Accelerated Reconstruction of Perfusion-Weighted MRI Enforcing Jointly Local and Nonlocal Spatio-temporal Constraints

08/25/2017
by   Cagdas Ulas, et al.
0

Perfusion-weighted magnetic resonance imaging (MRI) is an imaging technique that allows one to measure tissue perfusion in an organ of interest through the injection of an intravascular paramagnetic contrast agent (CA). Due to a preference for high temporal and spatial resolution in many applications, this modality could significantly benefit from accelerated data acquisitions. In this paper, we specifically address the problem of reconstructing perfusion MR image series from a subset of k-space data. Our proposed approach is motivated by the observation that temporal variations (dynamics) in perfusion imaging often exhibit correlation across different spatial scales. Hence, we propose a model that jointly penalizes the voxel-wise deviations in temporal gradient images obtained based on a baseline, and the patch-wise dissimilarities between the spatio-temporal neighborhoods of entire image sequence. We validate our method on dynamic susceptibility contrast (DSC)-MRI and dynamic contrast-enhanced (DCE)-MRI brain perfusion datasets acquired from 10 tumor patients in total. We provide extensive analysis of reconstruction performance and perfusion parameter estimation in comparison to state-of-the-art reconstruction methods. Experimental results on clinical datasets demonstrate that our reconstruction model can potentially achieve up to 8-fold acceleration by enabling accurate estimation of perfusion parameters while preserving spatial image details and reconstructing the complete perfusion time-intensity curves (TICs).

READ FULL TEXT

page 3

page 5

page 6

page 8

page 12

research
02/21/2020

Parameter selection in dynamic contrast-enhanced magnetic resonance tomography

In this work we consider the image reconstruction problem of sparsely sa...
research
04/08/2018

Direct Estimation of Pharmacokinetic Parameters from DCE-MRI using Deep CNN with Forward Physical Model Loss

Dynamic contrast-enhanced (DCE) MRI is an evolving imaging technique tha...
research
10/28/2019

Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies

We propose a new computer aided detection framework for tumours acquired...
research
02/16/2021

A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images

Real-time magnetic resonance imaging (RT-MRI) of human speech production...
research
02/26/2019

Deep MR Fingerprinting with total-variation and low-rank subspace priors

Deep learning (DL) has recently emerged to address the heavy storage and...
research
10/05/2020

Characterization of surface motion patterns in highly deformable soft tissue organs from dynamic Magnetic Resonance Imaging

In this work, we present a pipeline for characterization of bladder surf...

Please sign up or login with your details

Forgot password? Click here to reset