Accelerated 1.2-minute 4-echo UTE-based CT-like Imaging using CG-SENSE and Deep Learning-based Denoising Reconstruction (DLR)

Motivation: Multi-echo UTE provides CT-like image contrast, which allows bone assessment without radiation. However, long scan-time and low resolution may hinder it wider clinical adoption. Goal(s): We aimed to reduce scan-time and/or improve image resolution/sharpness of mecho-UTE using a CG-SENSE and Deep Learning-based Denoising Reconstruction. Approach: On patients, 5.8min 0.8 mm3 isotropic 3D 4-echo UTE sequence was acquired and 2-5X retrospectively accelerated. The resolution and sharpness of CT-like images were measured and compared for gridding (GRID) and CG-SENSE+DLR. Results: DLR+CG-SENSE enables up to 5X acceleration (1.2min) with comparable resolution/sharpness compared to the reference 5.8min acquisition. Impact: CG-SENSE+DLR improves the resolution and sharpness of CT-like images that couples with a potential 1.2min scan time would encourage wider clinical adoption of radiation-free UTE for bone assessment.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0156
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accelerated 1.2-minute 4-echo UTE-based CT-like Imaging using CG-SENSE and Deep Learning-based Denoising Reconstruction (DLR)

Duane DeVries, Charles P. Ho, Takashi Kawai, Brian Tymkiw et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced X-ray and CT Imaging
article

Accelerated 1.2-minute 4-echo UTE-based CT-like Imaging using CG-SENSE and Deep Learning-based Denoising Reconstruction (DLR)

Duane DeVries, Charles P. Ho, Takashi Kawai, Brian Tymkiw, Dawn Berkeley, Matthew T. Provencher, Scott Tashman, Mo Kadbi, P Hung, Wissam AlGhuraibawi, Kacie Sorfleet, Mitsuhiro Bekku
article en

Abstract

Motivation: Multi-echo UTE provides CT-like image contrast, which allows bone assessment without radiation. However, long scan-time and low resolution may hinder it wider clinical adoption. Goal(s): We aimed to reduce scan-time and/or improve image resolution/sharpness of mecho-UTE using a CG-SENSE and Deep Learning-based Denoising Reconstruction. Approach: On patients, 5.8min 0.8 mm3 isotropic 3D 4-echo UTE sequence was acquired and 2-5X retrospectively accelerated. The resolution and sharpness of CT-like images were measured and compared for gridding (GRID) and CG-SENSE+DLR. Results: DLR+CG-SENSE enables up to 5X acceleration (1.2min) with comparable resolution/sharpness compared to the reference 5.8min acquisition. Impact: CG-SENSE+DLR improves the resolution and sharpness of CT-like images that couples with a potential 1.2min scan time would encourage wider clinical adoption of radiation-free UTE for bone assessment.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 76%
Advanced X-ray and CT Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.