A5005203644- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
- Bone and Joint Diseases
- Medical Image Segmentation Techniques
- Cardiac Imaging and Diagnostics
- Lower Extremity Biomechanics and Pathologies
- Advanced Image Processing Techniques
- Osteoarthritis Treatment and Mechanisms
- Lanthanide and Transition Metal Complexes
- Fetal and Pediatric Neurological Disorders
- Functional Brain Connectivity Studies
- Radiomics and Machine Learning in Medical Imaging
- Tensor decomposition and applications
- Electron Spin Resonance Studies
- Sparse and Compressive Sensing Techniques
- Image and Signal Denoising Methods
- NMR spectroscopy and applications
- Atomic and Subatomic Physics Research
- Cardiovascular Function and Risk Factors
- Total Knee Arthroplasty Outcomes
- Cerebrovascular and Carotid Artery Diseases
- Photoacoustic and Ultrasonic Imaging
- Sports injuries and prevention
Erasmus MC
2015-2024
Erasmus University Rotterdam
2015-2024
Erasmus MC Cancer Institute
2018-2023
Rotterdam University of Applied Sciences
2013-2020
Delft University of Technology
2010-2019
Cool Energy (United States)
2015
University Medical Center
2013
University Hospital and Clinics
2013
University of Antwerp
2006-2011
Abstract Improving the resolution in magnetic resonance imaging comes at cost of either lower signal‐to‐noise ratio, longer acquisition time or both. This study investigates whether so‐called super‐resolution reconstruction methods can increase slice selection direction and, as such, are a viable alternative to direct high‐resolution terms ratio and trade‐offs. The performance six acquisitions was compared with respect these based on iterative back‐projection, algebraic reconstruction,...
Abstract With diffusion tensor imaging, the of water molecules through brain structures is quantified by parameters, which are estimated assuming monoexponential diffusion‐weighted signal attenuation. The however, depend on weighting strength, b ‐value, hampers interpretation and comparison various imaging studies. In this study, a likelihood ratio test used to show that kurtosis model provides more accurate parameterization both Gaussian non‐Gaussian component compared with imaging. As...
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Diffusion kurtosis imaging (DKI) is a new magnetic resonance (MRI) model that describes the non-Gaussian diffusion behavior in tissues. It has recently been shown DKI parameters, such as radial or axial kurtosis, are more sensitive to brain physiology changes than well-known tensor (DTI) parameters several white and gray matter structures. In order estimate either DTI with maximum precision,...
In this note, we address the estimation of noise level in magnitude magnetic resonance (MR) images absence background data. Most methods proposed earlier exploit Rayleigh distributed region MR to estimate level. These methods, however, cannot be used for where no information is available. propose two different approaches image background. The first method based on local variance using maximum likelihood and second skewness data distribution. Experimental results synthetic real datasets show...
The role of wall shear stress (WSS) in atherosclerotic plaque development is evident, but the relation between WSS and composition advanced atherosclerosis, potentially resulting destabilization, a topic discussion. Using our previously developed image registration pipeline, we investigated two metrics, time-averaged (TAWSS) oscillatory index (OSI), local histologically determined set human carotid plaques. Our dataset 11 endarterectomy samples yielded 87 histological cross-sections, which...
Purpose Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a signal‐to‐noise ratio. Recently, methods have been proposed to improve the trade‐off between ratio, time of diffusion‐weighted images via super‐resolution reconstruction (SRR) techniques. However, during reconstruction, these SRR neglect q ‐space relation different images. Method An method that includes diffusion model directly reconstructs high resolution parameters from set was proposed. Our allows...
Abstract Diffusion weighted magnetic resonance images are often acquired with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise acquisition time, generally either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing visualization. In this article, we propose a super‐resolution method for diffusion that combines enhance the spatial tensor data. Each is reconstructed from...
Purpose A novel three‐dimensional (3D) T 1 and 2 mapping protocol for the carotid artery is presented. Methods 3D black‐blood imaging sequence was adapted allowing using multiple flip angles echo time (TE) preparation times. B performed to correct spatially varying deviations from nominal angle. The optimized simulations phantom experiments. In vivo scans were on six healthy volunteers in two sessions, a patient with advanced atherosclerosis. Compensation motion achieved by registration of...
Background To evaluate the influence of image registration on apparent diffusion coefficient (ADC) images obtained from abdominal free-breathing diffusion-weighted MR (DW-MRIs). Methods A comprehensive pipeline based automatic three-dimensional nonrigid registrations is developed to compensate for misalignments in DW-MRI datasets five healthy subjects scanned twice. Motion corrected both within each and between a time series. ADC distributions are compared with without two volumes interest...
There is an ongoing debate on how to model diffusivity in fiber crossings. We propose optimization framework for the selection of a dual tensor and set diffusion weighting parameters b, such that both shape orientation can be precisely as well accurately estimated. For that, we have adopted Cramér-Rao lower bound (CRLB) variance parameters, performed Monte Carlo simulations. found axial λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">||</sub>...
To evaluate the effect of automated registration in delayed gadolinium-enhanced MRI cartilage (dGEMRIC) knee on occurrence movement artefacts T1 map and reproducibility region-of-interest (ROI)-based measurements. Eleven patients with early-stage osteoarthritis ten healthy controls underwent dGEMRIC twice at 3 T. Controls unenhanced imaging. ROIs were manually drawn femoral tibial cartilage. calculation was performed without T1-weighted images. Automated three-dimensional rigid femur tibia...
A large number of mathematical models have been proposed to describe the measured signal in diffusion‐weighted (DW) magnetic resonance imaging (MRI). However, model comparison date focuses only on specific subclasses, e.g. compartment or models, and little no information is available literature how performance varies among different types models. To address this deficiency, we organized ‘White Matter Modeling Challenge’ during International Symposium Biomedical Imaging (ISBI) 2015...
Abstract Objective Infrapatellar fat pad (IPFP) fat-suppressed T2 (T2 FS ) hyperintense regions on MRI are an important imaging feature of knee osteoarthritis (OA) and thought to represent inflammation. These also common in non-OA subjects, may not always be linked Our aim was evaluate quantitative blood perfusion parameters, as surrogate measure inflammation, within -hyperintense patients with OA, patellofemoral pain (PFP) (supposed OA precursor), control subjects. Methods Twenty-two...
In this work we present a framework for reliably detecting significant differences in quantitative magnetic resonance imaging and evaluate it with diffusion tensor (DTI) experiments. As part of propose new spatially regularized maximum likelihood estimator that simultaneously estimates the parameters spatially-smoothly-varying noise level from acquisitions. The estimation method does not require repeated We show amount regularization can be set priori to achieve desired coefficient variation...
The purpose of this study was to determine the association between eye shape and volume measured with magnetic resonance imaging (MRI) optical biometry spherical equivalent (SE) in children.