Broken Bone 3D Reconstruction Using Automatic Landmark Alignment
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Solution Overview
Problem
Existing methods for determining anatomical fracture reconstruction in broken bones require significant human input and expertise, leading to inefficiencies and potential inaccuracies, especially in complex fractures involving numerous small fragments.
Innovation Solution
An automated method for bone reconstruction that uses automatic landmark detection and a refinement algorithm to align 3D surface models, eliminating the need for manual intervention and ensuring accurate alignment of bone fragments regardless of fracture complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If interactive or semi-automatic bone fragment alignment tools are used, then the surgeon can manually control the reconstruction process, but the process becomes time-consuming and requires significant human expertise
Solution Approach 1:
The system performs self-alignment of bone fragments through automated landmark detection and registration. The algorithm automatically identifies corresponding landmarks on bone fragments, establishes coordinate transformations, and reconstructs the bone without requiring manual surgeon intervention for alignment operations.
Solution Approach 2:
The patent replaces manual mechanical alignment operations with automated computational algorithms. Instead of requiring the surgeon to manually track and align bone fragments using interactive tools, the system uses image processing algorithms to automatically detect landmarks, compute transformations, and perform the alignment.
2Manufacturing precision
If manual landmark identification and selection is required, then the surgeon can adjust the reconstruction based on expertise, but the process becomes complex and time-consuming
Solution Approach 1:
The system automatically detects and registers landmarks on bone fragment surfaces without requiring manual selection. The algorithm autonomously identifies anatomical landmarks, establishes their correspondence between fragments, and performs the alignment registration, eliminating the need for complex manual interaction.
3Productivity
If automated reconstruction methods are used, then the process becomes faster and more efficient, but the accuracy may be compromised without human expertise
Solution Approach 1:
The patent replaces manual alignment operations with automated computational algorithms that perform landmark detection, coordinate transformation, and fragment registration. This substitution maintains high accuracy by using robust image processing techniques while achieving rapid automated reconstruction.
Data Source
AI summary
The present disclosure relates to the field of medical image processing and, more in particular, to a method for determining an anatomical fracture reconstruction based on one or more medical images of a broken bone, and a system configured for the same. According to an aspect the method comprises the steps of: receiving medical image data associated with the broken bone, identifying the plurality of bone fragments in the medical image data, generating a plurality of 3D surface models that virtually represent the bone fragments; registering a plurality of landmarks matching the surface models; generating a reconstructed model representing a reconstructed form of the broken bone by selecting at least two landmarks; generating a template model representing an optimal alignment of the surface models; repositioning the surface models to align at the selected landmarks set using the template model as reference; iteratively refining the reconstructed model by selecting different landmarks; changing the position of the surface models to align at the different landmarks; evaluating a quality measure that quantifies how changing the position affects the quality of the reconstructed model until a stopping condition is satisfied; and determining an anatomical reconstruction of the broken bone by comparing the position of the identified bone fragments in the medical image data with the position of the corresponding surface models in the reconstructed model.