Lymphatic Vessel Visualization via OCT Scattering Compensation
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Solution Overview
Problem
Current imaging techniques struggle to effectively visualize lymphatic vessels in vivo due to the low scattering nature of lymph fluid, leading to challenges in segmentation and false alarms, especially with conventional optical coherence tomography (OCT) methods which require highly scattering samples.
Innovation Solution
The use of an automatic filtering technique and vesselness model, specifically Hessian multi-scale filters, combined with scattering attenuation compensation and contrast enhancement, to detect and segment lymphatic vessels in OCT images, allowing for noninvasive, label-free visualization of lymphatic vessels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional OCT methods are used to image lymphatic vessels, then the imaging system is simple and noninvasive, but the visualization quality is poor due to low scattering nature of lymph fluid
Solution Approach 1:
The patent changes the optical parameters of the imaging system by using a swept-source OCT with wavelength tuning capabilities and adjusting the scanning parameters to optimize light interaction with lymphatic vessels. The system modifies imaging depth, resolution, and contrast parameters to enhance visualization of low-scattering lymph fluid without requiring invasive contrast agents.
Solution Approach 2:
The patent employs composite signal processing techniques that combine multiple OCT signal components and processing algorithms to create enhanced images. By integrating motion artifact correction, depth compensation, and multi-scale vessel detection algorithms, the system achieves superior visualization quality from the raw OCT data.
2Measurement precision
If conventional OCT imaging is used, then no contrast agents are needed, but segmentation accuracy is low and false alarms occur
Solution Approach 1:
The patent applies multi-scale vessel segmentation algorithms that divide the OCT image analysis into different spatial scales. By processing images at multiple resolutions and scales, the system can accurately distinguish lymphatic vessels from surrounding tissue and blood vessels, reducing segmentation errors and false positives.
Solution Approach 2:
The system implements feedback mechanisms where segmentation results are continuously refined through iterative processing. Motion artifact correction and depth compensation feedback loops adjust the imaging and processing parameters in real-time to maintain high segmentation accuracy and reduce false alarms.
3Reliability
If motion artifacts are present in OCT images, then the imaging process remains simple and quick, but image quality and diagnostic utility deteriorate
Solution Approach 1:
The patent applies preliminary motion artifact correction and depth compensation processing to OCT images before further analysis. By pre-correcting these artifacts using reference measurements and calibration data, the system maintains high image quality without requiring complex real-time intervention during imaging.
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
This approach enables robust and accurate visualization of lymphatic vessels, reducing segmentation errors and false alarms, and provides a three-dimensional model of lymphatic vessels, improving the understanding of lymphatic system functions and its role in diseases such as cancer and inflammatory conditions.
Implementation Method 1
conventional optical coherence tomography (OCT) methods which require highly scattering samples
Data Source
AI summary
The present technology relates generally to systems and methods for in vivo visualization of lymphatic vessels. A system includes an optical coherence tomography (OCT) device and a computing device coupled to the OCT device configured to cause the OCT device to perform an OCT scan, generate image data in response to the OCT scan, and apply an eigendecomposition filter to the image data to produce processed image data. Alternatively or in addition, the computing device can compensate for scattering attenuation along an optical axis of the OCT scan in the image data set to generate compensated image data, enhance contrast of the compensated image data along a cross-section substantially orthogonal to the optical axis to generate contrast-enhanced image data, and identify at least one lymphatic vessel in the image data.