Accuracy of artificial intelligence-based simulation for assessing lung vessels and volume using unenhanced computed tomography
This 3D image technique using UECT data may be comparable to that obtained with ECT data in terms of achieving lobar and partial segmental branch levels.
Authors
- Kentaro Fukuta
- Taro Oba
- Masatoshi Kakihana (ORCID: https://orcid.org/0000-0003-1737-6883)
- Ryosuke Amemiya (ORCID: https://orcid.org/0000-0003-4923-0344)
- Hideyuki Furumoto (ORCID: https://orcid.org/0000-0002-5000-4283)
- Yujin Kudo (ORCID: https://orcid.org/0000-0003-3187-9970)
- Jinho Park (ORCID: https://orcid.org/0000-0002-8135-0509)
- Yoshihisa Shimada (ORCID: https://orcid.org/0000-0003-3811-6159)
- Norihiko Ikeda (ORCID: https://orcid.org/0000-0002-5141-8808)
- Tatuso Ohira
- Masaru Hagiwara
- Tatsuo Oomori
- Yuki Nagamatu
Institutions
- Tokyo Medical University (JP)
Publication Details
- Journal
- European Journal of Cardio-Thoracic Surgery
- Published
- 2025-03-22
- DOI
- https://doi.org/10.1093/ejcts/ezae449
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08