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.
We are interested in investigating white matter connectivity using a novel computational framework that does not use diffusion tensor imaging (DTI) but only uses T1-weighted magnetic resonance imaging. The proposed method relies on correlating Jacobian determinants across different voxels based on the tensor-based morphometry (TBM) framework. In this paper, we show agreement between the TBM-based...
In this study, we propose a methodology to estimate 3D+time maps of left ventricular fibre strain from human structural and dynamic MRI data. A finite element model integrates fibre principal direction throughout the left ventricle from an ex vivo human diffusion tensor MRI acquisition and motion from tagged MRI. This combination enables the estimation of fibre strain and its variation throughout...
In this paper we address two problems related to the parametric reconstruction of the diffusion signal in the complete 3D Q-space. We propose a modified Spherical Polar Fourier (mSPF) basis to naturally impose the continuity of the diffusion signal on the whole space. This mathematical constraint results in a dimension reduction with respect to the original SPF basis. In addition, we derive the expression...
This paper presents a paradigm for population-based studies using geodesic connectivity maps computed from DTI (Diffusion Tensor Imaging) data. Geodesic connectivity maps provide a measure of connectivity characterization between different regions of the brain using a tensor-based measure that combines anisotropy and orientation information. A connectivity map is constructed relative to a given region...
In this paper we explore a parallel implementation for fast calculation of a tomographic projection operator for content-adaptive mesh model (CAMM) image reconstruction. Previously we introduced 2D and 3D tomographic image reconstruction using a CAMM for single positron emission computed tomography (SPECT). The proposed parallel method is fast and allows incorporation of a non-uniform attenuation...
In PET, as the spatial resolution of the measurement system is increased, multiple interactions of a single photon may be separately measured and such events are often removed from the data used in image reconstruction. While for some PET imaging tasks this effect is unimportant, for primate, brain and high-spatial-resolution imaging where sensitivity is important, such Inter Crystal Scattering (ICS)...
Both parallel Magnetic Resonance Imaging (pMRI) and Compressed Sensing (CS) are emerging techniques to accelerate conventional MRI by reducing the number of acquired data in the k-space. So far, first attempts to combine sensitivity encoding (SENSE) imaging in pMRI with CS have been proposed in the context of Cartesian trajectories. Here, we extend these approaches to non-Cartesian trajectories by...
The most common image representation method for biomedical image reconstruction uses pixels, and the image is assumed to be constant throughout the pixel. Other methods have also been used. In many reconstruction problems, the measured data is approximated by line integrals through the object. This fact suggests a new class of model representation methods based on classical Newton-Cotes methods of...
Compressed sensing (CS) has been successfully applied to accelerate conventional magnetic resonance imaging (MRI) with Fourier encoding. Total variation (TV) is usually used as the regularization function for image reconstruction. However, it is know that such ℓ1-based minimization algorithm needs more measurements than the ℓ0-based ones. On the other hand, ℓ0-based minimization is computational intractable...
Compressed sensing (CS) and parallel imaging (PI) have been widely studied for accelerating MRI reconstruction. Furthermore, the serial combination methods of CS and PI have been proposed for even higher speed of reconstruction. However, both reconstructed signals by CS and PI are not as accurate as acquired MR signals, so that errors of CS reconstruction as the first step will be propagated and even...
In order to reduce both acquisition and reconstruction times, illumination and detection in fluorescence molecular tomography have recently evolved from a point-based to a pattern-based approach. However, the choice of the best set of source patterns to project onto the sample is still an open problem. Here, we introduce a novel method, namely the virtual source patterns method, which allows for considering...
Circular holography is a novel reconstruction technique for Breast Microwave Radar (BMR) imaging. Compared to current state of the art BMR image formation methods, this reconstruction approach yields spatially accurate images with higher signal to noise ratios and no artifacts. Nevertheless, a preclinical study is required to assess the feasibility of this technique in realistic breast imaging scenarios...
Our contribution in this paper is two fold. First, we propose a novel discretization of the forward model for differential phase-contrast imaging that uses B-spline basis functions. The approach yields a fast and accurate algorithm for implementing the forward model, which is based on the first derivative of the Radon transform. Second, as an alternative to the FBP-like approaches that are currently...
Functional near infrared spectroscopy (fNIRS) is a non-invasive imaging modality to measure functional brain activities. Many researches have investigated diffuse optical tomography (DOT) to overcome the limitation of lack of depth information in fNIRS topographic approach. In this paper, we proposes a novel compressed sensing approach, especially using a 2-thresholding algorithm, that directly reconstructs...
Medical image simulation is useful for biological modeling, image analysis, and designing new imaging devices but it is not widely available due to the complexity of simulators, the scarcity of object models, and the heaviness of the associated computations. This paper presents the Virtual Imaging Platform, an openly-accessible web platform for multi-modality image simulation. The integration of simulators...
The differential phase contrast CT (DPC-CT) implemented with x-ray tube and grating is emerging as a new technology to improve the contrast sensitivity of the conventional CT. Via system modeling, analysis and computer simulation, we investigate the DPC-CT's characteristics of signal and noise and compare them with the conventional CT. The preliminary data show that the DPC-CT possesses a modulation...
Phase retrieval from Fresnel diffraction patterns is a nonlinear ill-posed inverse problem of paramount importance in various areas of applied physics. Recently a new non-linear iterative algorithm based on a Landweber method with an analytic calculation of the Frechet derivative adjoint has been proposed. In this work, we refine this scheme by introducing Fienup projectors in the algorithm. The new...
A weakly supervised image classification framework is presented in this paper. Given reference images marked by clinicians as relevant or irrelevant, we learn to automatically detect relevant patterns, i.e. patterns that only appear in relevant images. After training, relevant patterns are sought in unseen images in order to classify each image as relevant or irrelevant. No manual segmentations are...
Lower back pain (LBP) is widely prevalent in people all over the world and negatively affects the quality of life due to chronic pain and change in posture. Automatic localization of intervertebral discs from lumbar MRI is the first step towards computer-aided diagnosis of lower back ailments. Till date, most of the research has been useful in determining a point within each lumbar disc, hence we...
We have designed a computer aided diagnosis (CADx) system to assess the presence of cancer in FDG PET/CT exams of lymphoma patients. Detection performances of the random decision forest (RDF) and support vector machine (SVM) classifiers were assessed based on a feature set including 115 PET and CT first order and textural parameters. An original feature selection method based on combining different...
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.