Resultado de búsqueda
Deep-learning-based image reconstruction shows considerable promise to accelerate both static and dynamic MR imaging and to address imaging artifacts including aliasing, motion, and ghosting.
- PubMed
This article is an introductory overview aimed at clinical...
- PubMed
24 de dic. de 2021 · Magnetic resonance imaging (MRI) is an effective auxiliary diagnostic method in clinical medicine, but it has always suffered from the problem of long acquisition time. Compressed sensing and parallel imaging are two common techniques to accelerate MRI reconstruction.
This article is an introductory overview aimed at clinical radiologists with no experience in deep-learning-based MR image reconstruction and should enable them to understand the basic concepts and current clinical applications of this rapidly growing area of research across multiple organ systems.
1 de jul. de 2021 · To accelerate MR scan, three mainstream methods have been developed, namely, physics based fast imaging sequences, hardware based parallel imaging with multiple coils and signal processing based MR image reconstruction from incomplete k-space data.
22 de mar. de 2018 · Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised...
12 de sept. de 2018 · We have presented a deep learning based MR imaging reconstruction method, wherein real-valued neural network operations are replaced by complex convolutional operations.
Abstract: Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reconstructing MR images with subsampled k-space data.
