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

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

Contactless measurements of liquid sample electrical conductivity for estimating specific absorption rate in MR applications

Specific Absorption Rate (SAR) is the dosimetric parameter currently used as standard in the safety recommendation reports [1] for Magnetic Resonance Imaging (MRI) procedures. With the employment of MR systems with high field strengths (from 3T up to 8T), the study of the potential radiofrequency (RF) effects on the biological tissues due to higher radiofrequency, has a particular relevance [2]. Bottomley et al. [3] described a theoretical method to estimate the radiofrequency power deposition during MR exams, based on the sample geometry, the magnetic field radiofrequency, the MR sequence used (its pulse width, repetition time and flip angle) and, finally, the sample electrical conductivity. In this work we develop a liquid sample dielectric properties measurement system based on the evaluation of the resonance frequency and quality factor of a resonant circuit composed by a home-made coil. The major advantage of this method is the contactless between the liquid sample and the measurement electrode. We perform the measurement at 63.85MHz, corresponding to a 1.5T clinical MR environment, but this method can be used for measurements in the whole RF range, tuning the resonant circuit on the desired frequency

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

Quanti, quali, dove. Criteri e aree di programmazione dei distributori di carburante in Piemonte

Documenti Ires ; n.1/04- Indice #12- Il quadro di riferimento programmatico #12- I caratteri della rete distributiva attuale #19- Uno schema di classificazione delle aree #31- Il quadro sinottico dei risultati #44- La combinazione proposta #5

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

Automatic analysis of speech F0 contour for the characterization of mood changes in bipolar patients

da inserireBipolar disorders are characterized by a mood swing, ranging from mania to depression. A system that could monitor and eventually predict these changes would be useful to improve therapy and avoid dangerous events. Speech might convey relevant information about subjects' mood and there is a growing interest to study its changes in presence of mood disorders. In this work we present an automatic method to characterize fundamental frequency (F0) dynamics in voiced part of syllables. The method performs a segmentation of voiced sounds from running speech samples and estimates two categories of features. The first category is borrowed from Taylor's Tilt intonational model. However, the meaning of the proposed features is different from the meaning of Taylor's ones since the former are estimated from all voiced segments without performing any analysis of intonation. A second category of features takes into account the speed of change of F0. In this work, the proposed features are first estimated from an emotional speech database. Then, an analysis on speech samples acquired from eleven psychiatric patients experiencing different mood states, and eighteen healthy control subjects is introduced. Subjects had to perform a text reading task and a picture commenting task. The results of the analysis on the emotional speech database indicate that the proposed features can discriminate between high and low arousal emotions. This was verified both at single subject and group level. An intra-subject analysis was performed on bipolar patients and it highlighted significant changes of the features with different mood states, although this was not observed for all the subjects. The directions of the changes estimated for different patients experiencing the same mood swing, were not coherent and were task-dependent. Interestingly, a single-subject analysis performed on healthy controls and on bipolar patients recorded twice with the same mood label, resulted in a very small number of significant differences. In particular a very good specificity was highlighted for the Taylor-inspired features and for a subset of the second category of features, thus strengthening the significance of the results obtained with patients. Even if the number of enrolled patients is small, this work suggests that the proposed features might give a relevant contribution to the demanding research field of speech-based mood classifiers. Moreover, the results here presented indicate that a model of speech changes in bipolar patients might be subject-specific and that a richer characterization of subject status could be necessary to explain the observed variability

Improvement of Magnetic Resonance Imaging at Low Field using a Birdcage Coil

The main goal of this research was to demonstrate the utility of using a transmitter-receiver birdcage coil for magnetic resonance imaging at very low static field (0.18 T). As well known, the SNR decreases with frequency, thus reducing the image quality at very low field. Moreover, we would expect that the birdcage coil Q factor reduces with fre-quency. But, from experimental evidence, we proved that at low frequency (7.66 MHz), the Q factor for a well-designed birdcage coil reverses the trend, reach-ing unexpected high values. It is a prerequisite to use low static magnetic field in microimaging applica-tions for small animals experiments

A fast algorithm for phased array image reconstruction in Magnetic Resonance Imaging

Abstract: Radiofrequency receiver coils in magnetic resonance imaging systems are used to pick up the signals emitted by the nuclei. Surface coils provide a high signal-to-noise ratio because of their small sensitive region but the usable field of view is also limited to the size of the sensitive region. Using coil array permits to obtain high SNR and a large region of sensitivity: the outputs from the receiver channels are combined in order to construct a single composite image from the data of many coils. For the image construction, usually sum-of-squares (SoS) method is used, which combines data without the knowledge of the coils sensitivity but it is known to provide low contrast images. In this work we investigate and test on MR images a simple method (SUPER algorithm) which uses an estimation of coils field maps to combine the data from the phased array elements to yield an image with higher contrast respect to the usual SoS

Computational Analysis of a Radiofrequency Knee Coil for Low-Field MRI Using FDTD

Magnetic resonance imaging (MRI) is essential for the diagnosis and treatment of musculoskeletal conditions. Low-field (< 0.5T) imaging is a cost-effective alternative to more expensive high-field strength imaging due to the inexpensive setting, greater patient comfort and better safety profile. On the other hand, if compared with high-field body scanners, the low-field scanners produce poor-quality images with lower signal-to-noise ratio. Especially in low-field MR, receiver coil performance plays a significant role in image quality. Coil performance is generally evaluated using classical electromagnetic theory, but when the coil is loaded with a sample, an analytical solution is extremely difficult to derive, so that a trial-and-error approach is often followed. Numerical methods have been proposed in literature as good alternatives to predict MRI coil performance. In this study the performance of a knee coil for low-field (0.5 T) MR scanners is analyzed using workbench tests and numerical simulation with a software program based on the finite difference time domain method. Parameter performances measured using the classical workbench test are compared with those obtained using numerical simulations. Finally, the knee coil performance is validated with images acquired in a commercial low-field MR system. RI Positano, Vincenzo/A-6953-2008 OI Positano, Vincenzo/0000-0001-6955-957