Automated ischemic stroke lesion detection on non-contrast brain CT: a large-scale clinical feasibility test AI stroke lesion detection on NCCT
The automated NCCT-based lesion detection model demonstrated reliable diagnostic performance and provided clinically relevant prognostic information in endovascular thrombectomy-treated stroke patients.
Authors
- JoonNyung Heo (ORCID: https://orcid.org/0000-0001-6287-6348)
- Wi‐Sun Ryu (ORCID: https://orcid.org/0000-0002-2823-5253)
- Johanna Maria Ospel (ORCID: https://orcid.org/0000-0003-0029-6764)
- Myung-Jae Lee (ORCID: https://orcid.org/0000-0003-0475-1437)
- Chi Kyung Kim (ORCID: https://orcid.org/0000-0002-0423-7297)
- Leonard Sunwoo (ORCID: https://orcid.org/0000-0003-0374-8658)
- Nishita Singh (ORCID: https://orcid.org/0000-0003-3647-0904)
- Jong‐Won Chung (ORCID: https://orcid.org/0000-0002-9200-8899)
- Dongmin Kim (ORCID: https://orcid.org/0000-0001-6931-7653)
- Beom Joon Kim (ORCID: https://orcid.org/0000-0002-2719-3012)
- Beom Joon Kim (ORCID: https://orcid.org/0000-0003-2320-7621)
- Hee‐Joon Bae
Institutions
- University of Calgary (CA)
- Yonsei University (KR)
- Korea University Medical Center (KR)
- Samsung Medical Center (KR)
- Foothills Medical Centre (CA)
- Seoul National University Bundang Hospital (KR)
- Chonnam National University Hospital (KR)
- University of Manitoba (CA)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2025-08-26
- DOI
- https://doi.org/10.3389/fnins.2025.1643479
- Citations
- 1
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- National Research Foundation
- Korea Health Industry Development Institute
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea