Structured Light Optical Tracking for Real-Time 3D Anatomy Mapping
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Solution Overview
Problem
Conventional optical tracking systems in surgical environments face inefficiencies and inaccuracies when using visible light, particularly in CPU-intensive image analysis and unreliable fiducial marker detection, leading to lower update rates and registration challenges.
Innovation Solution
An optical tracking system utilizing RGB color sensors and a structured light module projects patterns in the NIR spectrum to capture depth maps, enabling accurate three-dimensional surface reconstruction and tracking of anatomical structures, with processors calibrating poses and stitching multiple images for enhanced precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If visible light image analysis is used for optical tracking, then the system can capture color information and provide visual feedback, but the CPU-intensive processing reduces update rates and lowers tracking reliability
Solution Approach 1:
The patent segments the tracking task by using dedicated fiducial marker detection algorithms that process only specific marker patterns rather than analyzing entire color images. This selective processing maintains visual information for markers while reducing overall computational load, thereby improving update rates without complete loss of visual tracking data
Solution Approach 2:
The patent replaces CPU-intensive visible light image analysis with optimized algorithms that leverage the specific properties of fiducial markers. By substituting general-purpose image processing with specialized marker detection routines, the system achieves higher update rates while preserving essential tracking information
2Loss of information
If visible light image analysis is used for fiducial marker detection, then color information is available for verification, but detection reliability decreases due to CPU-intensive processing
Solution Approach 1:
The patent extracts and processes only the essential fiducial marker features rather than analyzing complete color images. By taking out the specific marker detection task from general image analysis, the system achieves more reliable and consistent marker detection with reduced computational overhead, improving overall tracking reliability
Solution Approach 2:
The patent changes the processing parameters by optimizing detection algorithms for specific marker characteristics rather than general color image properties. This parameter optimization enables more reliable marker detection at lower computational costs, enhancing tracking reliability without requiring full color image processing
3Measurement precision
If conventional optical tracking systems use NIR spectrum with high intensity sources and low integration time, then noise is reduced in images, but the system complexity increases with synchronized emission and integration requirements
Solution Approach 1:
The patent applies preliminary synchronization of the NIR light source emission with the CMOS image sensor integration time. By pre-coordinating the timing of light emission and sensor exposure, the system achieves optimal signal-to-noise ratio without requiring complex real-time synchronization mechanisms during operation
Solution Approach 2:
The patent implements a system where the NIR light source and CMOS sensor work in a self-synchronized manner through their inherent operational cycles. The periodic emission and integration naturally align without requiring external complex synchronization control, reducing device complexity while maintaining high 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
This approach improves surgical efficiency by providing real-time, accurate tracking and deeper digitalization, allowing for augmented reality overlays and improved surgical workflow, particularly in computer-assisted surgery systems like NAVIO.
Implementation Method 1
an optical tracking device with a structured light module and at least one optical module including an image sensor and spaced from the structured light module at a known distance. The structured light module projects patterns in the NIR spectrum
Implementation Method 2
The structured light module projects patterns in the NIR spectrum to capture depth maps, enabling accurate three-dimensional surface reconstruction
Data Source
AI summary
A system is disclosed that includes an optical tracking device and a surgical computing device. The optical tracking device includes a structured light module and an optical module that includes an image sensor and is spaced from the structured light module at a known distance. The surgical computing device includes a display device, a non-transitory computer readable medium including instructions, and processor(s) configured to execute the instructions to generate a depth map from a first image captured by the image sensor during projection of a pattern into a surgical environment by the structured light module. The pattern is projected in a near-infrared (NIR) spectrum. The processor(s) are further configured to execute the stored instructions to reconstruct a 3D surface of anatomical structure(s) based on the generated depth map. Additionally, the processor(s) are configured to execute the stored instructions to output the reconstructed 3D surface to the display device.