Improvement of image quality of diffusion-weighted imaging (DWI) with deep learning reconstruction of the pancreas: comparison with respiratory-gated conventional DWI

BHDLR-DWIs (short TE) provided the best pancreatic morphology image quality, whereas RGDLR-DWIs were superior for solid lesion detection.

Authors

Institutions

Publication Details

Journal
Japanese Journal of Radiology
Published
2025-04-26
DOI
https://doi.org/10.1007/s11604-025-01790-w
Primary Topic
MRI in cancer diagnosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improvement of image quality of diffusion-weighted imaging (DWI) with deep learning reconstruction of the pancreas: comparison with respiratory-gated conventional DWI

Yasuo Adachi, Kazuki Oyama, Thomas Benkert, Yasunari Fujinaga et al.
Japanese Journal of Radiology
MRI in cancer diagnosis
article

Improvement of image quality of diffusion-weighted imaging (DWI) with deep learning reconstruction of the pancreas: comparison with respiratory-gated conventional DWI

Yasuo Adachi, Kazuki Oyama, Thomas Benkert, Yasunari Fujinaga, Yoshihiro Kito, Minoru Mitsuda, Katsuya Maruyama, Fumihito Ichinohe, Omar Darwish
article en

Abstract

BHDLR-DWIs (short TE) provided the best pancreatic morphology image quality, whereas RGDLR-DWIs were superior for solid lesion detection.

Japanese Journal of RadiologyVol. 43(9)
Shinshu University (JP), Shinshu University Hospital (JP), Siemens Healthcare (United States) (US), Siemens Healthineers (Germany) (DE)
Japan Society for the Promotion of Science
Openalex Percentile: Top 87%
MRI in cancer diagnosis
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.