Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
GPT-5.1
GPT-5.1 104 tok/s
Gemini 3.0 Pro 54 tok/s
Gemini 2.5 Flash 165 tok/s Pro
Kimi K2 202 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

4D Real-Time GRASP MRI at Sub-Second Temporal Resolution (2208.05508v1)

Published 10 Aug 2022 in physics.med-ph and eess.IV

Abstract: Intra-frame motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly-accelerated 4D (3D+time) real-time MRI framework with sub-second temporal resolution combining standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel) reconstruction. Specifically, 4D real-time MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., sub-second/3D volume). It does not require sequence modification to acquire additional navigation data, is compatible with commercially available stack-of-stars sequences, and does not need an intermediate reconstruction step. The proposed 4D real-time MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). With the ability to acquire each 3D image in less than one second, intra-frame respiratory blurring can be intrinsically reduced for body applications with our approach, which also eliminates the need for motion detection and motion compensation.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.