Jul 2026· Magnetic Resonance in Medicine· Vol 96, pp. 2072 - 2082· 0 citations· 45 references
Medicine
TL;DR
A segmented 3D echo planar imaging sequence is evaluated based on a segmented 3D echo planar imaging (3D‐EPI) sequence, accelerated with 2D Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA) undersampling and denoised with a deep learning‐based network.
Abstract
Recent updates to the diagnostic criteria of multiple sclerosis (MS) require whole‐brain T2*‐weighted (T2*w) imaging with submillimeter resolution to detect novel diagnostic biomarkers such as the central vein sign. However, to achieve the needed submillimeter spatial resolution, conventional T2*w 3D gradient‐echo scans sequences are limited by prohibitively long scan times for clinical use. Here, we evaluated a different approach based on a segmented 3D echo planar imaging (3D‐EPI) sequence, accelerated with 2D Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA) undersampling and denoised with a deep learning‐based network.
Purpose To determine whether structural MRI information can improve reconstruction of highly accelerated 3D snapshot chemical exchange saturation transfer (CEST) MRI. Methods Fully sampled brain CEST data were retrospectively undersampled at acceleration factors (AFs) of 4, 6, 8, 10, and 12. We compared reconstruction...
E. Mensah, Abrar Faiyaz, G. Schifitto et al.· bioRxiv· 0 citations
The Frequency Attention Residual Denoising (FARD) network is proposed, a multi-contrast fusion model that leverages both spatial and frequency-domain processing to enhance apparent isotropic detail on a 1mm3 grid for all contrasts from these complementary inputs.
Alexander Nazarov, N. Kiryati, Dani Roizen et al.· Medical Image Analysis· 0 citations
A fast, B1 +‐corrected T1 mapping protocol based on PETALUTE (a 3D dual‐echo ultrashort echo time MRI sequence with a petal‐like rosette k‐space trajectory) using a variable flip‐angle (VFA) acquisition for T1 mapping to assess ferumoxytol distribution is developed.
Zhen Jiang, S. Sawiak, Alexandra Lipka et al.· Medical Physics (Lancaster)· 0 citations
Deep Resolve improved the robustness of automated brain segmentation in accelerated T2-weighted MRI, reducing cross-protocol variability and improving spatial reproducibility, with the largest reduction in reference-relative error in the most acceleration-sensitive pipeline.
J. Lasek, R. Obuchowicz, M. Strzelecki et al.· medRxiv· 0 citations
VIPP-SR (View-Independent Patched Projection Super-Resolution), a cross-contrast guided super-resolution framework that restores the inter-plane resolution of an existing anisotropic T2w volume without an isotropic ground-truth T2w, is proposed.
M. Shen, Haicheng Wang, Meghna Trivedi et al.· 0 citations
RATIONALE AND OBJECTIVES
This study aimed to efficiently denoise short 7 T MRI acquisitions to achieve the image quality of longer scans using a generative Artificial Intelligence (AI) model.
MATERIALS AND METHODS
A 7T Conditional Diffusion Model (7TCDM) was trained on an in-house 7T dataset of 11 examinations consis...
