Organ-Specific Coordinate System for 3D Medical Imaging Localization
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Solution Overview
Problem
Current 3D imaging localization methods in medical imaging face challenges in accurately describing the location of lesions and aligning anatomical structures across different examinations due to deformable soft tissues and patient positioning variations, leading to inadequate precision and reproducibility.
Innovation Solution
A smart localization system that loads and segments 3D imaging datasets to define structures, uses organ-specific coordinate systems, and determines corresponding coordinates across time points, enabling precise localization of anatomical features through segmentation, reference points, and artificial intelligence, allowing for accurate tracking of lesions and anatomical changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional matrix-based localization (slice number and pixel coordinate) is used, then the system is simple to operate, but the measurement precision of anatomical localization deteriorates due to deformable soft tissues and patient positioning variations
Solution Approach 1:
The patent segments the 3D imaging dataset to define specific anatomical structures (organs, lesions, etc.) and establishes organ-specific coordinate systems for each segmented structure. This segmentation approach enables precise tracking of anatomical features across different time points by maintaining consistent coordinate references within each structure, thereby improving localization precision without requiring overly complex manual alignment procedures
Solution Approach 2:
The patent introduces a smart localization system that acts as an intermediary between traditional imaging display and precise anatomical localization. This system automatically determines corresponding coordinates across different examinations by utilizing segmented structure definitions and coordinate system transformations, eliminating the need for manual scrolling and visual alignment while improving measurement precision
2Productivity
If manual scrolling and visual alignment are used for localization across different examinations, then the device complexity is low, but the productivity deteriorates due to time-consuming manual processes
Solution Approach 1:
The patent performs preliminary segmentation of 3D imaging datasets to define anatomical structures and establish coordinate systems before the localization process. By pre-defining structures and their coordinate references, the system enables rapid automatic localization across different time points without requiring time-consuming manual scrolling and visual alignment, thereby significantly improving productivity
Solution Approach 2:
The smart localization system performs self-service by automatically determining corresponding coordinates between different examinations using the pre-established segmented structure definitions and coordinate systems. The system autonomously matches anatomical features across time points without requiring manual intervention, thereby eliminating time-consuming manual processes and improving localization efficiency
3Measurement precision
If organ-specific coordinate systems are implemented, then the measurement precision of lesion tracking is improved, but the ease of operation deteriorates due to increased system complexity
Solution Approach 1:
The smart localization system serves as an intermediary that automatically handles the complexity of organ-specific coordinate systems. It performs coordinate transformations and structure matching in the background, presenting simplified results to the user. This approach maintains high lesion tracking precision through accurate coordinate referencing while shielding users from the operational complexity of managing multiple organ-specific coordinate systems
Data Source
AI summary
This patent includes a method and apparatus for assigning a three-dimensional coordinate system to a segmented structure of a three-dimensional imaging examination of a tangible volume containing discrete structures. The boundary of a segmented structure, which corresponds to a discrete structure is determined through a segmentation algorithm. The assigned three-dimensional coordinate system has an origin and a set of coordinate axes. This allows each voxel within the segmented structure of the three-dimensional imaging examination to have a precise coordinate. This provides improved longitudinal analysis and more precise localization within the segmented structure.