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Research questionHow can multiclass semantic segmentation separate devices, anatomy, and background in catheterization angiograms?Catheterization angiograms contain several structures that must be distinguished at the pixel level. Background dominance and differences between devices and vessels make multiclass labeling more difficult than binary foreground segmentation.
AI
Computer Vision
Health
Image & Video Processing
Machine Learning
Research Paper
Latest papersRecent research connected to this question, newest first.Dual-Part Multi-Lateral Branched Network for Multi-Class Segmentation in Cardiovascular Catheterization AngiogramsThe source evaluates a multiclass segmentation architecture on angiograms from phantom models, a synthetic human-simulated aorta, and an animal model. Evidence is limited to separating guidewire, catheter, vessel, and background pixels in those settings and does not establish clinical human deployment.research paper · Sep 4, 2026
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