Search results for " Wavelet analysis"

showing 7 items of 7 documents

Differential diagnostic features of bone marrow biopsies in essential thrombocythemia

2004

Essential Thrombocythemia (ET) is a chronic myeloproliferative disorder (CMPD) characterized by a high platelet count and originating from a multipotent stem cell. For a long time, according to Polycythaemia Vera Study Group (PVSG) criteria, ET diagnosis has not included histopathological data. Bone Marrow (BM) histology was used only to exclude previous or other subtypes of Ph-CMD or Myelodysplastic syndromes (MDS). In addition, the lack of any cytogenetic or molecular-biological marker has made the discrimination between ET and cases of Reactive Thrombocytosys (RT) without a well known cause quite problematic. Analogously, the distinction of ET from the other Ph- CMPDs with similar clinic…

Classification essential thrombocythemia image segmentation wavelet analysis.Settore INF/01 - Informatica
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An approach based on wavelet analysis for feature extraction in the electroretinogram

2011

Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time–frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathol…

Electroretinogram a-Wave Photoreceptoral response Achromatopsia Wavelet analysisSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders

2008

This work describes an automatic method for discrimination in microphotographs between normal and pathological human megakaryocytes and between two kinds of disorders of these cells. A segmentation procedure has been developed, mainly based on mathematical morphology and wavelet transform, to isolate the cells. The features of each megakaryocyte (e.g. area, perimeter and tortuosity of the cell and its nucleus, and shape complexity via elliptic Fourier transform) are used by a regression tree procedure applied twice: the first time to find the set of normal megakaryocytes and the second to distinguish between the pathologies. The output of our classifier has been compared to the interpretati…

Decision treeReproducibility of ResultHealth InformaticsMathematical morphologySensitivity and SpecificityWavelet analysiPattern Recognition Automatedsymbols.namesakeWaveletMegakaryocyteMegakaryocyteArtificial IntelligenceImage Interpretation Computer-AssistedmedicineAnimalsHumansRadiology Nuclear Medicine and imagingComputer visionSegmentationMyeloproliferative DisorderCells Cultured1707MathematicsHealth InformaticMyeloproliferative DisordersSettore INF/01 - InformaticaRadiological and Ultrasound TechnologyAnimalbusiness.industryMorphometryReproducibility of ResultsWavelet transformPattern recognitionAutomatic classification; Elliptic Fourier transform; Morphometry; Wavelet analysis; Animals; Cells Cultured; Humans; Image Enhancement; Image Interpretation Computer-Assisted; Megakaryocytes; Myeloproliferative Disorders; Pattern Recognition Automated; Reproducibility of Results; Sensitivity and Specificity; Algorithms; Artificial Intelligence; Computer Graphics and Computer-Aided Design; 1707; Radiology Nuclear Medicine and Imaging; Health Informatics; Radiological and Ultrasound TechnologyImage EnhancementComputer Graphics and Computer-Aided DesignAlgorithmFourier transformmedicine.anatomical_structuresymbolsAutomatic classificationElliptic Fourier transformComputer Vision and Pattern RecognitionArtificial intelligencebusinessMegakaryocytesClassifier (UML)AlgorithmsHumanMedical Image Analysis
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The Decline in U.S. Output Growth Volatility: A Wavelet Analysis

2013

The aim of the paper is to determine whether or not the volatility of the growth rate of US output has changed in the period since late 1940's, and to attribute a precise date, if possible, to any such change. By applying the Discrete Wavelet Transform (DWT) to the annualized quarter-to quarter output growth series, we can test the homogeneity of the variance on a scale by scale basis without needing to fit a parametric model to the observed time series. A version of the Inclan and Tiao (1994) Normalised and Centered Cumulative Sum of Squares test, adapted to wavelet analysis, leads us to reject the null hypothesis of constant variance in the two levels of decomposition of the highest resol…

Volatility Growth Wavelet analysis Change-Point Detection NCCSS.Settore SECS-P/05 - Econometria
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ERG signal analysis using wavelet transform

2009

The wavelet analysis is a powerful tool for analyzing and detecting features of signals characterized by time-dependent statistical properties, as biomedical signals. The identification and the analysis of the components of these signals in the time-frequency domain, give meaningful information about the physiological mechanisms that govern them. This article presents the results of the wavelet analysis applied to the a-wave component of the human electroretinogram. In order to deepen and improve our knowledge about the behavior of the early photoreceptoral response, including the possible activation of interactions and correlations among the photoreceptors, we have detected and identified …

Statistics and ProbabilitySignal processingComputer scienceApplied MathematicsWavelet AnalysisMexican hat waveletWavelet transformLuminanceRetinaSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Electroretinogram – a-wave – Photoreceptoral response – Wavelet analysis – Mexican hat waveletRange (mathematics)Identification (information)WaveletOrder (biology)ElectroretinographyHumansPhotoreceptor CellsBiological systemPhotic StimulationEcology Evolution Behavior and SystematicsTheory in Biosciences
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Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement

2017

The screening of chromosomal defects, as trisomy 13, 18 and 21, can be obtained by the measurement of the nuchal translucency thickness scanning during the end of the first trimester of pregnancy. This contribution proposes an automatic methodology to detect mid-sagittal sections to identify the correct measurement of nuchal translucency. Wavelet analysis and neural network classifiers are the main strategies of the proposed methodology to detect the frontal components of the skull and the choroid plexus with the support of radial symmetry analysis. Real clinical ultrasound images were adopted to measure the performance and the robustness of the methodology, thus it can be highlighted an er…

Computer scienceSpeech recognition02 engineering and technologyWavelet analysi03 medical and health sciences0302 clinical medicineWaveletMid-sagittal section Neural network Nuchal translucency Symmetry transform Wavelet analysis.Nuchal translucencyRobustness (computer science)Nuchal Translucency Measurement0202 electrical engineering electronic engineering information engineeringmedicineMid-sagittal sectionSettore INF/01 - InformaticaArtificial neural networkbusiness.industrySymmetry transformPattern recognitionmedicine.diseaseNeural networkSagittal planemedicine.anatomical_structureNuchal translucencyMorphological analysis020201 artificial intelligence & image processingArtificial intelligenceTrisomybusiness030217 neurology & neurosurgery
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Spectral Structures in Econometrics: Modern Techniques in Wavelet Analysis and Band Limited Estimation

2007

This thesis presents a number of innovative techniques that can be used in the analysis of econometric data sequences in which the underlying components can be identified by their spectral signatures. To present these techniques intelligibly requires the preparatory expositions of Fourier analysis and of the theory of linear filtering that are presented in Chapters 2 and 3. Amongst the techniques for extracting components from short non stationary sequences that are described in Chapter 3 is a variant of the Hodrick--Prescott filter with a smoothing parameter that varies locally. This enables us to extract from the data trends that incorporate a number of structural breaks. The inadequacy o…

Band-limited estimation wavelet analysis Fourier analysisbusiness cycle output growth volatility.Settore SECS-P/05 - Econometria
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