Large multimodality model fine-tuned for detecting breast and esophageal carcinomas on CT: a preliminary study
The fine-tuned LMM could detect both breast and esophageal carcinomas on chest contrast-enhanced CT with high diagnostic performance. Usefulness of large multimodality models in chest cancer imaging has not been assessed so far. The fine-tuned large multimodality model could detect breast and esophageal carcinomas with high diagnostic performance (area under the receiver operating characteristic curve of 0.890 and 0.880, respectively).
Authors
- Osamu Abe (ORCID: https://orcid.org/0000-0002-1180-2629)
- Takatoshi Kubo (ORCID: https://orcid.org/0000-0003-3512-1980)
- Masashi Kawamura (ORCID: https://orcid.org/0000-0001-8312-732X)
- Shigeru Kiryu (ORCID: https://orcid.org/0000-0003-1440-9483)
- Koichiro Yasaka (ORCID: https://orcid.org/0000-0002-0324-6562)
- Yuki Sonoda
Institutions
- The University of Tokyo (JP)
- International University of Health and Welfare (JP)
Publication Details
- Journal
- Japanese Journal of Radiology
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1007/s11604-024-01718-w
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21