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Revolutionizing Radiology Reporting With Artificial Intelligence-Based Voice Recognition: A Pilot Study on Lumbar Spine Magnetic Resonance Imaging

Authors
 Minwook Lee  ;  Hee Woo Cho  ;  Young Han Lee 
Citation
 Investigative Magnetic Resonance Imaging, Vol.29(2) : 96-99, 2025-06 
Journal Title
Investigative Magnetic Resonance Imaging
ISSN
 2384-1095 
Issue Date
2025-06
Keywords
Interpretation time ; Voice recognition ; Artificial intelligence ; Spine ; Magnetic resonance imaging
Abstract
Purpose
This study evaluated whether the interpretation speed of routine lumbar spine magnetic resonance imaging (MRI) increases when using an artificial intelligence (AI)-based voice recognition system compared with the conventional keyboard typing method.

Materials and Methods
We retrospectively reviewed 527 routine lumbar spine MRI images performed between November 2022 and February 2023. Two radiologists interpreted 292 and 235 images using conventional keyboard typing and dictation with an AI-based voice recognition system, respectively. Interpretation time, report character count, and turnaround time for the two methods were compared.

Results
Interpretation time was significantly reduced by 21.7% using dictation with the AI-based voice recognition method compared with that using the conventional keyboard typing method (p < 0.05). However, no statistically significant differences were observed in the reported character count or turnaround time (p > 0.05).

Conclusion
AI-based voice recognition system for interpreting lumbar spine MRI significantly reduced interpretation time compared with the conventional keyboard typing method, suggesting enhanced efficiency for radiologists.
Files in This Item:
T202506061.pdf Download
DOI
10.13104/imri.2025.0005
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Lee, Minwook(이민욱) ORCID logo https://orcid.org/0000-0003-2822-0489
Lee, Young Han(이영한) ORCID logo https://orcid.org/0000-0002-5602-391X
Cho, Hee Woo(조희우) ORCID logo https://orcid.org/0000-0002-5079-6954
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/207643
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