The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Kinetic analysis of dynamic PET data requires a correct knowledge of the arterial input function (AIF) which is often not straightforward to measure. An alternative method to invasive blood sampling is the simultaneous estimation (SIME) method, where the AIF and kinetic parameters are estimated at the same time using kinetic information from different regions. We have previously shown that if the...
For an efficient analysis the estimation of the noise level in images is very important to specific estimates of each modality. Moreover, it is a fundamental step and indispensable procedure for a number of image processing approaches. Especially in magnetic resonance images (MRI) due to the Rician presented in these, where the level of noise must be evaluated. In this paper a new method to estimate...
This paper reports on a novel method for estimating the sensor bias of three-axis magnetometers (or any other field sensor). Our approach employs relative angular position measurements to estimate the three-axis magnetometer measurement bias, significantly improving magnetometer-based attitude estimation. Relative angular position measurements can be calculated from a variety of sources, including...
This paper is focused on quantitative perfusion analysis using MRI and ultrasound. In both MRI and ultrasound, most approaches allow estimation of rate constants (Ktrans, kep for MRI) and indices (AUC, TTP) that are only related to the physiological perfusion parameters of a tissue (e.g. blood flow, vessel permeability) but do not allow their absolute quantification. Recent methods for quantification...
A pixel-wise method for absolute and local aortic pressures estimation using 3D velocities in MRI and carotid pressure curves to set-up reference pressure values is presented. This method is based on the Navier-Stokes equation and a fast iterative algorithm. Its reliability was demonstrated: 1) in a synthetic phantom by comparison against simplified Bernoulli equation applied at peak velocities, and...
Relaxometry mapping is a quantitative modality in magnetic resonance imaging (MRI) widely used in neuroscirence studies. Despite its relevance and utility, voxel measurement of relaxation time in relaxometry MRI is compromised by noise that is inherent to MRI modality and acquisition hardware. In order to enhance signal to noise ratio (SNR) and quality of relaxometry mapping we propose application...
It has been shown that Electrical Properties d(EPs) of biological tissues can be derived from MR-based B1 measurement. A strong appeal for these ‘Electrical Property Tomography’ (EPT) methods is to estimate real-time and subject-specific local specific absorption rate (SAR) induced by RF transmission. In order to investigate the feasibility of EPT-based local SAR estimation, following previously proposed...
In this work, we investigate the problem of estimating time-varying noise distribution parameter on a factor graph. A new message passing scheme is proposed by incorporating the variational Bayes (VB) into the belief propagation algorithm for estimating of time-varying noise distribution parameter in a low-density parity-check decoder. The scheme can also be used for the estimation of the correlation...
T∗2 mapping or R∗2 mapping for brain function offers advantages such as providing quantitative measurements independent of the MRI acquisition parameters (e.g. echo time TE). However, magnetic field susceptibility in the human brain can prevent an accurate estimation of R∗2, which in turn impacts the ability to study brain function. The present work investigates the effects of in-plane magnetic susceptibility-induced...
Independent component analysis (ICA) has been widely applied to identify brain functional networks from multiple-subject fMRI. However, the best approach to handle artifacts is not yet clear. In this work, we study and compare two ICA approaches for artifact removal using simulations and real fMRI data. The first approach, recommended by the human connectome project, performs ICA on individual data...
High precision measurement of magnetic fields has been of great importance for both fundamental physics and practical applications. Magnetometers based on atomic spin effect provide a new technique for high precision measurement and have been enabled as the most sensitive magnetic sensors at present. However, the atomic spins used as probes to sense the magnetic fields are prone to the decoherence...
Aim at magnetic resonance imaging (MRI) inherent bias field, a new method to estimate image bias field based on diffusion was proposed, which was based on an intuitive assumption that the true bias field can be evolved and approximated by image surface. To constrain this evolution, an energy function was designed based on two diffusion constraints. One was that the bias-free image has concise representation...
Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity inhomogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. In this paper, it is assumed that the local image data within each voxel's neighborhood satisfy the Gaussian mixture model (GMM),...
In high-field magnetic resonance imaging (MRI), water-fat separation in the presence of B0 field inhomogeneity is important research. Various field map estimation techniques that use three-point multi-echo acquisitions have been developed for reliable water fat separation. Among the numerous techniques, iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL)...
Magnetic resonance imaging is affected by intensity inhomogeneity, also known as the bias field, which is mainly caused by imperfections in the radio frequency coils or inhomogeneous coil sensitivities in the receiving coils. In this paper, we proposed a new method which automatically correct the bias field using a regularized method. The method does not need extra scan devices or empirical data....
Since compressive sensing (CS) is robust to noise and does not require any special hardware, CS-based methods are advantageous to other ones for increasing MRI speed. Monotonic re-ordering (sorting) of the desired signal can increase its sparsity and consequently CS reconstruction efficiency. To use this, it is essential to estimate re-ordering operator which usually has been done by parallel imaging...
Wild bootstrap resampling technique was proposed to improve parameter estimations of intra-voxel incoherent motion (IVIM) MRI, i.e. diffusion fraction (f), diffusion (D) and pseudo-diffusion (D∗), without increasing scan time. It was verified via simulation and clinical scan. In simulation, estimation accuracy and uncertainty obtained from asymptotic fitting with and without wild bootstrapping were...
The pharmacokinetic (PK) parameters estimated from DCE-MRI by the nonlinear least squares approach on each pixel individually may be biased and erroneous. To obtain more reliable estimation, we propose a method to utilize the information of anatomical structure contained in the DCE-MRI image sequence for the reconstruction of PK parameter maps through the guided image filtering. Using the DCE-MRI...
Diffusion magnetic resonance imaging (dMRI) and resting state functional MRI (RS-fMRI) provide two complementary views of brain circuitry. dMRI facilitates the estimation of anatomical connectivity (AC) through fiber tractography, while RS-fMRI enables the estimation of functional connectivity (FC) based on temporal signal correlations between different brain areas. Recently, there is a methodological...
Analytic multi-compartment models have gained a tremendous popularity in the recent literature for studying the brain white matter microstructure from diffusion MRI. This class of models require the number of compartments to be known in advance. In the white matter however, several non-collinear bundles of axons, termed fascicles, often coexist in a same voxel. Determining the optimal fascicle configuration...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.