📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Cerebrovascular super-resolution 4D Flow MRI - Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure. (2023)

First Author: Ferdian E

Attributed to: Adaptive, Multi-scale, Data-Infused Biomechanical Models for Cardiac Diagnostic and Prognostic Assessment funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1016/j.media.2023.102831

PubMed Identifier: 37244143

Publication URI: http://europepmc.org/abstract/MED/37244143

Type: Journal Article/Review

Volume: 88

Parent Publication: Medical image analysis

ISSN: 1361-8415