[HTML][HTML] A review and experimental evaluation of deep learning methods for MRI reconstruction
Following the success of deep learning in a wide range of applications, neural network-
based machine-learning techniques have received significant interest for accelerating …
based machine-learning techniques have received significant interest for accelerating …
Image reconstruction: From sparsity to data-adaptive methods and machine learning
The field of medical image reconstruction has seen roughly four types of methods. The first
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …
[HTML][HTML] SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
Diffusion tensor magnetic resonance imaging (DTI) is a widely adopted neuroimaging
method for the in vivo map** of brain tissue microstructure and white matter tracts …
method for the in vivo map** of brain tissue microstructure and white matter tracts …
[HTML][HTML] DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning
Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue
microstructure and structural connectivity in the living human brain. Nonetheless, the …
microstructure and structural connectivity in the living human brain. Nonetheless, the …
Distortion‐free, high‐isotropic‐resolution diffusion MRI with gSlider BUDA‐EPI and multicoil dynamic B0 shimming
Purpose We combine SNR‐efficient acquisition and model‐based reconstruction strategies
with newly available hardware instrumentation to achieve distortion‐free in vivo diffusion …
with newly available hardware instrumentation to achieve distortion‐free in vivo diffusion …
3D‐EPI blip‐up/down acquisition (BUDA) with CAIPI and joint H ankel structured low‐rank reconstruction for rapid distortion‐free high‐resolution T 2* map**
Purpose This work aims to develop a novel distortion‐free 3D‐EPI acquisition and image
reconstruction technique for fast and robust, high‐resolution, whole‐brain imaging as well …
reconstruction technique for fast and robust, high‐resolution, whole‐brain imaging as well …
Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)
Diffusion MRI is a useful neuroimaging tool for non-invasive map** of human brain
microstructure and structural connections. The analysis of diffusion MRI data often requires …
microstructure and structural connections. The analysis of diffusion MRI data often requires …
Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction
Purpose To introduce a combined machine learning (ML)‐and physics‐based image
reconstruction framework that enables navigator‐free, highly accelerated multishot echo …
reconstruction framework that enables navigator‐free, highly accelerated multishot echo …
[HTML][HTML] High-fidelity mesoscale in-vivo diffusion MRI through gSlider-BUDA and circular EPI with S-LORAKS reconstruction
Purpose To develop a high-fidelity diffusion MRI acquisition and reconstruction framework
with reduced echo-train-length for less T 2* image blurring compared to typical highly …
with reduced echo-train-length for less T 2* image blurring compared to typical highly …
RUN‐UP: Accelerated multishot diffusion‐weighted MRI reconstruction using an unrolled network with U‐Net as priors
Purpose To accelerate and improve multishot diffusion‐weighted MRI reconstruction using
deep learning. Methods An unrolled pipeline containing recurrences of model‐based …
deep learning. Methods An unrolled pipeline containing recurrences of model‐based …