Patient-Specific Medical Implant Planning via Shape Feature Segmentation
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Solution Overview
Problem
Current methods for producing patient-specific medical implants lack efficient automation and adequate anatomical alignment, leading to potential integration issues and complications such as inflammation, wear, and increased follow-up treatment costs due to insufficient spatial resolution and lack of additional medical information.
Innovation Solution
A method involving image data segmentation to define shape features corresponding to tissue structures, comparing these features with stored data sets to create a production model that aligns with patient-specific anatomy, utilizing multiple imaging modalities for detailed resolution and incorporating additional medical information for improved implant integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a separate planning process is carried out for each patient-specific implant based on three-dimensional image data, then patient-specific anatomical alignment is achieved, but production complexity and time increase significantly
Solution Approach 1:
The planning process is segmented into reusable modular components including database queries, segmentation algorithms, and shape feature extractions that can be independently developed, tested, and reused across different patients and implant types, reducing overall system complexity while maintaining precision
Solution Approach 2:
Reference implants and their associated planning data are pre-stored in a database before actual production. These pre-prepared templates contain segmented tissue structures and shape features that can be directly queried and adapted, eliminating the need to perform complete planning processes from scratch for each new implant
2Measurement precision
If only three-dimensional image data is used for implant planning, then spatial resolution is achieved, but additional medical information such as healing process data is lost
Solution Approach 1:
Multiple data sources including three-dimensional medical images, two-dimensional radiological images, and structured medical records are merged into a unified patient-specific data model. This integration allows the system to simultaneously utilize spatial information from images and clinical context from medical records, preventing information loss while maintaining measurement precision
Solution Approach 2:
A database serves as an intermediary layer between image data and implant planning algorithms. The database stores and structures diverse medical information in standardized formats, enabling seamless integration of spatial resolution data from images with additional clinical information without direct coupling between different data sources
3Manufacturing precision
If manual planning processes are used for each implant, then detailed anatomical consideration is achieved, but production efficiency and automation decrease
Solution Approach 1:
The system performs automated segmentation of tissue structures and automatic extraction of shape features from medical images without requiring manual intervention for each planning step. The database automatically queries and retrieves appropriate reference implants based on patient-specific parameters, enabling high-volume production while maintaining detailed anatomical consideration through algorithmic precision
Solution Approach 2:
The system incorporates feedback loops where planning results are automatically validated against anatomical constraints and medical requirements. The database stores outcomes of planning processes that can be used to refine and improve future planning operations, enabling continuous improvement of automation accuracy while maintaining high production speeds
Data Source
AI summary
A method is disclosed for creating a production model for a patient-specific medical object. Image data relating to a body region are segmented into regions, each region corresponding with structures of different tissue. By way of the regions that correspond with the structures, a number of shape features is determined for the medical object. The shape features are compared with shape data relating to a plurality of stored object data sets. On the basis of the comparison of the shape features with the shape data, a prototype of the medical object is specified. The prototype of the medical object is defined as a production model. The production model is stored on a data carrier and/or output via an interface.