Automated Detection and Differentiation of Stanford Type A and Type B Aortic Dissections in CTA Scans Using Deep Learning
This deep learning automatic model can accurately and quickly detect type A AD patients, and could serve as an imaging triage in an emergency setting and facilitate early intervention and surgery to decrease the mortality rates of type A AD patients.
Authors
- Chun‐Yu Lin (ORCID: https://orcid.org/0000-0003-3375-520X)
- Hung-Hsien Liu
- Chun‐Bi Chang (ORCID: https://orcid.org/0000-0002-8605-3829)
- Chang‐Fu Kuo (ORCID: https://orcid.org/0000-0002-9770-5730)
- Chengyu Ma (ORCID: https://orcid.org/0000-0001-9589-6177)
- Li-Jen Wang (ORCID: https://orcid.org/0000-0002-2263-4835)
- Y.-J. Chen
Institutions
- Chang Gung University (TW)
- Chang Gung Memorial Hospital (TW)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-12-25
- DOI
- https://doi.org/10.3390/diagnostics15010012
- Citations
- 7
- Primary Topic
- Aortic Disease and Treatment Approaches
- Type
- article
- Field-Weighted Citation Impact
- 2.93
Funders
- Chang Gung Medical Foundation