This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …

Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an
enormous evolution from theoretical concepts in the early 1980s to the robust imaging …

Abstract Multishot Magnetic Resonance Imaging (MRI) is a promising data acquisition
technique that can produce a high-resolution image with relatively less data acquisition time …

Quantitative radiomics features, extracted from medical images, characterize tumour-
phenotypes and have been shown to provide prognostic value in predicting clinical …

Deep Learning has become a very promising avenue for magnetic resonance image (MRI)
reconstruction. In this work, we explore the potential of unrolled networks for non-Cartesian …

While enabling accelerated acquisition and improved reconstruction accuracy, current deep
MRI reconstruction networks are typically supervised, require fully sampled data, and are …

In this work, we propose a novel image reconstruction framework that directly learns a
neural implicit representation in k-space for ECG-triggered non-Cartesian Cardiac Magnetic …

Quantitative mapping of MR tissue parameters such as the spin‐lattice relaxation time (T1),
the spin‐spin relaxation time (T2), and the spin‐lattice relaxation in the rotating frame (T1ρ) …

In this study, a fast data-driven optimization approach, named bias-accelerated subset
selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the …

Cardiac magnetic resonance imaging (MRI) is appealing to guide complex cardiac
procedures because it is ionizing radiation‐free and offers flexible soft‐tissue contrast …