89 citations
- The University of MelbourneAU12 papers
- Monash UniversityAU8 papers
- The University of QueenslandAU6 papers
- University of New EnglandAU5 papers
- Commonwealth Scientific and Industrial Research OrganisationAU4 papers
- La Trobe UniversityAU4 papers
- Queensland University of TechnologyAU4 papers
- UNSW SydneyAU3 papers
- Data61AU2 papers
- National Imaging FacilityAU2 papers
- OpticaUS2 papers
- Advanced Photon Source1 paper
5 papers · 1 filter
Robust, fast and accurate mapping of diffusional mean kurtosis
Megan E. Farquhar, Qianqian Yang, Viktor Vegh
Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, tr…
NeXtQSM -- A complete deep learning pipeline for data-consistent quantitative susceptibility mapping trained with hybrid data
Francesco Cognolato, Kieran O'Brien, Jin Jin +4
Deep learning based Quantitative Susceptibility Mapping (QSM) has shown great potential in recent years, obtaining similar results to established non-learning approaches. Many curr…
Accelerating Quantitative Susceptibility Mapping using Compressed Sensing and Deep Neural Network
Yang Gao, Martijn Cloos, Feng Liu +3
Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are r…
Low-signal limit of X-ray single particle imaging
Kartik Ayyer, Andrew J. Morgan, Andrew A. Aquila +7
An outstanding question in X-ray single particle imaging experiments has been the feasibility of imaging sub 10-nm-sized biomolecules under realistic experimental conditions where…
On the efficiency of computational imaging with structured illumination
T. E. Gureyev, D. M. Paganin, A. Kozlov +2
A generic computational imaging setup is considered which assumes sequential illumination of a semi-transparent object by an arbitrary set of structured illumination patterns. For…