Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair.
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| Title: | Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair. |
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| Authors: | Akouris PP; Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada., Kim S; Department of Medical Biophysics and Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.; Vector Institute, Toronto, ON, Canada.; Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada., Javidan AP; Division of Vascular Surgery, University of Toronto, Toronto, ON, Canada.; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada., McIntosh C; Department of Medical Biophysics and Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.; Vector Institute, Toronto, ON, Canada.; Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada., Crawford SA; Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.; Division of Vascular Surgery, University of Toronto, Toronto, ON, Canada.; Division of Vascular Surgery, Department of Surgery, University Health Network, Toronto, ON, Canada. |
| Source: | Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists [J Endovasc Ther] 2026 Apr 22, pp. 15266028261437610. Date of Electronic Publication: 2026 Apr 22. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Publications Country of Publication: United States NLM ID: 100896915 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1545-1550 (Electronic) Linking ISSN: 15266028 NLM ISO Abbreviation: J Endovasc Ther Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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