bioRxiv / medRxiv
open access
Does Deep Learning Vascular Segmentation on CTA Improve Vertebral Artery Dissection Detection?
PurposeThe aims of this study were to develop an externally validated deep learning vascular segmentation model for digital enhancement of vertebral artery dissection detection on CTA and to assess clinical utility of the model through a paired crossover reader study. Materials and MethodsThis retr
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions#1118461
- Beyond Volume Overlap: Surface Matching for Topology-Aware Coronary Artery Segmentation#1115696
- VesselSDF: Distance Field Priors for Vascular Network Reconstruction#1247272
- Deep learning for medical imaging : automated ultrasound diagnosis and physics-informed elastography reconstructionn#1368589
- Deep Learning-Based Segmentation of Peritoneal Cancer Index Regions from CT Imaging#984150
Record · ID 1406793
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive