Models and methods for analyzing DCE‐MRI: A review
Purpose: To present a review of most commonly used techniques to analyze dynamic
contrast‐enhanced magnetic resonance imaging (DCE‐MRI), discusses their strengths and …
contrast‐enhanced magnetic resonance imaging (DCE‐MRI), discusses their strengths and …
AI‐Enhanced Diagnosis of Challenging Lesions in Breast MRI: A Methodology and Application Primer
Computer‐aided diagnosis (CAD) systems have become an important tool in the
assessment of breast tumors with magnetic resonance imaging (MRI). CAD systems can be …
assessment of breast tumors with magnetic resonance imaging (MRI). CAD systems can be …
Variational Bayesian inference for a nonlinear forward model
Variational Bayes (VB) has been proposed as a method to facilitate calculations of the
posterior distributions for linear models, by providing a fast method for Bayesian inference …
posterior distributions for linear models, by providing a fast method for Bayesian inference …
[HTML][HTML] Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an MRI technique
for quantifying perfusion that can be used in clinical applications for classification of tumours …
for quantifying perfusion that can be used in clinical applications for classification of tumours …
Improved intravoxel incoherent motion analysis of diffusion weighted imaging by data driven Bayesian modeling
In addition to the diffusion coefficient, fitting the intravoxel incoherent motion model to
multiple b‐value diffusion‐weighted MR data gives pseudo‐diffusion measures associated …
multiple b‐value diffusion‐weighted MR data gives pseudo‐diffusion measures associated …
Ensemble of expert deep neural networks for spatio-temporal denoising of contrast-enhanced MRI sequences
Dynamic contrast-enhanced MRI (DCE-MRI) is an imaging protocol where MRI scans are
acquired repetitively throughout the injection of a contrast agent. The analysis of dynamic …
acquired repetitively throughout the injection of a contrast agent. The analysis of dynamic …
A comparative simulation study of bayesian fitting approaches to intravoxel incoherent motion modeling in diffusion‐weighted MRI
PT While - Magnetic resonance in medicine, 2017 - Wiley Online Library
Purpose To assess the performance of various least squares and Bayesian modeling
approaches to parameter estimation in intravoxel incoherent motion (IVIM) modeling of …
approaches to parameter estimation in intravoxel incoherent motion (IVIM) modeling of …
Convolutional neural networks for direct inference of pharmacokinetic parameters: application to stroke dynamic contrast-enhanced MRI
Background and Purpose: The T1-weighted dynamic contrast enhanced (DCE)-MRI is an
imaging technique that provides a quantitative measure of pharmacokinetic (PK) parameters …
imaging technique that provides a quantitative measure of pharmacokinetic (PK) parameters …
Neuroconductor: an R platform for medical imaging analysis
SUMMARY Neuroconductor (https://neuroconductor. org) is an open-source platform for
rapid testing and dissemination of reproducible computational imaging software. The goals …
rapid testing and dissemination of reproducible computational imaging software. The goals …
Reliable estimation of incoherent motion parametric maps from diffusion-weighted MRI using fusion bootstrap moves
Diffusion-weighted MRI has the potential to provide important new insights into physiological
and microstructural properties of the body. The Intra-Voxel Incoherent Motion (IVIM) model …
and microstructural properties of the body. The Intra-Voxel Incoherent Motion (IVIM) model …