The results show that the compression ratios strongly depend on the type of the image. The best methods turned out to be TMW, CALIC and JPEG-LS. The analysis step in TMW is very time-consuming. CALIC gives high compression ratios in a reasonable time, whereas JPEG-LS is nearly as effective and very fast.

Computer Graphics↗