AI-Guided Tracheal OCT Mapping for Real-Time 3D Imaging
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Solution Overview
Problem
Current imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) are not well suited for real-time imaging of the trachea due to their low temporal resolution, and manual interpretation of ultra-fast optical coherence tomography (UF-OCT) images is time-consuming and subjective.
Innovation Solution
A system utilizing ultrafast optical coherence tomography (UF-OCT) combined with artificial intelligence (AI) for real-time mapping of the trachea, capturing high-resolution 3D images at very high frame rates and analyzing them in real time to provide accurate anatomical and disease status predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computed tomography or magnetic resonance imaging is used to image the trachea, then clear anatomical details are provided, but temporal resolution is low and real-time imaging is not achieved
Solution Approach 1:
The patent replaces traditional mechanical/X-ray-based CT and MRI imaging systems with optical coherence tomography technology. UF-OCT uses light interference principles to achieve high-speed, high-resolution imaging of the trachea in real-time, eliminating the temporal resolution limitations of CT and MRI while maintaining anatomical detail clarity.
2Speed
If ultra-fast optical coherence tomography is used to capture high-resolution 3D images, then imaging speed and resolution are improved, but manual interpretation becomes time-consuming and subjective
Solution Approach 1:
The patent introduces an artificial intelligence module as an intermediary between the UF-OCT imaging system and the clinician. The AI module automatically analyzes the high-resolution 3D images captured by UF-OCT, providing objective interpretations and reducing the time required for image analysis while maintaining diagnostic accuracy.
Solution Approach 2:
The patent replaces manual human interpretation of medical images with an AI-based automated analysis system. This substitution eliminates subjectivity and time-consuming manual review while preserving the high imaging speed and resolution capabilities of UF-OCT.
3Measurement precision
If manual interpretation of UF-OCT images is performed, then detailed analysis is possible, but the process is time-consuming and subjective
Solution Approach 1:
The patent introduces an artificial intelligence module as an intermediary between the high-resolution UF-OCT imaging system and the clinician. The AI module automatically analyzes the captured images, providing objective interpretations and reducing the time required for image analysis while maintaining diagnostic accuracy.
Solution Approach 2:
The patent enables the imaging system to perform self-analysis through integrated AI algorithms. The system automatically processes and interprets its own output images without requiring extensive manual review, thereby reducing analysis time and eliminating subjectivity while preserving measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time, accurate, and objective mapping of the trachea, facilitating diagnosis, surgery, and monitoring by providing high-resolution 3D images and AI-driven predictions.
Implementation Method 1
OCT employs low-coherence interferometry to measure changes in back scattered light to differentiate areas of blood flow from the areas of static flow
Implementation Method 2
Optical coherence tomography (OCT) is an image technique that uses low-coherence light, typically near-infrared light, to capture micrometer-resolution, two and three-dimension images from within optical scattering media such as biological tissue
Data Source
AI summary
A system and method are disclosed for real-time mapping of a target hollow internal body structure each as the trachea using ultrafast swept-source optical coherence tomography (SS-OCT) and artificial intelligence (AI). The system includes an SS-OCT imaging device that captures high-resolution 3D images of the trachea at very high frame rates, and an AI module that analyzes and interprets the images in real time. The AI module can recognize patterns and features in the images and make predictions about the tracheal anatomy or disease status. The system can provide a detailed, up-to-date model of the trachea in real time, and can be used for a variety of applications including diagnosis, surgery, and monitoring.