3D Image Alignment via Common Coordinate System
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Solution Overview
Problem
Existing methods for calculating the positional relationship between multiple three-dimensional images of the same patient are inefficient due to exponential increases in calculations and difficulties in defining transformation functions for images outside the subject range, leading to complex calculations and large computational loads.
Innovation Solution
An image processing device and method that sets a three-dimensional common coordinate system, establishes correspondence relationships between image pixels and the coordinate system, and calculates positional relationships using these correspondences, allowing for efficient alignment and storage of image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transformation functions are calculated for all combinations of three-dimensional images, then positional relationships can be accurately determined, but the number of calculations increases exponentially
Solution Approach 1:
The patent introduces a common coordinate system as an intermediary reference framework. Instead of calculating transformation functions between all pairs of images (direct approach), the system establishes correspondence relationships between each image and the common coordinate system, then derives positional relationships through this intermediate reference. This mediator approach reduces computational complexity from exponential to linear scale while maintaining measurement accuracy.
Solution Approach 2:
The patent segments the complex task of determining all pairwise positional relationships into separate, manageable correspondence relationship calculations. Each three-dimensional image is independently processed to establish its correspondence relationship with the common coordinate system, then these segmented results are combined to determine any required positional relationships. This segmentation transforms the exponential complexity problem into a series of simpler, independent calculations.
2Productivity
If transformation functions are used to define three-dimensional images, then positional relationships can be calculated efficiently, but images outside the subject range of the reference image cannot be defined
Solution Approach 1:
The common coordinate system serves as a universal reference framework that can accommodate three-dimensional images of any subject range. Rather than being limited to a specific reference image's field of view, the coordinate system acts as a multi-functional anchor that can establish correspondence relationships with images covering the entire patient body, making the system adaptable to various imaging scenarios.
Solution Approach 2:
The patent transitions from a reference-image-centered approach (two-dimensional transformation functions) to a coordinate-system-centered approach (three-dimensional spatial correspondence). This dimensional shift allows the system to handle images beyond the reference image's subject range by establishing spatial correspondences in the broader coordinate space rather than being constrained by the reference image's limitations.
3Adaptability or versatility
If a common coordinate system is established for all three-dimensional images, then positional relationships can be calculated for any image combination, but the complexity of setting up the coordinate system increases
Solution Approach 1:
The common coordinate system is automatically constructed by processing the correspondence relationships derived from the three-dimensional images themselves. The system uses the image data and their spatial relationships to self-configure the coordinate system, eliminating the need for manual setup or pre-defined complex transformation parameters. This self-service approach simplifies the setup process while maintaining high adaptability.
Solution Approach 2:
The correspondence relationships between images and the common coordinate system are established in advance during the image acquisition and processing phase. By performing this preliminary action before final positional relationship calculations are needed, the system prepares the coordinate framework ahead of time, reducing the complexity of subsequent operations and enabling flexible image combination analysis.
Data Source
AI summary
A three-dimensional common coordinate system is defined and a first correspondence relationship between each pixel of a first three-dimensional image which has at least a portion of a human body as a subject and coordinates on the common coordinate system is set. A second three-dimensional image which has at least a portion of the human body as a subject that at least partially overlaps the subject in the first three-dimensional image is aligned with the first three-dimensional image to calculate a correspondence relationship between pixels of the first three-dimensional image and the second three-dimensional image. A second correspondence relationship between each pixel of the second three-dimensional image and coordinates on the common coordinate system is calculated on the basis of the calculated correspondence relationship and the set first correspondence relationship. The first correspondence relationship and the second correspondence relationship are stored.