Overview of MiReportor: Generating Reports for Multimodal Medical Images

Xuwen Wang, Hetong Ma, Zhen Guo, Jiao Li


Abstract
This demo paper presents a brief introduction of MiReportor, a computer-aided medical imaging report generator, which leverages a unified framework of medical image understanding and generation to predict readable descriptions for medical images, and assists radiologists in imaging reports writing.
Anthology ID:
2023.inlg-demos.1
Volume:
Proceedings of the 16th International Natural Language Generation Conference: System Demonstrations
Month:
September
Year:
2023
Address:
Prague, Czechia
Editors:
C. Maria Keet, Hung-Yi Lee, Sina Zarrieß
Venues:
INLG | SIGDIAL
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–3
Language:
URL:
https://aclanthology.org/2023.inlg-demos.1
DOI:
Bibkey:
Cite (ACL):
Xuwen Wang, Hetong Ma, Zhen Guo, and Jiao Li. 2023. Overview of MiReportor: Generating Reports for Multimodal Medical Images. In Proceedings of the 16th International Natural Language Generation Conference: System Demonstrations, pages 1–3, Prague, Czechia. Association for Computational Linguistics.
Cite (Informal):
Overview of MiReportor: Generating Reports for Multimodal Medical Images (Wang et al., INLG-SIGDIAL 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.inlg-demos.1.pdf
Supplementary attachment:
 2023.inlg-demos.1.Supplementary_Attachment.zip