Project
The scar visualisation is essential to make an accurate diagnosis. Black-blood images provide a representation of the scar in bright pixels and the blood in dark pixels. This image is selected visually within a set of images presenting various black-blood contrasts. The image presenting the darkest blood, hence the best scar contrast, will be selected. This operator-dependant task often leads to variability and increases the technicians’ workload. The aim of this project is to fully automate this task while enhancing its accuracy and time efficiency.
Abstract
Joint bright- and black-blood MRI techniques provide improved scar localization and contrast. Black-blood contrast is obtained after the visual selection of an optimal inversion time (TI) which often results in uncertainties, inter- and intra-observer variability and increased workload. In this work, we propose an artificial intelligence-based algorithm to enable fully automated TI selection and simplify myocardial scar imaging.
Publications
2023
- Maillot et al., Automated inversion time selection for black-blood late gadolinium enhancement cardiac imaging in clinical practice, MRM, doi: 10.1007/s10334-023-01101-2 [PDF]
- de Villedon de Naide et al., Automated contrast selection of bright- and black-blood LGE imaging for robust myocardial scar imaging, ISMRM, SCMR
2022
- Maillot et al., Automated black-blood late gadolinium enhancement cardiac imaging through explainable user-independent inversion time selection, ISMRM