Voxel Tagging with Fiber Optic Shape Sensing
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Solution Overview
Problem
Current medical imaging modalities often fail to accurately digitize the geometry of internal cavities, making it difficult to understand and analyze their features, especially during interventional procedures where precise shape sensing and temporal data are crucial.
Innovation Solution
A voxel tagging system employing fiber optic shape sensing and localization technology, which uses optical fibers to sense strain and interpret positions within a volume, associating health parameter data with timestamps to create a three-dimensional representation of internal structures, enabling accurate reconstructions and visualization of dynamic anatomical changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fiber optic shape sensing is used to accurately map internal cavity geometry, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The internal cavity mapping is divided into discrete voxel elements that can be independently tagged and processed. The fiber optic sensor is segmented into multiple measurement points along its length, allowing distributed strain sensing at different locations. This segmentation enables accurate geometry reconstruction while keeping each individual voxel processing simple.
Solution Approach 2:
A computer-readable medium acts as an intermediary to store and process the relationship between fiber optic strain measurements and corresponding voxel positions. The intermediary system correlates shape data with health parameter data, eliminating the need for complex real-time processing hardware and reducing overall system complexity while maintaining high measurement precision.
2Loss of information
If time-resolved reconstructions are generated to capture dynamic anatomical changes, then information completeness is improved, but data processing complexity increases
Solution Approach 1:
Voxels are pre-tagged with health parameter data and timestamps during the data acquisition phase, before any complex processing is required. This preliminary tagging organizes temporal information in a structured format that simplifies subsequent reconstruction and analysis, reducing the complexity of time-resolved data processing.
Solution Approach 2:
The system adds a temporal dimension to the spatial voxel data by associating each voxel with timestamp and health parameter information. This transforms the data from simple 3D geometry into 4D spatio-temporal representations, allowing dynamic anatomical changes to be captured and analyzed without requiring complex processing algorithms.
3Measurement precision
If ultra-dense point cloud data is acquired at high data rates, then measurement precision is improved, but productivity decreases due to processing bottlenecks
Solution Approach 1:
The system extracts only the essential geometric and temporal information from ultra-dense point cloud data by mapping points to a voxel grid structure. This extraction process removes redundant data while preserving the critical shape and temporal characteristics, enabling high-precision measurements to be processed more efficiently.
Solution Approach 2:
Instead of processing the original ultra-dense point cloud data directly, the system creates a simplified voxel-based copy that represents the same geometric information in a more compact and computationally efficient format. This copying approach maintains measurement precision while dramatically improving processing throughput and productivity.
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 system provides accurate, time-resolved reconstructions of medical device shapes and internal cavity geometry, allowing for improved understanding and visualization of anatomical structures and functions, facilitating better diagnostic and therapeutic interventions.
Implementation Method 1
a sensing enabled device having an optical fiber configured to sense induced strain within the device
Data Source
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AI summary
A voxel tagging system (100) includes a sensing enabled device (104) having an optical fiber (126) configured to sense induced strain within the device (Bragg grating sensor). An interpretation module (112) is configured to receive signals from the optical fiber interacting with an internal organ, e.g. heart, and to interpret the signals to determine positions visited by the at least one optical fiber within the internal organ. A data source (152, 154) is configured to generate data associated with an event or status, e.g. respiration, ECG phase, time stamp, etc.. A storage device (116) is configured to store a history (136) of the positions visited in the internal organ and associate the positions with the data generated by the data source (152, 154).