Echo planar time‐resolved imaging with subspace reconstruction and optimized spatiotemporal encoding

  title={Echo planar time‐resolved imaging with subspace reconstruction and optimized spatiotemporal encoding},
  author={Zijing Dong and Fuyixue Wang and Timothy G. Reese and Berkin Bilgiç and Kawin Setsompop},
  journal={Magnetic Resonance in Medicine},
  pages={2442 - 2455}
To develop new encoding and reconstruction techniques for fast multi‐contrast/quantitative imaging. 

Diffusion‐PEPTIDE: Distortion‐ and blurring‐free diffusion imaging with self‐navigated motion‐correction and relaxometry capabilities

To implement the time‐resolved relaxometry PEPTIDE technique into a diffusion acquisition to provide self‐navigated, distortion‐ and blurring‐free diffusion imaging that is robust to motion, while

Accelerating T2 mapping of the brain by integrating deep learning priors with low‐rank and sparse modeling

To accelerate T2 mapping with highly sparse sampling by integrating deep learning image priors with low‐rank and sparse modeling.

Wave-encoding and Shuffling Enables Rapid Time Resolved Structural Imaging

Purpose. T 2 -Shuffling reconstructs multiple T 2 -weighted images from a single volumetric fast spin-echo (3D-FSE) scan. Wave-CAIPI achieves good reconstruction at high accelerations by better

Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI

The proposed Latent Signal Model framework inserts the decoder portion of the auto-encoder into the forward model and directly reconstructs the latent representation and achieves consistent quantitative NRMSE and qualitative improvement over linear approaches.

Single projection driven real-time multi-contrast (SPIDERM) MR imaging using pre-learned spatial subspace and linear transformation

SPIDERM is capable of generating real-time multi-contrast 3D images with a low latency and an imaging framework based on SPIDERM has the potential to serve as a standalone package for MR-guided radiation therapy by offering adaptive simulation through a ‘prep’ scan and real- time image guidance through a‘live” scan.

An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data

It is concluded that the use of an untrained neural network together with a physics-based regularization loss shows promise as a measure for determining the optimal stopping point in training without relying on fully-sampled ground truth data.

Motion‐corrected 3D‐EPTI with efficient 4D navigator acquisition for fast and robust whole‐brain quantitative imaging

To develop a motion estimation and correction method for motion‐robust three‐dimensional (3D) quantitative imaging with 3D‐echo‐planar time‐resolved imaging.

SNR‐efficient distortion‐free diffusion relaxometry imaging using accelerated echo‐train shifted echo‐planar time‐resolving imaging (ACE‐EPTI)

To develop an efficient acquisition technique for distortion‐free diffusion MRI and diffusion‐relaxometry.



Echo planar time‐resolved imaging (EPTI)

To develop an efficient distortion‐ and blurring‐free multi‐shot EPI technique for time‐resolved multiple‐contrast and/or quantitative imaging.

Motion‐corrected k‐space reconstruction for interleaved EPI diffusion imaging

To develop a new approach to correct for physiological and macroscopic motion in multishot, interleaved echo‐planar diffusion imaging.

Model‐based nonlinear inverse reconstruction for T2 mapping using highly undersampled spin‐echo MRI

To develop a model‐based reconstruction technique for T2 mapping based on multi‐echo spin‐echo MRI sequences with highly undersampled Cartesian data encoding.

Propeller echo‐planar time‐resolved imaging with dynamic encoding (PEPTIDE)

To develop a motion‐robust extension to the recently developed echo‐planar time‐resolved imaging (EPTI) approach, referred to as PROPELLER EPTI with dynamic encoding (PEPTIDE), by incorporating

Interleaved EPI diffusion imaging using SPIRiT‐based reconstruction with virtual coil compression

To develop a novel diffusion imaging reconstruction framework based on iterative self‐consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with

Accelerated MR parameter mapping with low‐rank and sparsity constraints

To enable accurate magnetic resonance (MR) parameter mapping with accelerated data acquisition, utilizing recent advances in constrained imaging with sparse sampling.

General phase regularized reconstruction using phase cycling

To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water–fat imaging and flow imaging.

Simultaneous QSM and metabolic imaging of the brain using SPICE

To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three‐dimensional 1H‐MRSI acquisition without water suppression.

High‐resolution 1H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction

To develop data acquisition and image reconstruction methods to enable high‐resolution 1H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed subspace‐based spectroscopic

T2 shuffling: Sharp, multicontrast, volumetric fast spin‐echo imaging

A new acquisition and reconstruction method called T2 Shuffling is presented for volumetric fast spin‐echo (three‐dimensional [3D] FSE) imaging. T2 Shuffling reduces blurring and recovers many images