AI RESEARCH
Autonomous Skeletal Landmark Localization towards Agentic C-Arm Control
arXiv CS.CV
•
ArXi:2604.18740v1 Announce Type: new Purpose: Automated C-arm positioning ensures timely treatment in patients requiring emergent interventions. When a conventional Deep Learning (DL) approach for C-arm control fails, clinicians must revert to manual operation, resulting in additional delays. Consequently, an agentic C-arm control framework based on multimodal large language models (MLLMs) is highly desirable, as it can incorporate clinician feedback and use reasoning to make adjustments toward accurate positioning.