3D Bone Model Registration with Projected Point Sets
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Solution Overview
Problem
Existing methods for registering a three-dimensional (3D) model of a bone with a real bone during orthopedic surgery face challenges in ensuring accurate alignment due to inaccuracies in registration points, leading to suboptimal transformation matrices.
Innovation Solution
A registration method that adjusts a first image model using a previous transformation matrix, projects registration points onto a second image model, and registers these points to obtain a second transformation matrix, utilizing closest distance projection points and objective functions to minimize pose differences, with iterative refinement using rough and fine registration points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If registration points are used to align the 3D model with the real bone, then alignment is achieved, but inaccuracies in registration points lead to suboptimal transformation matrices and reduced registration accuracy
Solution Approach 1:
The patent introduces a projection point set as an intermediary between the registration point set and the second image model. Instead of directly using registration points on the real bone to determine transformation, the system projects these points onto the image model to create projection points, which then serve as the basis for calculating the transformation matrix. This intermediary step reduces the direct dependence on potentially inaccurate registration points while maintaining the alignment function.
Solution Approach 2:
The patent creates a copy of the registration point set by projecting it onto the second image model to generate a projection point set. This copied point set retains the spatial relationships and transformation information of the original registration points but exists in the image space where it can be more reliably used for calculating the transformation matrix, thereby reducing the impact of registration point inaccuracies.
2Measurement precision
If more registration points are used to improve alignment accuracy, then precision increases, but the complexity of the registration process and computational requirements increase
Solution Approach 1:
The patent performs preliminary projection of the registration point set onto the second image model to create the projection point set before calculating the transformation matrix. This preliminary action transforms the problem space from physical coordinates to image coordinates, simplifying subsequent calculations and reducing the complexity of the registration process while maintaining or improving precision.
Solution Approach 2:
The patent segments the registration process into distinct stages: obtaining the first transformation matrix from previous registration, adjusting the first image model to create the second image model, projecting registration points to create projection points, and finally calculating the second transformation matrix. This segmentation allows each stage to be optimized independently, reducing overall process complexity.
Data Source
AI summary
The present application relates to a registration method and apparatus, and a computer device and a readable storage medium. The method comprises: acquiring a first image model of an object to be registered, which is used in previous registration, and a first transformation matrix, which is obtained in the previous registration; for the current registration, adjusting the first image model based on the first transformation matrix, so as to obtain a second image model; projecting a first registration point set on the surface of said object onto the surface of the second image model, so as to obtain a projection point set; and registering the first registration point set and the projection point set, so as to obtain a second conversion matrix.