Suitable classification of mortars from ancient roman and renaissance frescoes using thermal analysis and chemometrics

Background Literature on mortars has mainly focused on the identification and characterization of their components in order to assign them to a specific historical period, after accurate classification. For this purpose, different analytical techniques have been proposed. Aim of the present study was to verify whether the combination of thermal analysis and chemometric methods could be used to obtain a fast but correct classification of ancient mortar samples of different ages (Roman era and Renaissance). Results Ancient Roman frescoes from Museo Nazionale Romano (Terme di Diocleziano, Rome, Italy) and Renaissance frescoes from Sistine Chapel and Old Vatican Rooms (Vatican City) were analyzed by thermogravimetry (TG) and differential thermal analysis (DTA). Principal Component analysis (PCA) on the main thermal data evidenced the presence of two clusters, ascribable to the two different ages. Inspection of the loadings allowed to interpret the observed differences in terms of the experimental variables. Conclusions PCA allowed differentiating the two kinds of mortars (Roman and Renaissance frescoes), and evidenced how the ancient Roman samples are richer in binder (calcium carbonate) and contain less filler (aggregate) than the Renaissance ones. It was also demonstrated how the coupling of thermoanalytical techniques and chemometric processing proves to be particularly advantageous when a rapid and correct differentiation and classification of cultural heritage samples of various kinds or ages has to be carried out

Automatic Characterization of Myocardial Perfusion in Contrast Enhanced MRI

The use of contrast medium in cardiac MRI allows joining the high-resolution anatomical information provided by standard magnetic resonance with functional information obtained by means of the perfusion of contrast agent in myocardial tissues. The current approach to perfusion MRI characterization is the qualitative one, based on visual inspection of images. Moving to quantitative analysis requires extraction of numerical indices of myocardium perfusion by analysis of time/intensity curves related to the area of interest. The main problem in quantitative image sequence analysis is the heart movement, mainly due to patient respiration. We propose an automatic procedure based on image registration, segmentation of the myocardium, and extraction and analysis of time/intensity curves. The procedure requires a minimal user interaction, is robust with respect to the user input, and allows effective characterization of myocardial perfusion. The algorithm was tested on cardiac MR images acquired from voluntaries and in clinical routine

A fast and accurate simulator for the design of birdcage coils in MRI

The birdcage coils are extensively used in MRI systems since they introduce a high signal to noise ratio and a high radiofrequency magnetic field homogeneity that guarantee a large field of view. The present article describes the implementation of a birdcage coil simulator, operating in high-pass and low-pass modes, using magnetostatic analysis of the coil. Respect to other simulators described in literature, our simulator allows to obtain in short time not only the dominant frequency mode, but also the complete resonant frequency spectrum and the relevant magnetic field pattern with high accuracy. Our simulator accounts for all the inductances including the mutual inductances between conductors. Moreover, the inductance calculation includes an accurately birdcage geometry description and the effect of a radiofrequency shield. The knowledge of all the resonance modes introduced by a birdcage coil is twofold useful during birdcage coil design: - higher order modes should be pushed far from the fundamental one, - for particular applications, it is necessary to localize other resonant modes (as the Helmholtz mode) jointly to the dominant mode. The knowledge of the magnetic field pattern allows to a priori verify the field homogeneity created inside the coil, when varying the coil dimension and mainly the number of the coil legs. The coil is analyzed using equivalent circuit method. Finally, the simulator is validated by implementing a low-pass birdcage coil and comparing our data with the literature

Correction to: Measured PET Data Characterization with the Negative Binomial Distribution Model

The article "Measured PET Data Characterization with the Negative Binomial Distribution Model", written by Maria Filomena Santarelli, Vincenzo Positano, Luigi Landini was originally published Online First without open access. After publication in volume [37], issue [3], page [299-312] the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to © The Author(s) [2018] and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made

Automatic PET-CT Image Registration Method Based on Mutual Information and Genetic Algorithms

Hybrid PET/CT scanners can simultaneously visualize coronary artery disease as revealed by computed tomography (CT) and myocardial perfusion as measured by positron emission tomography (PET). Manual registration is usually required in clinical practice to compensate spatial mismatch between datasets. In this paper, we present a registration algorithm that is able to automatically align PET/CT cardiac images. The algorithm bases on mutual information (MI) as registration metric and on genetic algorithm as optimization method. A multiresolution approach was used to optimize the processing time. The algorithm was tested on computerized models of volumetric PET/CT cardiac data and on real PET/CT datasets. The proposed automatic registration algorithm smoothes the pattern of the MI and allows it to reach the global maximum of the similarity function. The implemented method also allows the definition of the correct spatial transformation that matches both synthetic and real PET and CT volumetric datasets

The influence of noise in dynamic PET direct reconstruction

In the present work a study is carried out in order to assess the efficiency of the direct reconstruction algorithms on noisy dynamic PET data. The study is performed via Monte Carlo simulations of a uniform cylindrical phantom whose emission values change in time according to a kinetic law. After generating the relevant projection data and properly adding the effects of different noise sources on them, the direct reconstruction and parametric estimation algorithm is applied. The resulting kinetic parameters and reconstructed images are then quantitatively evaluated with appropriate indexes. The simulation is repeated considering different sources of noise and different values of them. The results obtained allow us to affirm that the direct reconstruction algorithm tested maintains a good efficiency also in presence of noise

Philippus Positanus dei, et apostolicae sedis gratia episcopus Calvensis ... Expectantibus (I) vobis beatam spem, & adventum Magni Dei ..

1 manifesto : 1 stemma ; 48 cm Data di emanzione in calce: 22. decembris 1720 Data di stampa presunta: 1720 (emanazione) In testa stemma vescovile xilogr Iniziale xilogr

Technological innovations in magnetic resonance for early detection of cardiovascular diseases

Most recent technical innovations in cardiovascular MR imaging (CMRI) are presented in this review. They include hardware and software developments, and novelties in parametric mapping. All these recent improvements lead to high spatial and temporal resolution and quantitative information on the heart structure and function. They make it achievable ambitious goals in the field of mapletic resonance, such as the early detection of cardiovascular pathologies. In this review article, we present recent innovations in CMRI, emphasizing the progresses performed and the solutions proposed to some yet opened technical problems

A Conway–Maxwell–Poisson (CMP) model to address data dispersion on positron emission tomography

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy