Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain
Recent technological advancements have revolutionized routine brain magnetic resonance
imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease …
imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease …
Design of multifunctional color routers with Kerker switching using generative adversarial networks
To achieve optoelectronic devices with high resolution and efficiency, there is a pressing
need for optical structural units that possess an ultrasmall footprint yet exhibit strong …
need for optical structural units that possess an ultrasmall footprint yet exhibit strong …
Implicit neural representation for free-breathing MR fingerprinting (INR-MRF): co-registered 3D whole-liver water T1, water T2, proton density fat fraction, and R2 …
Purpose: To develop an MRI technique for free-breathing 3D whole-liver quantification of
water T1, water T2, proton density fat fraction (PDFF), R2*. Methods: An Eight-echo spoiled …
water T1, water T2, proton density fat fraction (PDFF), R2*. Methods: An Eight-echo spoiled …
Physics-Based Deep Learning Methods for Magnetic Resonance Data Sampling, Image Reconstruction and Quantitative Susceptibility Mapping
J Zhang - 2023 - search.proquest.com
Improved magnetic resonance (MR) data sampling, under-sampled image reconstruction,
and dipole inversion can be achieved using physics-based deep learning methods. These …
and dipole inversion can be achieved using physics-based deep learning methods. These …