3D Tracer-to-Surface Distance Mapping for Resection Accuracy
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Solution Overview
Problem
Existing dual-modality imaging systems struggle to accurately determine the minimum distance between a tracer distribution and an anatomical surface, crucial for evaluating resection accuracy in tissue specimens, due to large data sets and 2D visualization limitations.
Innovation Solution
A computer-implemented method that co-registers 3D functional and anatomical image data, selects tracer and anatomical boundary voxels, calculates Euclidean distances, and generates a 3D minimum distance map, which can be displayed as color-coded or topographic, aiding quick assessment of resection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D functional and anatomical image data are co-registered and processed to determine minimum distances, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex task of minimum distance determination into distinct processing steps: receiving functional image data, receiving anatomical image data, co-registering the datasets, selecting tracer boundary voxels, selecting anatomical boundary voxels, calculating distances, and generating visual displays. This segmentation manages complexity by breaking down the overall process into manageable, modular operations that can be performed sequentially by the processing system.
Solution Approach 2:
The patent introduces intermediate structures to facilitate the complex processing: coordinate systems serve as intermediaries for co-registration, tracer boundary voxels and anatomical boundary voxels serve as intermediate representations of the respective datasets, and the minimum distance map serves as an intermediate visual product. These intermediaries simplify the overall task by creating structured representations at each processing stage.
2Measurement precision
If 3D image data are processed to determine minimum distances, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary actions by co-registering the functional and anatomical image datasets before distance calculation, establishing a standardized coordinate framework in advance. The system also pre-identifies and selects tracer boundary voxels and anatomical boundary voxels as discrete sets, preparing the data structures beforehand. These preliminary actions organize the data efficiently, enabling faster distance computations when needed.
Solution Approach 2:
The patent replaces manual measurement and analysis methods with automated computational processing. The computer-implemented system automatically performs co-registration, voxel selection, distance calculations, and visual display generation, eliminating time-consuming manual operations and providing rapid, precise measurements that would be impractical to perform manually on complex 3D datasets.
3Ease of operation
If 2D slices or projections are used for visualization, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent transitions from 2D visualization limitations to 3D spatial representation by generating and displaying minimum distance maps that preserve three-dimensional spatial relationships. The system calculates distances in 3D space and presents them in a manner that maintains spatial context, allowing users to visualize and interpret minimum distances accurately without the distortion inherent in 2D projections while still providing operational simplicity through graphical display.
Solution Approach 2:
The patent employs color-coded visual displays to represent minimum distance values, where different colors indicate different distance ranges. This color-coding system provides intuitive, easy-to-interpret visualization that maintains measurement precision by preserving the actual distance values while presenting them in a visually accessible format that is simple to operate with and interpret.
Data Source
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AI summary
Computer-implemented method for determining a minimum distance between a tracer distribution and an anatomical surface, the method comprising the steps of receiving 3D functional image data of a tissue specimen including a tracer from a functional imaging module, receiving 3D anatomical image data from an anatomical imaging module and co-registering said 3D functional image data and said 3D anatomical image data.