Lumen Edge Detection in Optical Coherence Tomography Images
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Solution Overview
Problem
Current OCT image processing techniques face challenges in accurately detecting lumen edges due to non-uniform illumination, noise, and artifacts such as stent reflections and guidewires, leading to unreliable results, especially in complex geometries and real-world conditions.
Innovation Solution
The proposed method employs a range-based peak search in polar coordinates for each A-line, combining pixel intensity and gradient values to define significant edges, and uses localized calculations to identify and interpolate lumen edges, avoiding global threshold assumptions and addressing uneven illumination and artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If global threshold methods are used for lumen edge detection, then the detection process is simple, but the accuracy deteriorates due to non-uniform illumination and artifacts
Solution Approach 1:
The patent divides the image processing into multiple stages: initial edge detection using gradient methods, artifact identification and removal, and refined lumen edge detection. This segmentation allows each stage to focus on specific tasks, improving overall accuracy while maintaining manageable complexity
Solution Approach 2:
The patent applies local adaptive thresholding instead of global thresholding, where threshold values are adjusted locally based on illumination conditions and tissue characteristics. This allows accurate edge detection in regions with non-uniform illumination and near metal artifacts without compromising the entire image
2Device complexity
If image processing algorithms assume uniform illumination, then the algorithms are simpler to implement, but the reliability deteriorates in real-world conditions with varying vessel curvature and metal objects
Solution Approach 1:
The patent dynamically adjusts processing parameters such as threshold values, gradient calculation windows, and artifact suppression strength based on local image characteristics including illumination intensity, vessel curvature, and presence of metal artifacts. This adaptability maintains reliability across diverse clinical conditions
Solution Approach 2:
The patent implements dynamic artifact suppression that adapts to the presence and characteristics of metal objects detected in the image. The suppression strength and method are adjusted in real-time based on artifact detection results, maintaining reliability in the presence of varying metal implants and guidewires
3Measurement precision
If neighboring images are correlated to smooth lumen edges, then the accuracy improves, but the processing time increases
Solution Approach 1:
The patent applies correlation smoothing selectively rather than uniformly across all images. Neighboring image correlation is applied primarily at boundaries and regions where edge detection uncertainty is high, rather than processing every pixel in every image, thus improving accuracy where needed while limiting time consumption
Solution Approach 2:
The patent performs preliminary artifact removal and initial edge detection before applying correlation smoothing. This preliminary processing reduces the complexity of subsequent correlation operations by eliminating sources of error early, allowing faster and more focused smoothing operations
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 improves the accuracy and reliability of lumen edge detection by correlating neighboring images, reducing outliers, and providing consistent results even in challenging conditions, such as varying vessel curvature and proximity to metal objects.
Implementation Method 1
A light from a light source delivers and splits into a reference arm and a sample (or measurement) arm with a splitter (e.g., a beamsplitter). A reference beam is reflected from a reference mirror (partially reflecting or other reflecting element) in the reference arm while a sample beam is reflected or scattered from a sample in the sample arm. Both beams combine (or are recombined) at the splitter and generate interference patterns.
Implementation Method 2
Single mode fibers are commonly used for OCT optical probes, and double clad fibers are also commonly used for fluorescence and/or spectroscopy.
Data Source
AI summary
One or more devices, systems, methods and storage mediums for performing optical coherence tomography (OCT) while detecting one or more lumen edges, one or more stent struts, and/or one or more artifacts are provided. Examples of applications include imaging, evaluating and diagnosing biological objects, such as, but not limited to, for Gastro-intestinal, cardio and/or ophthalmic applications, and being obtained via one or more optical instruments, such as, but not limited to, optical probes, catheters, capsules and needles (e.g., a biopsy needle). Preferably, the OCT devices, systems methods and storage mediums include or involve a method, such as, but not limited to, for removing the detected one or more artifacts from the image(s).