Quantitative magnetic resonance imaging (qMRI) techniques aim to play the role of non-invasive biopsies, suitable for diagnostic purposes or to monitor the path of a pathology and the efficacy of a therapy over time, to make the healthcare system more efficient and to promote personalized medicine.
To make qMRI images more reliable, objectively comparable, and machine-interpretable, APULEIO investigates how to evaluate the uncertainty of the measurements performed within each single pixel of the images themselves.
To achieve this goal, the project focuses on two promising qMRI techniques, Electric Properties Tomography (EPT) and Magnetic Resonance Fingerprinting (MRF), adopted as case studies to develop software for quantitative imaging with embedded uncertainty evaluation.
As a side product of the research, the project
develops open access databases composed of experimental data acquired on tissue-mimicking phantoms and in vivo on human volunteers, as well as synthetic data obtained by simulating the corresponding digital twins, which can be used as a reference to test EPT and MRF reconstructions.
Contributing scientific sectors
