Researchers validated AI-driven facial blurring software to safeguard privacy during remote interventional radiology procedures.
Key Details
- 1AI-based facial blurring software, originally developed for TV, was adapted for IR teleproctoring to ensure patient privacy.
- 2The BlurOn system from Nippon Television Network and NTT Data removes identifiers before video leaves the IR suite.
- 3Proof-of-concept and multi-institutional clinical trials included thoracic draining, central venous port insertions, and hepatic arterial infusion procedures.
- 4All four procedures completed successfully; video quality and delays were satisfactory for remote guidance and education.
- 5Both operators and remote viewers found the setup straightforward and workflow-friendly, noting educational and practical benefits.
Why It Matters
Addressing privacy concerns is a critical step for broader adoption of remote telementoring in IR, potentially expanding expert access and advanced procedure dissemination globally. This AI tool may help standardize secure, privacy-compliant teleproctoring workflows in interventional practice.
Source
AuntMinnie
Related News
•Radiology Business
Experts Urge Development of Generalist Radiology AI to Cut Costs and Improve Care
Leading scientists advocate for broader, generalist radiology AI models to overcome limitations of narrow, single-task solutions.
•AuntMinnie
General LLMs Show Promise in Detecting Critical Findings in Radiology Reports
Stanford and Mayo Clinic Arizona researchers demonstrated that LLMs like GPT-4 can categorize critical findings in radiology reports using few-shot prompting.
•AuntMinnie
Experts Outline Framework and Benefits for Generalist Radiology AI
Researchers propose key features and benefits for implementing generalist radiology AI (GRAI) frameworks over narrow AI tools.