Summary of Ai-driven View Guidance System in Intra-cardiac Echocardiography Imaging, by Jaeyoung Huh and Paul Klein and Gareth Funka-lea and Puneet Sharma and Ankur Kapoor and Young-ho Kim
AI-driven View Guidance System in Intra-cardiac Echocardiography Imaging
by Jaeyoung Huh, Paul Klein, Gareth Funka-Lea, Puneet Sharma, Ankur Kapoor, Young-Ho Kim
First submitted to arxiv on: 25 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel AI-driven view guidance system is proposed to assist operators in navigating intra-cardiac echocardiography (ICE) imaging without requiring specialized knowledge. The system operates in a continuous closed-loop with human-in-the-loop feedback, modeling the relative position and orientation vectors between arbitrary views and clinically defined ICE views in a spatial coordinate system. By predicting and updating necessary catheter manipulations, the system ensures seamless integration into existing clinical workflows. Simulation-based performance evaluation using real clinical data achieved an 89% success rate, while semi-simulation human-in-the-loop testing validated feasibility. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new AI tool helps doctors use special heart imaging machines called intra-cardiac echocardiography (ICE) cameras without needing years of practice. The system uses computer algorithms to guide the camera’s movement and make sure it gets the right pictures. It does this by predicting how much the camera needs to move and when, so the doctor can easily get the best views of the heart. This tool could make ICE imaging faster and more accurate, which is important for people who need heart procedures. |
