1,721,258 research outputs found
Magnetic resonance spectroscopic signal processing for in vivo tissue metabolic studies RID A-6953-2008
No full text
Combining high-performance computing and networking for advanced 3-D cardiac imaging RID A-6953-2008
No full textThis paper deals with the integration of a powerful parallel computer-based image analysis and visualization system for cardiology into a hospital information system. Further services are remote access to the hospital Web server through an internet network. The visualization system includes dynamic three-dimensional representation of two types of medical images (e.g,, magnetic resonance and nuclear medicine) as well as two images in the same modality (e.g., basal versus stress images). A series of software tools for quantitative image analysis developed for supporting diagnosis of cardiac disease are also available, including automated image segmentation and quantitative time evaluation of left ventricular volumes and related indices during cardiac cycle, myocardial mass, and myocardial perfusion indices. The system has been tested both at a specialized cardiologic center and for remote consultation in diagnosis of cardiac disease by using anatomical and perfusion magnetic resonance images
Nonlinear analysis of carotid artery echographic images RID A-6953-2008
No full textThis study deals with application of nonlinear analysis to the identification of spatial complex patterns in echographic images of normal and pathological carotid arteries. Complexity measures indices in normal and atherosclerotic plaques, related to slow space-temporal evolution of biological patterns, are evaluated. In particular, we found that the correlation dimension index lets to differentiate normal from pathological groups, allowing to infer on complex interaction mechanism responsible of plaque formation process
Regularization techniques on least squares non-uniform fast Fourier transform
No full textNon-Cartesian acquisition strategies are widely used in MRI to dramatically reduce the acquisition time while at the same time preserving the image quality. Among non-Cartesian reconstruction methods, the least squares non-uniform fast Fourier transform (LS_NUFFT) is a gridding method based on a local data interpolation kernel that minimizes the worst-case approximation error. The interpolator is chosen using a pseudoinverse matrix. As the size of the interpolation kernel increases, the inversion problem may become ill-conditioned. Regularization methods can be adopted to solve this issue. In this study, we compared three regularization methods applied to LS_NUFFT. We used truncated singular value decomposition (TSVD), Tikhonov regularization and L1-regularization. Reconstruction performance was evaluated using the direct summation method as reference on both simulated and experimental data. We also evaluated the processing time required to calculate the interpolator. First, we defined the value of the interpolator size after which regularization is needed. Above this value, TSVD obtained the best reconstruction. However, for large interpolator size, the processing time becomes an important constraint, so an appropriate compromise between processing time and reconstruction quality should be adopted
Can Imaging Techniques Identify Smoking-Related Cardiovascular Disease?
No full textThis article reviews the current techniques employed to assess endothelial dysfunction in different categories of smokers. Simple but effective methods to assess regional and local properties of large arteries for epidemiologic studies are firstly discussed. After, more complex but accurate image-based methods are described. In particular, the role of high resolution magnetic resonance to quantify, in a single examination, vascular function at different sites of peripheral and central arteries is summarized. Finally, the role of positron emission tomography and magnetic resonance flow mapping is described to assess myocardial microcirculation at rest and under external stressors
Automated cardiac MR image segmentation: theory and measurement evaluation RID A-6953-2008
No full textWe present a new approach to magnetic resonance image segmentation with a Gradient-Vector-Flow-based snake applied to selective smoothing filtered images. The system also allows automated image segmentation in the presence of grey scale inhomogeneity, as in cardiac Magnetic Resonance imaging. Removal of such inhomogeneities is a difficult task, but we proved that using non-linear anisotropic diffusion filtering, myocardium edges are selectively preserved. The approach allowed medical data to be automatically segmented in order to track not only endocardium, which is usually a less difficult task, but also epicardium in anatomic and perfusion studies with Magnetic Resonance. The method developed proceeds in three distinct phases: (a) an anisotropic diffusion filtering tool is used to reduce grey scale inhomogeneity and to selectively preserve edges; (b) a Gradient-Vector-Flow-based snake is applied on filtered images to allow capturing a snake from a long range and to move into concave boundary regions; and (c) an automatic procedure based on a snake is used to fit both endocardium and epicardium borders in a multiphase, multislice examination. A good agreement (P < 0.001) between manual and automatic data analysis, based on the mean difference+/-SD, was assessed in a pool of 907 cardiac function and perfusion images. (C) 2002 IPEM. Published by Elsevier Science Ltd. All rights reserved
Molecular imaging: Its application in cardiovascular diagnosis RID A-6953-2008
No full textThe emerging field of molecular and genomic imaging is providing new opportunities to visualize and quantify the biology of living organisms. To reach such goal all the major imaging modalities concur to this new field, each with its mechanism for generating contrast and with its spatial resolution and specificity. This review deals with a brief introduction to the molecular imaging principles and reports on the state-of-the-art in cardiovascular disease
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