Deep Learning-Based Fully Automated Aortic Valve Leaflets and Root Measurement From Computed Tomography Images ― A Feasibility Study ―
This fully automated algorithm can assist in evaluating aortic valve/root anatomy for planning surgical and transcatheter treatments while saving time and minimizing workload.
Authors
- Naoki Tomii (ORCID: https://orcid.org/0000-0002-5485-4883)
- Haruo Yamauchi (ORCID: https://orcid.org/0000-0003-1526-1759)
- Shu Takagi (ORCID: https://orcid.org/0000-0002-9353-2465)
- Minoru Ōno (ORCID: https://orcid.org/0000-0001-6443-8042)
- Gakuto Aoyama
- Ichiro Sakuma (ORCID: https://orcid.org/0000-0002-4919-9466)
- Kenji Ino
- Takuya Sakaguchi (ORCID: https://orcid.org/0000-0002-2862-2325)
- Hiroyuki Tsukihara
- Katsuhiko Fujimoto
Institutions
- Canon (Japan) (JP)
- University of Tokyo Hospital (JP)
- Canon Medical Systems Corporation (Japan) (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Circulation Journal
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1253/circj.cj-24-1031
- Citations
- 2
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- Canon Medical Systems Corporation
- Japan Science and Technology Agency
- Center of Innovation Program