Article

Perfusion estimation using MRI-based measurements and a porous media flow model

2023-04-28

Abstract excerpt

The measurement of perfusion and filtration of blood in biological tissue give rise to important clinical parameters used in diagnosis, follow-up, and therapy. In this paper we address techniques for perfusion analysis using processed contrast agent concentration data from dynamic MRI acquisitions. New methodology for analysis is evaluated and verified using synthetic data generated on a tissue geometry. <h4>Autho...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9398e19f-f419-5fa6-81e1-5ce54699d870
DOI: 10.1101/2023.04.25.538213

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Perfusion estimation using MRI-based measurements and a porous media flow modelDOI 10.1101/2023.04.25.538213Read

SpinFlowSim: a blood flow simulation framework for histology-informed diffusion MRI microvasculature mapping in cancerSemantic proximity Read

Cerebrovascular super-resolution 4D Flow MRI – using deep learning to non-invasively quantify velocity, flow, and relative pressureSemantic proximity Read

Improving Glioblastoma Classification Using Quantitative Transport Mapping with a Synthetic Data Trained Deep Neural NetworkSemantic proximity Read

Non-invasive arterial input function estimation using an MRI atlas and machine learningSemantic proximity Read

Parameter quantification for oxygen transport in the human brainSemantic proximity Read

Uncertainty quantification in cerebral circulation simulations focusing on the collateral flow: Surrogate model approach with machine learningSemantic proximity Read

Redefining Hemodynamic Imaging in Stroke: Perfusion Parameter Map Generation from TOF-MRA using Artificial IntelligenceSemantic proximity Read

Machine Learning for Aiding Blood Flow Velocity Estimation Based on AngiographySemantic proximity Read

Physics-Informed AI Framework Enables Generalizable and Reliable Cerebrovascular Hemodynamic ProfilingSemantic proximity Read

A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formationSemantic proximity Read

On the sensitivity analysis of porous finite element models for cerebral perfusion estimationSemantic proximity Read

MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic strokeSemantic proximity Read