2010
Journal article
Open Access
Climate change assessment for Mediterranean agricultural areas by statistical downscaling
Palatella L, Miglietta M M, Paradisi P, Lionello P
In this paper we produce projections of seasonal precipitation for four Mediterranean areas: Apulia region (Italy), Ebro river basin (Spain), Po valley (Italy) and An- talya province (Turkey). We performed the statistical down- scaling using Canonical Correlation Analysis (CCA) in two versions: in one case Principal Component Analysis (PCA) filter is applied only to predictor and in the other to both pre- dictor and predictand. After performing a validation test, CCA after PCA filter on both predictor and predictand has been chosen. Sea level pressure (SLP) is used as predictor. Downscaling has been carried out for the scenarios A2 and B2 on the basis of three GCM's: the CCCma-GCM2, the Csiro-MK2 and HadCM3. Three consecutive 30-year pe- riods have been considered. For Summer precipitation in Apulia region we also use the 500 hPa temperature (T500) as predictor, obtaining comparable results. Results show dif- ferent climate change signals in the four areas and confirm the need of an analysis that is capable of resolving internal differences within the Mediterranean region. The most ro- bust signal is the reduction of Summer precipitation in the Ebro river basin. Other significative results are the increase of precipitation over Apulia in Summer, the reduction over the Po-valley in Spring and Autumn and the increase over the Antalya province in Summer and Autumn.Source: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (PRINT), vol. 10 (issue 7), pp. 1647-1661
Palatella L, Miglietta M M, Paradisi P, Lionello P
In this paper we produce projections of seasonal precipitation for four Mediterranean areas: Apulia region (Italy), Ebro river basin (Spain), Po valley (Italy) and An- talya province (Turkey). We performed the statistical down- scaling using Canonical Correlation Analysis (CCA) in two versions: in one case Principal Component Analysis (PCA) filter is applied only to predictor and in the other to both pre- dictor and predictand. After performing a validation test, CCA after PCA filter on both predictor and predictand has been chosen. Sea level pressure (SLP) is used as predictor. Downscaling has been carried out for the scenarios A2 and B2 on the basis of three GCM's: the CCCma-GCM2, the Csiro-MK2 and HadCM3. Three consecutive 30-year pe- riods have been considered. For Summer precipitation in Apulia region we also use the 500 hPa temperature (T500) as predictor, obtaining comparable results. Results show dif- ferent climate change signals in the four areas and confirm the need of an analysis that is capable of resolving internal differences within the Mediterranean region. The most ro- bust signal is the reduction of Summer precipitation in the Ebro river basin. Other significative results are the increase of precipitation over Apulia in Summer, the reduction over the Po-valley in Spring and Autumn and the increase over the Antalya province in Summer and Autumn.Source: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (PRINT), vol. 10 (issue 7), pp. 1647-1661
2010
Journal article
Open Access
Complex intermittency blurred by noise: theory and application to neural dynamics
Allegrini P, Menicucci D, Bedini R, Gemignani A, Paradisi P
We propose a model for the passage between metastable states of mind dynamics. As changing points we use the rapid transition processes simultaneously detectable in EEG signals related to different cortical areas. Our model consists of a non-Poissonian intermittent process, which signals that the brain is in a condition of complexity, upon which a Poisson process is superimposed. We provide an analytical solution for the waiting- time distribution for the model, which is well obeyed by physiological data. Although the role of the Poisson process remains unexplained, the model is able to reproduce many behaviors reported in literature, although they seem contradictory.Source: PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR AND SOFT MATTER PHYSICS, vol. 82 (issue 1), pp. 015103-1-015103-4
DOI: 10.1103/physreve.82.015103
Metrics:
Allegrini P, Menicucci D, Bedini R, Gemignani A, Paradisi P
We propose a model for the passage between metastable states of mind dynamics. As changing points we use the rapid transition processes simultaneously detectable in EEG signals related to different cortical areas. Our model consists of a non-Poissonian intermittent process, which signals that the brain is in a condition of complexity, upon which a Poisson process is superimposed. We provide an analytical solution for the waiting- time distribution for the model, which is well obeyed by physiological data. Although the role of the Poisson process remains unexplained, the model is able to reproduce many behaviors reported in literature, although they seem contradictory.Source: PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR AND SOFT MATTER PHYSICS, vol. 82 (issue 1), pp. 015103-1-015103-4
DOI: 10.1103/physreve.82.015103
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| CNR IRIS
2010
Journal article
Restricted
Detection limit of biomarkers using the near-infrared band-gap fluorescence of single-walled carbon nanotubes
D' Acunto M, Colantonio S, Moroni D, Salvetti O
Progress is being made in the development of microanalytical systems for biosensing. Because the sensor signal-to-noise ratio increases with decreasing size for many devices, considerable effort to fabricate small sensors is going to be addressed. Due to their hollow cylindrical structure, carbon nanotubes (CNTs) are considered very promising for many potential nano-device applications. Fluorescence microscopy in the near-infrared (NIR) between 950 and 1600nm has been developed as a novel method to image and study single-walled carbon nanotubes (SWNTs) in a variety of environments. Recently, hybridisation of DNA using NIR band-gap fluorescence has been experimentally demonstrated. We describe a numerical simulation, where the fluorescence shift energy is connected to exciton density variation when the molecular recognition is located on the SWNT immersed in a physiological solution.Source: JOURNAL OF MODERN OPTICS (PRINT), vol. 57 (issue 18), pp. 1695-1699
DOI: 10.1080/09500341003658170
Metrics:
D' Acunto M, Colantonio S, Moroni D, Salvetti O
Progress is being made in the development of microanalytical systems for biosensing. Because the sensor signal-to-noise ratio increases with decreasing size for many devices, considerable effort to fabricate small sensors is going to be addressed. Due to their hollow cylindrical structure, carbon nanotubes (CNTs) are considered very promising for many potential nano-device applications. Fluorescence microscopy in the near-infrared (NIR) between 950 and 1600nm has been developed as a novel method to image and study single-walled carbon nanotubes (SWNTs) in a variety of environments. Recently, hybridisation of DNA using NIR band-gap fluorescence has been experimentally demonstrated. We describe a numerical simulation, where the fluorescence shift energy is connected to exciton density variation when the molecular recognition is located on the SWNT immersed in a physiological solution.Source: JOURNAL OF MODERN OPTICS (PRINT), vol. 57 (issue 18), pp. 1695-1699
DOI: 10.1080/09500341003658170
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Journal of Modern Optics | CNR IRIS | CNR IRIS | www.informaworld.com
2010
Contribution to journal
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Computer technology for the quantification of pericardial fat assessed through cardiac CT
Coppini G, Favilla R, Moroni D, Pieri G, Schlueter M, Bianchi M, Coceani M, Mazzarisi A, Salvetti O, Marraccini P
Pericardial fat is associated with the extent of coronary artery disease (CAD) and with cardiovascular mortality. The aim of the study was to develop a computer software for the detection and measurement of pericardial fat in patients with suspected CAD. Methods: A dedicated software was developed to quantify pericardial fat from standard calcium score scans (acquisition triggered at 70% of the R-R interval, image reconstruction with a slice thickness of 2.5 mm without overlap). The procedure is based on the following phases: 1) A trace of the pericardial boundary in two orthogonal long-axis slices of the heart is performed by the operator. 2) An initial and approximate representation of the pericardial surface is generated. 3) The pericardial fat is then segmented by applying a Level Set method; 4) The ventricular region is defined by recognizing the atrioventricular groove and split in two by the interventricular groove. 5) If necessary, further manual editing of the pericardial boundary can be carried out. The method output provides the total volume of pericardial fat, as well as the regional distribution of fat in the right and left ventricles. Results: To test the performance of the software, we used scans from a set of 22 patients (63±8 years, 64% male, body mass index [BMI] 27.4±5.2 kg/m2) referred to our Institute for suspected CAD and undergoing cardiac CT. The average time needed to complete the analysis of pericardial fat was less than five minutes. In our patient sample, we observed a total pericardial volume of 95.7±32.1 mm3, which was divided unevenly between the right (59.4±28.3 mm3) and left (38.9±12.6 mm3) ventricles. Conclusions: Pericardial fat volume may be assessed non-invasively through cardiac CT, without leading to increased radiological exposure and post-processing times. The use of a computer software, such as the one tested in the present study, permits a systematic evaluation of epicardial fat that may prove useful for the risk sSource: EUROPEAN HEART JOURNAL, vol. 31 (issue 41), p. 436
Coppini G, Favilla R, Moroni D, Pieri G, Schlueter M, Bianchi M, Coceani M, Mazzarisi A, Salvetti O, Marraccini P
Pericardial fat is associated with the extent of coronary artery disease (CAD) and with cardiovascular mortality. The aim of the study was to develop a computer software for the detection and measurement of pericardial fat in patients with suspected CAD. Methods: A dedicated software was developed to quantify pericardial fat from standard calcium score scans (acquisition triggered at 70% of the R-R interval, image reconstruction with a slice thickness of 2.5 mm without overlap). The procedure is based on the following phases: 1) A trace of the pericardial boundary in two orthogonal long-axis slices of the heart is performed by the operator. 2) An initial and approximate representation of the pericardial surface is generated. 3) The pericardial fat is then segmented by applying a Level Set method; 4) The ventricular region is defined by recognizing the atrioventricular groove and split in two by the interventricular groove. 5) If necessary, further manual editing of the pericardial boundary can be carried out. The method output provides the total volume of pericardial fat, as well as the regional distribution of fat in the right and left ventricles. Results: To test the performance of the software, we used scans from a set of 22 patients (63±8 years, 64% male, body mass index [BMI] 27.4±5.2 kg/m2) referred to our Institute for suspected CAD and undergoing cardiac CT. The average time needed to complete the analysis of pericardial fat was less than five minutes. In our patient sample, we observed a total pericardial volume of 95.7±32.1 mm3, which was divided unevenly between the right (59.4±28.3 mm3) and left (38.9±12.6 mm3) ventricles. Conclusions: Pericardial fat volume may be assessed non-invasively through cardiac CT, without leading to increased radiological exposure and post-processing times. The use of a computer software, such as the one tested in the present study, permits a systematic evaluation of epicardial fat that may prove useful for the risk sSource: EUROPEAN HEART JOURNAL, vol. 31 (issue 41), p. 436
2010
Conference article
Restricted
Separating reflections from a single image using spatial smoothness and structure information
Yan Q, Kuruoglu E E, Yang X, Xu Y, Kayabol K
We adopt two priors to realize reflection separation from a single image, namely spatial smoothness, which is based on pixels' color dependency, and structure difference, which is got from different source images (transmitted image and reflected image) and different color channels of the same image. By analysing the optical model of reflection, we simplify the mixing matrix further and realize the method for getting spatially varying mixing coefficients. Based on the priors and using Gibbs sampling and appropriate probability density with Bayesian framework, our approach can achieve impressive results for many real world images that corrupted with reflections.DOI: 10.1007/978-3-642-15995-4_79
Metrics:
Yan Q, Kuruoglu E E, Yang X, Xu Y, Kayabol K
We adopt two priors to realize reflection separation from a single image, namely spatial smoothness, which is based on pixels' color dependency, and structure difference, which is got from different source images (transmitted image and reflected image) and different color channels of the same image. By analysing the optical model of reflection, we simplify the mixing matrix further and realize the method for getting spatially varying mixing coefficients. Based on the priors and using Gibbs sampling and appropriate probability density with Bayesian framework, our approach can achieve impressive results for many real world images that corrupted with reflections.DOI: 10.1007/978-3-642-15995-4_79
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doi.org | CNR IRIS | CNR IRIS | www.springerlink.com
2010
Book
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Advanced Infrared Technology and Applications
Abbozzo Ronchi L, Carlomagno G M, Corsi C, Grinzato E, Pippi I, Salvetti O
This special issue of the Journal of Modern Optics contains extended versions of selected papers accepted and presented at the 10th International Workshop on Advanced Infrared Technology and Applications held on 8-11 September 2009 at the Astronomy and Space Science Department of the University of Florence, Italy. The workshop - an event in a biennial series of meetings that started in 1991, and organised by Fondazione 'Giorgio Ronchi' (Florence), the Institutes of Information Science and Technologies 'Alessandro Faedo' (Pisa), Construction Technologies (Padova), Applied Physics 'Nello Carrara' (Florence) of the Italian National Research Council and the CREO Consortium, L'Aquila - constitutes a forum for bringing together academic and industrial researchers to exchange knowledge, ideas and experiences in the field of infrared (IR) science and technology. The main topics of the workshop included, in particular, advanced technology and materials, smart and fibre-optic sensors, aerospace and industrial applications, astronomy and earth monitoring, nondestructive tests and evaluation, systems for cultural heritage, near-, mid-, and long-wavelength systems, and image processing and data analysis. This special issue includes 17 papers that discuss scientific and technological aspects related to a few of these areas.Source: JOURNAL OF MODERN OPTICS (PRINT), pp. 1661-1662
DOI: 10.1080/09500340.2010.527708
Metrics:
Abbozzo Ronchi L, Carlomagno G M, Corsi C, Grinzato E, Pippi I, Salvetti O
This special issue of the Journal of Modern Optics contains extended versions of selected papers accepted and presented at the 10th International Workshop on Advanced Infrared Technology and Applications held on 8-11 September 2009 at the Astronomy and Space Science Department of the University of Florence, Italy. The workshop - an event in a biennial series of meetings that started in 1991, and organised by Fondazione 'Giorgio Ronchi' (Florence), the Institutes of Information Science and Technologies 'Alessandro Faedo' (Pisa), Construction Technologies (Padova), Applied Physics 'Nello Carrara' (Florence) of the Italian National Research Council and the CREO Consortium, L'Aquila - constitutes a forum for bringing together academic and industrial researchers to exchange knowledge, ideas and experiences in the field of infrared (IR) science and technology. The main topics of the workshop included, in particular, advanced technology and materials, smart and fibre-optic sensors, aerospace and industrial applications, astronomy and earth monitoring, nondestructive tests and evaluation, systems for cultural heritage, near-, mid-, and long-wavelength systems, and image processing and data analysis. This special issue includes 17 papers that discuss scientific and technological aspects related to a few of these areas.Source: JOURNAL OF MODERN OPTICS (PRINT), pp. 1661-1662
DOI: 10.1080/09500340.2010.527708
Metrics:
2010
Journal article
Open Access
Surface growth processes induced by AFM debris production. A continuum picture
D' Acunto M
Recent ultra-high vacuum (UHV) scratching atomic force microscopy (AFM) experiments showed the formation of small clusters, larger aggregates or regular patterns on the surface being scanned. In this paper, we suggest a theory that should capture the basic mechanisms that produce the formation of such structures. Such cluster structures, generally self-organized in regular structures, are mainly produced by the flux of adatoms generated by the AFM tip stripping off adatoms during the continuous passage of the probe tip on the surface being analysed. We assume that surface diffusion is the dominant transport mechanism of mass and a nonequilibrium thermodynamics framework for the self-organized growth process is developed. The accurate knowledge of such growth structures is important for two main reasons: it is possible to have an indirect measurement of the incidence of the wear basic mechanisms involved during the AFM scratching test while analysing the structures generated and the patterned structures produced could be used as a base (precursor factor) for mature surface growth processes. Despite granular structure of atom-by-atom nature of the debris, our theory uses a continuum approach for the description of the surface growth induced during the wearing passage of the probe tip.Source: PHYSICA. B, CONDENSED MATTER, vol. 405 (issue 2), pp. 793-801
DOI: 10.1016/j.physb.2009.10.003
Metrics:
D' Acunto M
Recent ultra-high vacuum (UHV) scratching atomic force microscopy (AFM) experiments showed the formation of small clusters, larger aggregates or regular patterns on the surface being scanned. In this paper, we suggest a theory that should capture the basic mechanisms that produce the formation of such structures. Such cluster structures, generally self-organized in regular structures, are mainly produced by the flux of adatoms generated by the AFM tip stripping off adatoms during the continuous passage of the probe tip on the surface being analysed. We assume that surface diffusion is the dominant transport mechanism of mass and a nonequilibrium thermodynamics framework for the self-organized growth process is developed. The accurate knowledge of such growth structures is important for two main reasons: it is possible to have an indirect measurement of the incidence of the wear basic mechanisms involved during the AFM scratching test while analysing the structures generated and the patterned structures produced could be used as a base (precursor factor) for mature surface growth processes. Despite granular structure of atom-by-atom nature of the debris, our theory uses a continuum approach for the description of the surface growth induced during the wearing passage of the probe tip.Source: PHYSICA. B, CONDENSED MATTER, vol. 405 (issue 2), pp. 793-801
DOI: 10.1016/j.physb.2009.10.003
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CNR IRIS | www.sciencedirect.com | Physica B Condensed Matter | CNR IRIS | CNR IRIS
2010
Conference article
Restricted
Dependent component analysis for cosmology: a case study
Kuruoglu E E
In this paper, we discuss various dependent component analysis approaches available in the literature and study their performances on the problem of separation of dependent cosmological sources from multichannel microwave radiation maps of the sky. Realisticaly simulated cosmological radiation maps are utilised in the simulations which demonstrate the superior performance obtained by tree-dependent component analysis and correlated component analysis methods when compared to classical ICA.DOI: 10.1007/978-3-642-15995-4_67
Metrics:
Kuruoglu E E
In this paper, we discuss various dependent component analysis approaches available in the literature and study their performances on the problem of separation of dependent cosmological sources from multichannel microwave radiation maps of the sky. Realisticaly simulated cosmological radiation maps are utilised in the simulations which demonstrate the superior performance obtained by tree-dependent component analysis and correlated component analysis methods when compared to classical ICA.DOI: 10.1007/978-3-642-15995-4_67
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doi.org | CNR IRIS | CNR IRIS | www.springerlink.com
2010
Journal article
Restricted
Modelling with mixture of symmetric stable distributions using Gibbs sampling
Salasgonzalez D, Kuruoglu E E, Ruiz D P
The stable distribution is a very useful tool to model impulsive data. In this work, a fully Bayesian mixture of symmetric stable distribution model is presented. Despite the non-existence of closed form for alpha-stable distributions, the use of the product property makes it possible to infer on parameters using a straight forward Gibbs sampling. This model is compared to the mixture of Gaussians model. Our proposed methodology is proved to be more robust to outliers than the mixture of Gaussians. Therefore, it is suitable to model mixture of impulsive data. Moreover, as Gaussian is a particular case of the alpha-stable distribution, the proposed model is a generalization of mixture of Gaussians. Mixture of symmetric alpha-stable is intensively tested on both simulated and real data.Source: SIGNAL PROCESSING, vol. 90 (issue 3), pp. 774-783
DOI: 10.1016/j.sigpro.2009.07.003
Metrics:
Salasgonzalez D, Kuruoglu E E, Ruiz D P
The stable distribution is a very useful tool to model impulsive data. In this work, a fully Bayesian mixture of symmetric stable distribution model is presented. Despite the non-existence of closed form for alpha-stable distributions, the use of the product property makes it possible to infer on parameters using a straight forward Gibbs sampling. This model is compared to the mixture of Gaussians model. Our proposed methodology is proved to be more robust to outliers than the mixture of Gaussians. Therefore, it is suitable to model mixture of impulsive data. Moreover, as Gaussian is a particular case of the alpha-stable distribution, the proposed model is a generalization of mixture of Gaussians. Mixture of symmetric alpha-stable is intensively tested on both simulated and real data.Source: SIGNAL PROCESSING, vol. 90 (issue 3), pp. 774-783
DOI: 10.1016/j.sigpro.2009.07.003
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Signal Processing | CNR IRIS | CNR IRIS
2010
Journal article
Open Access
Modeling non-Gaussian time-varying vector autoregressive processes by particle filtering
Gencaga D, Kuruoglu E E, Ertuzun A
We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical processes, mobile communication channels and biomedical signals. In the literature, most work utilize multivariate Gaussian models for the mentioned applications, mainly due to the lack of efficient analytical tools for modeling with non-Gaussian distributions. In this paper, we propose a particle filtering approach which can model non-Gaussian autoregressive processes having cross-correlations among them. Moreover, time-varying parameters of the process can be modeled as the most general case by using this sequential Bayesian estimation method. Simulation results justify the performance of the proposed technique, which potentially can model also Gaussian processes as a sub-case.Source: MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING, vol. 21 (issue 1), pp. 73-85
DOI: 10.1007/s11045-009-0081-8
Metrics:
Gencaga D, Kuruoglu E E, Ertuzun A
We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical processes, mobile communication channels and biomedical signals. In the literature, most work utilize multivariate Gaussian models for the mentioned applications, mainly due to the lack of efficient analytical tools for modeling with non-Gaussian distributions. In this paper, we propose a particle filtering approach which can model non-Gaussian autoregressive processes having cross-correlations among them. Moreover, time-varying parameters of the process can be modeled as the most general case by using this sequential Bayesian estimation method. Simulation results justify the performance of the proposed technique, which potentially can model also Gaussian processes as a sub-case.Source: MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING, vol. 21 (issue 1), pp. 73-85
DOI: 10.1007/s11045-009-0081-8
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Aperta - TÜBİTAK Açık Arşivi | Multidimensional Systems and Signal Processing | CNR IRIS | CNR IRIS | www.springerlink.com
2010
Journal article
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Multichannel blind separation and deconvolution of images for document analysis
Tonazzini A, Gerace I, Martinelli F
In this paper we apply Bayesian blind source separation (BSS) from noisy convolutive mixtures to jointly separate and restore source images degraded through unknown blur operators, and then linearly mixed. We found that this problem arises in several image processing applications, among which there are some interesting instances of degraded document analysis. In particular, the convolutive mixture model is proposed for describing multiple views of documents affected by the overlapping of two or more text patterns. We consider two different models, the interchannel model, where the data represent multispectral views of a single-sided document, and the intrachannel model, where the data are given by two sets of multispectral views of the recto and verso side of a document page. In both cases, the aim of the analysis is to recover clean maps of the main foreground text, but also the enhancement and extraction of other document features, such as faint or masked patterns. We adopt Bayesian estimation for all the unknowns, and describe the typical local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. This a priori information is particularly suitable for the kind of objects depicted in the images treated, i.e. homogeneous texts in homogeneous background, and, as such, is capable to stabilize the ill-posed, inverse problem considered. The method is validated through numerical and real experiments that are representative of various real scenarios.Source: IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 19 (issue 4), pp. 912-925
DOI: 10.1109/tip.2009.2038814
Metrics:
Tonazzini A, Gerace I, Martinelli F
In this paper we apply Bayesian blind source separation (BSS) from noisy convolutive mixtures to jointly separate and restore source images degraded through unknown blur operators, and then linearly mixed. We found that this problem arises in several image processing applications, among which there are some interesting instances of degraded document analysis. In particular, the convolutive mixture model is proposed for describing multiple views of documents affected by the overlapping of two or more text patterns. We consider two different models, the interchannel model, where the data represent multispectral views of a single-sided document, and the intrachannel model, where the data are given by two sets of multispectral views of the recto and verso side of a document page. In both cases, the aim of the analysis is to recover clean maps of the main foreground text, but also the enhancement and extraction of other document features, such as faint or masked patterns. We adopt Bayesian estimation for all the unknowns, and describe the typical local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. This a priori information is particularly suitable for the kind of objects depicted in the images treated, i.e. homogeneous texts in homogeneous background, and, as such, is capable to stabilize the ill-posed, inverse problem considered. The method is validated through numerical and real experiments that are representative of various real scenarios.Source: IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 19 (issue 4), pp. 912-925
DOI: 10.1109/tip.2009.2038814
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IEEE Transactions on Image Processing | CNR IRIS | CNR IRIS
2010
Journal article
Restricted
Preliminary description of a self-similarity phenomenon in the connection patterns of dreams
Barcaro U, Rizzi P
The objective of the research was to recognize and describe a phenomenon of self-similarity in dreams, specifically in the connection patterns of dreams: These patterns were obtained by means of a linguistic analysis of data including dream reports and associations provided by the dreamer. Dreams of four patients in therapy, three for each patient, were considered. It was found that a well-defined pattern (Basic Pattern) existed at three levels: links among dream sources of a dream, connections among source clusters of a dream, and connections among different dreams of a same patient. This self-similarity pattern was meaningfully interpretable at all the three levels. Considering the small number of patients, the description and interpretation of the results should be viewed as only preliminary. However, a minimum value for the occurrence frequency of the observed phenomenon can be given with good statistical significance.Source: DREAMING, vol. 20 (issue 2), pp. 136-148
DOI: 10.1037/a0019241
Metrics:
Barcaro U, Rizzi P
The objective of the research was to recognize and describe a phenomenon of self-similarity in dreams, specifically in the connection patterns of dreams: These patterns were obtained by means of a linguistic analysis of data including dream reports and associations provided by the dreamer. Dreams of four patients in therapy, three for each patient, were considered. It was found that a well-defined pattern (Basic Pattern) existed at three levels: links among dream sources of a dream, connections among source clusters of a dream, and connections among different dreams of a same patient. This self-similarity pattern was meaningfully interpretable at all the three levels. Considering the small number of patients, the description and interpretation of the results should be viewed as only preliminary. However, a minimum value for the occurrence frequency of the observed phenomenon can be given with good statistical significance.Source: DREAMING, vol. 20 (issue 2), pp. 136-148
DOI: 10.1037/a0019241
Metrics:
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Dreaming | CNR IRIS | CNR IRIS | psycnet.apa.org
2010
Journal article
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Bayesian source separation for cosmology [Estimating cosmological components]
Kuruoglu E E
Recent satellite missions have provided and continue to provide us with vast amounts of data on radiation measurements that generally present themselves as superpositions of various cosmological sources, most importantly cosmic microwave background (CMB) radiation and other galactic and extragalactic sources. We would like to obtain the estimates of these sources separately since they carry vital information of cosmological significance about our Universe. Although initial attempts to obtain sources have utilized blind estimation techniques, the presence of important astrophysical prior information and the demanding nature of the problem makes the use of informed techniques possible and indispensable. In this article, our objective is to present a formulation of the problem in Bayesian framework for the signal processing community and to provide a panorama of Bayesian source separation techniques for the estimation of cosmological components from the observation mixtures.Source: IEEE SIGNAL PROCESSING MAGAZINE, vol. 27 (issue 1), pp. 43-54
DOI: 10.1109/msp.2009.934718
Metrics:
Kuruoglu E E
Recent satellite missions have provided and continue to provide us with vast amounts of data on radiation measurements that generally present themselves as superpositions of various cosmological sources, most importantly cosmic microwave background (CMB) radiation and other galactic and extragalactic sources. We would like to obtain the estimates of these sources separately since they carry vital information of cosmological significance about our Universe. Although initial attempts to obtain sources have utilized blind estimation techniques, the presence of important astrophysical prior information and the demanding nature of the problem makes the use of informed techniques possible and indispensable. In this article, our objective is to present a formulation of the problem in Bayesian framework for the signal processing community and to provide a panorama of Bayesian source separation techniques for the estimation of cosmological components from the observation mixtures.Source: IEEE SIGNAL PROCESSING MAGAZINE, vol. 27 (issue 1), pp. 43-54
DOI: 10.1109/msp.2009.934718
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IEEE Signal Processing Magazine | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2010
Journal article
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Decision support in heart failure through processing of electro- and echocardiograms
Chiarugi F, Colantonio S, Emmanouilidou D, Martinelli M, Moroni D, Salvetti O
Objective: Signal and imaging investigations are currently key components in the diagnosis, prognosis and follow up of heart diseases. Nowadays, the need for more efficient, cost-effective and personalised care has led to a renaissance of clinical decision support systems (CDSSs). The purpose of this paper is to present an effective way of achieving a high-level integration of signal and image processing methods in the general process of care, by means of a clinical decision support system, and to discuss the advantages of such an approach. From the wide range of heart diseases, heart failure, whose complexity best highlights the benefits of this integration, has been selected. Methods: After an analysis of users' needs and expectations, significant and suitably designed image and signal processing algorithms are introduced to objectively and reliably evaluate important features involved in decisional problems in the heart failure domain. Then, a CDSS is conceived so as to combine the domain knowledge with advanced analytical tools for data processing. In particular, the relevant and significant medical knowledge and experts' knowhow are formalised according to an ontological formalism, suitably augmented with a base of rules for inferential reasoning. Results: The proposed methods were tested and evaluated in the daily practice of the physicians operating at the Department of Cardiology, University Magna Graecia, Catanzaro, Italy, on a population of 79 patients. Different scenarios, involving decisional problems based on the analysis of biomedical signals and images, were considered. In these scenarios, after some training and 3 months of use, the CDSS was able to provide important and useful suggestions in routine workflows, by integrating the clinical parameters computed through the developed methods for echocardiographic image segmentation and the algorithms for electrocardiography processing. Conclusions: The CDSS allows the integration of signal and image procSource: ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 50, pp. 95-104
DOI: 10.1016/j.artmed.2010.05.001
Metrics:
Chiarugi F, Colantonio S, Emmanouilidou D, Martinelli M, Moroni D, Salvetti O
Objective: Signal and imaging investigations are currently key components in the diagnosis, prognosis and follow up of heart diseases. Nowadays, the need for more efficient, cost-effective and personalised care has led to a renaissance of clinical decision support systems (CDSSs). The purpose of this paper is to present an effective way of achieving a high-level integration of signal and image processing methods in the general process of care, by means of a clinical decision support system, and to discuss the advantages of such an approach. From the wide range of heart diseases, heart failure, whose complexity best highlights the benefits of this integration, has been selected. Methods: After an analysis of users' needs and expectations, significant and suitably designed image and signal processing algorithms are introduced to objectively and reliably evaluate important features involved in decisional problems in the heart failure domain. Then, a CDSS is conceived so as to combine the domain knowledge with advanced analytical tools for data processing. In particular, the relevant and significant medical knowledge and experts' knowhow are formalised according to an ontological formalism, suitably augmented with a base of rules for inferential reasoning. Results: The proposed methods were tested and evaluated in the daily practice of the physicians operating at the Department of Cardiology, University Magna Graecia, Catanzaro, Italy, on a population of 79 patients. Different scenarios, involving decisional problems based on the analysis of biomedical signals and images, were considered. In these scenarios, after some training and 3 months of use, the CDSS was able to provide important and useful suggestions in routine workflows, by integrating the clinical parameters computed through the developed methods for echocardiographic image segmentation and the algorithms for electrocardiography processing. Conclusions: The CDSS allows the integration of signal and image procSource: ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 50, pp. 95-104
DOI: 10.1016/j.artmed.2010.05.001
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Artificial Intelligence in Medicine | CNR IRIS | CNR IRIS | www.sciencedirect.com
2010
Book
Restricted
Astronomy and cosmology
Leshem A, Kamalabadi F, Kuruoglu E E, Van Der Veen A
Special issue on Astronomy and cosmologyDOI: 10.1109/msp.2009.934928
Metrics:
Leshem A, Kamalabadi F, Kuruoglu E E, Van Der Veen A
Special issue on Astronomy and cosmologyDOI: 10.1109/msp.2009.934928
Metrics:
See at:
IEEE Signal Processing Magazine | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2010
Conference article
Restricted
Non-stationary t-distribution prior for image source separation from blurred observations
Kayabol K, Kuruoglu E E
We propose a non-stationary spatial image model for blind image separation problem. Our model is defined on first order image differentials. We model the image differentials using t-distribution with space varying scale parameters. This prior image model has been used in the Bayesian formulation and the image source are estimated using a Langevin sampler method. We have tested the proposed model on astrophysical image mixtures and obtained better results regarding to stationary model.DOI: 10.1007/978-3-642-15995-4_63
Metrics:
Kayabol K, Kuruoglu E E
We propose a non-stationary spatial image model for blind image separation problem. Our model is defined on first order image differentials. We model the image differentials using t-distribution with space varying scale parameters. This prior image model has been used in the Bayesian formulation and the image source are estimated using a Langevin sampler method. We have tested the proposed model on astrophysical image mixtures and obtained better results regarding to stationary model.DOI: 10.1007/978-3-642-15995-4_63
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doi.org | CNR IRIS | CNR IRIS | www.springerlink.com
2010
Journal article
Open Access
Correlated component analysis for diffuse component separation with error estimation on simulated Planck polarization data
Ricciardi S, Bonaldi A, Natoli P, Polenta G, Baccigalupi C, Salerno E, Kayabol K, Bedini L, De Zotti G
We present a data analysis pipeline for cosmic microwave background (CMB) polarization experiments, running from multifrequency maps to the power spectra. We focus mainly on component separation and, for the first time, we work out the covariance matrix accounting for errors associated with the separation itself. This allows us to propagate such errors and evaluate their contributions to the uncertainties on the final products. The pipeline is optimized for intermediate and small scales, but could be easily extended to lower multipoles.We exploit realistic simulations of the sky, tailored for the Planck mission. The component separation is achieved by exploiting the correlated component analysis in the harmonic domain, which we demonstrate to be superior to the real-space application.We present two techniques to estimate the uncertainties on the spectral parameters of the separated components. The component separation errors are then propagated by means of Monte Carlo simulations to obtain the corresponding contributions to uncertainties on the component maps and on the CMB power spectra. For the Planck polarization case they are found to be subdominant compared to noise.Source: MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (PRINT), vol. 406 (issue 3), pp. 1644-1658
DOI: 10.1111/j.1365-2966.2010.16819.x
Metrics:
Ricciardi S, Bonaldi A, Natoli P, Polenta G, Baccigalupi C, Salerno E, Kayabol K, Bedini L, De Zotti G
We present a data analysis pipeline for cosmic microwave background (CMB) polarization experiments, running from multifrequency maps to the power spectra. We focus mainly on component separation and, for the first time, we work out the covariance matrix accounting for errors associated with the separation itself. This allows us to propagate such errors and evaluate their contributions to the uncertainties on the final products. The pipeline is optimized for intermediate and small scales, but could be easily extended to lower multipoles.We exploit realistic simulations of the sky, tailored for the Planck mission. The component separation is achieved by exploiting the correlated component analysis in the harmonic domain, which we demonstrate to be superior to the real-space application.We present two techniques to estimate the uncertainties on the spectral parameters of the separated components. The component separation errors are then propagated by means of Monte Carlo simulations to obtain the corresponding contributions to uncertainties on the component maps and on the CMB power spectra. For the Planck polarization case they are found to be subdominant compared to noise.Source: MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (PRINT), vol. 406 (issue 3), pp. 1644-1658
DOI: 10.1111/j.1365-2966.2010.16819.x
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Monthly Notices of the Royal Astronomical Society | Monthly Notices of the Royal Astronomical Society | CNR IRIS | CNR IRIS
2010
Journal article
Restricted
The K(pi, 1) problem for the affine Artin group of type (B)over-tilde(n) and its cohomology
Callegaro F, Moroni D, Salvetti M
We prove that the complement to the affine complex arrangement of type (B) over tilde (n) is a K(pi, 1) space. We also compute the cohomology of the affine Artin group G (B) over tilde (n) ( of type (B) over tilde (n)) with coefficients in interesting local systems. In particular, we consider the module Q [q+/-1; t+/-1]; where the first n standard generators of G (B) over tilde (n) act by (-q)-multiplication while the last generator acts by (-t)-multiplication. Such a representation generalizes the analogous 1-parameter representation related to the bundle structure over the complement to the discriminant hypersurface, endowed with the monodromy action of the associated Milnor fibre. The cohomology of G (B) over tilde (n) with trivial coefficients is derived from the previous one.Source: JOURNAL OF THE EUROPEAN MATHEMATICAL SOCIETY, vol. 12, pp. 1-22
DOI: 10.471/jems/187
Metrics:
Callegaro F, Moroni D, Salvetti M
We prove that the complement to the affine complex arrangement of type (B) over tilde (n) is a K(pi, 1) space. We also compute the cohomology of the affine Artin group G (B) over tilde (n) ( of type (B) over tilde (n)) with coefficients in interesting local systems. In particular, we consider the module Q [q+/-1; t+/-1]; where the first n standard generators of G (B) over tilde (n) act by (-q)-multiplication while the last generator acts by (-t)-multiplication. Such a representation generalizes the analogous 1-parameter representation related to the bundle structure over the complement to the discriminant hypersurface, endowed with the monodromy action of the associated Milnor fibre. The cohomology of G (B) over tilde (n) with trivial coefficients is derived from the previous one.Source: JOURNAL OF THE EUROPEAN MATHEMATICAL SOCIETY, vol. 12, pp. 1-22
DOI: 10.471/jems/187
Metrics:
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CNR IRIS | CNR IRIS | www.ems-ph.org
2010
Journal article
Open Access
Adaptive langevin sampler for separation of t-distribution modelled astrophysical maps
Kayabol K, Kuruoglu E E, Sanz J L, Sankur B, Salerno E, Herranz D
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the astrophysical sources and describe the derivation details. In this scheme, we use the Langevin stochastic equation for transitions, which enables parallel drawing of random samples from the posterior, and reduces the computation time significantly (by two orders of magnitude). In addition, Student's t-distribution parameters are updated throughout the iterations. The results on astrophysical source separation are assessed with two performance criteria defined in the pixel and the frequency domains.Source: IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 19 (issue 9), pp. 2357-2368
DOI: 10.1109/tip.2010.2048613
DOI: 10.48550/arxiv.1101.1396
Metrics:
Kayabol K, Kuruoglu E E, Sanz J L, Sankur B, Salerno E, Herranz D
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the astrophysical sources and describe the derivation details. In this scheme, we use the Langevin stochastic equation for transitions, which enables parallel drawing of random samples from the posterior, and reduces the computation time significantly (by two orders of magnitude). In addition, Student's t-distribution parameters are updated throughout the iterations. The results on astrophysical source separation are assessed with two performance criteria defined in the pixel and the frequency domains.Source: IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 19 (issue 9), pp. 2357-2368
DOI: 10.1109/tip.2010.2048613
DOI: 10.48550/arxiv.1101.1396
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arXiv.org e-Print Archive | IEEE Transactions on Image Processing | IEEE Transactions on Image Processing | doi.org | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2010
Journal article
Open Access
Quantification of epicardial fat by cardiac CT imaging
Coppini G, Favilla R, Marraccini P, Moroni D, Pieri G
The aim of this work is to introduce and design image processing methods for the quantitative analysis of epicardial fat by using cardiac CT imaging. Indeed, epicardial fat has recently been shown to correlate with cardiovascular disease, cardiovascular risk factors and metabolic syndrome. However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements. In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring. In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues. In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat. In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation. In the second step, a variational formulation of level set methods - including a specially-designed region homogeneity energy based on Gaussian mixture models- is used to recover spatial coherence and smoothness of fat depots. Experimental results show that the introduced method may be efficiently used for the quantification of epicardial fat.Source: THE OPEN MEDICAL INFORMATICS JOURNAL, vol. 4, pp. 126-135
DOI: 10.2174/1874431101004010126
Metrics:
Coppini G, Favilla R, Marraccini P, Moroni D, Pieri G
The aim of this work is to introduce and design image processing methods for the quantitative analysis of epicardial fat by using cardiac CT imaging. Indeed, epicardial fat has recently been shown to correlate with cardiovascular disease, cardiovascular risk factors and metabolic syndrome. However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements. In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring. In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues. In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat. In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation. In the second step, a variational formulation of level set methods - including a specially-designed region homogeneity energy based on Gaussian mixture models- is used to recover spatial coherence and smoothness of fat depots. Experimental results show that the introduced method may be efficiently used for the quantification of epicardial fat.Source: THE OPEN MEDICAL INFORMATICS JOURNAL, vol. 4, pp. 126-135
DOI: 10.2174/1874431101004010126
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Open Medical Informatics Journal | Open Medical Informatics Journal | Open Medical Informatics Journal | CNR IRIS | CNR IRIS | www.ncbi.nlm.nih.gov