Pulmonary endoscopy · Endobronchial ultrasound
Locate the node. Characterize the finding.
AI assistance for the detection and characterization of lymph nodes, differentiating benign and malignant findings during and in previously acquired EBUS images.
EBUS · LIVE IMAGE AI DETECTION
01 · Intended use
AI assistance for lymph-node assessment in EBUS.
Smart Node EBUS® assists with detection and characterization of lymph nodes in live and previously acquired endobronchial ultrasound images.
The platform localizes the target with a bounding box, differentiates benign and malignant findings, and prepares structured information for clinician review.
AI
The clinical challenge
EBUS lymph-node assessment remains operator dependent.
Accurate localization and characterization are central to nodal staging, yet ultrasound appearance can be difficult to interpret consistently across operators, devices and clinical settings.
“The opportunity is to support more reproducible detection, characterization and targeted sampling.”
02
How it works
One continuous path from examination to report.
The interface follows the same logic as the technology: information progressively resolves as it moves through the analysis.
EBUS acquisition
Live or previously acquired endobronchial ultrasound images enter the analysis workflow.
Node localization
The AI identifies lymph-node regions and places a precise bounding box around the target.
Feature analysis
Ultrasound appearance is analyzed across the selected lymph-node region.
Characterization
The finding is differentiated as benign or malignant for clinician review.
Structured report
The result is organized into a standardized AI-driven diagnostic report.
AI capabilities
Designed for focused, reproducible EBUS assessment.
90.6%
Accuracy reported for malignant lymph-node characterization
Lymph-node detection
Automatically localizes lymph nodes in endobronchial ultrasound images.
Benign or malignant characterization
Supports differentiation of lymph-node findings using AI-assisted image analysis.
Precision targeting
Displays bounding boxes that support focused review and biopsy targeting.
Real-time and retrospective analysis
Works during EBUS examinations and with previously acquired images.
Standardized reporting
Generates structured AI-driven results for clinician validation.
03
Scientific validation
Clinical evidence for AI-assisted EBUS lymph-node assessment.
Artificial Intelligence and Endobronchial Ultrasound for Lymph-Node Detection and Characterization: A Pioneer Multicenter Transatlantic Study
Journal of Clinical Medicine · 2026 · Multicenter and multidevice validation
Read publication ↗Clinical benefits
Focused detection. More consistent characterization.
01
Earlier and more accurate detection of lymph nodes
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Product performance target above 95% diagnostic accuracy
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Real-time and post-procedural image analysis
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Precision biopsy targeting supported by bounding boxes
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Fewer unnecessary procedures and greater workflow efficiency
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Standardized AI-driven diagnostic reports
↗Smart Node EBUS®
Bring intelligent lymph-node assessment to EBUS.
Talk to our team ↗The products and technologies showcased are part of our advanced research and development pipeline and may be pending regulatory approval in your market.