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Automatic segmentation of intracranial aneurysms by deep learning algorithm and analysis of their rupture risk factors

Automatic segmentation of intracranial aneurysms by deep learning algorithm and analysis of their rupture risk factors

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400084598
Enrollment
Unknown
Registered
2024-05-21
Start date
2024-06-01
Completion date
Unknown
Last updated
2024-05-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

intracranial aneurysms

Interventions

Aneurysm ruptured group and non-ruptured group:None

Sponsors

The First Affiliated Hospital of Wenzhou Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: 1. Patients with intracranial aneurysms confirmed by DSA or CTA 2. Older than 18 years old

Exclusion criteria

Exclusion criteria: 1. Fusiform aneurysm or offending artery is difficult to identify 2. Aneurysm complicated with vascular diseases (such as moyamoya disease, arteriovenous malformation, etc.) 3. Patients underwent surgery or interventional therapy before CTA examination

Design outcomes

Primary

MeasureTime frame
anuerysm rupture;—

Countries

China

Contacts

Public ContactYunjun Yang

The First Affiliated Hospital of Wenzhou Medical University

yyjunjim@163.com+86 577 5557 8777

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026