Compressed Quantitative MRI
Lead Research Organisation:
Heriot-Watt University
Department Name: Sch of Engineering and Physical Science
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
Publications
Naghibzadeh S
(2018)
Facet-Based Regularization for Scalable Radio-Interferometric Imaging
Besson A
(2018)
Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction.
in IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Golbabaee M
(2019)
CoverBLIP: accelerated and scalable iterative matched-filtering for magnetic resonance fingerprint reconstruction*
in Inverse Problems
Lyons A
(2019)
Computational time-of-flight diffuse optical tomography
in Nature Photonics
Besson A
(2019)
A Physical Model of Nonstationary Blur in Ultrasound Imaging
in IEEE Transactions on Computational Imaging
Repetti A
(2019)
Scalable Bayesian Uncertainty Quantification in Imaging Inverse Problems via Convex Optimization
in SIAM Journal on Imaging Sciences
Terris M
(2020)
Building Firmly Nonexpansive Convolutional Neural Networks
Duarte R
(2020)
Greedy approximate projection for magnetic resonance fingerprinting with partial volumes
in Inverse Problems
Description | New algorithms can be developed for Quantitative imaging that are fast and enable the identification of multiple tissues per pixel in the image |
Exploitation Route | They can be used throughout medical imaging, or for other imaging applications |
Sectors | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Healthcare |