Cloud-Based Orthopedic Fixing System Automates Parameter Recognition
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Solution Overview
Problem
The widespread adoption of advanced orthopedic external spatial frames like the Taylor spatial frame is hindered in China due to high use costs, inefficient parameter recognition, and manual dependency on doctors, leading to inaccurate treatments and increased patient pain.
Innovation Solution
An intelligent orthopedic external fixing system based on a cloud platform integrates medical registration technology, computer image recognition, three-dimensional reconstruction, and deep machine learning to automatically obtain malformation parameters, customize orthopedic equipment, and reduce doctor dependence, utilizing a Taylor spatial frame manufacturing module with servo control and real-time monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual parameter recognition is used by doctors, then treatment can be performed, but efficiency is low and accuracy is poor
Solution Approach 1:
The patent replaces the manual mechanical process of doctor-based parameter recognition with an automated image recognition system using computer vision and deep learning algorithms. The system automatically identifies malformation parameters, mounting parameters, and bone structure characteristics from medical images, eliminating the need for manual measurement and significantly improving both accuracy and efficiency.
Solution Approach 2:
The system enables self-service by allowing the orthopedic external fixing system to automatically recognize and acquire treatment parameters without requiring continuous doctor intervention. The image recognition module autonomously processes medical images and extracts necessary parameters, making the system independent of manual operation for routine parameter acquisition.
2Manufacturing precision
If Taylor spatial frame is used, then treatment precision is improved, but use cost increases and operation difficulty increases
Solution Approach 1:
The system performs self-adjustment through automated parameter recognition and cloud platform processing. The image recognition module automatically determines optimal mounting parameters and malformation characteristics, and the cloud platform generates personalized treatment plans, eliminating the need for complex manual calculations and adjustments by doctors.
Solution Approach 2:
The patent introduces a cloud platform as an intermediary between the medical imaging system and the orthopedic external fixing system. The cloud platform processes complex image recognition tasks, stores patient data, generates treatment plans, and provides remote expert consultation, thereby simplifying the operation for local doctors while maintaining high treatment precision.
3Ease of manufacture
If domestic enterprises produce advanced external spatial frames, then local production is achieved, but profit is extremely low due to technical communication barriers
Solution Approach 1:
The patent creates a universal platform that combines image recognition, cloud computing, and orthopedic treatment functions. This multi-functional system serves multiple purposes: automated diagnosis, treatment planning, manufacturing guidance, and remote consultation, thereby creating additional value streams beyond simple equipment production and improving profitability.
Solution Approach 2:
The cloud platform acts as an intermediary that connects domestic manufacturers with international technical standards and expert knowledge. It enables technology transfer, facilitates collaboration with foreign experts, and provides access to advanced algorithms and treatment protocols, thereby overcoming technical communication barriers and enhancing the competitiveness of domestic enterprises.
4Device complexity
If complex growth factors are not considered in rehabilitation, then treatment process is simplified, but residual malformations occur and patient pain increases
Solution Approach 1:
The system performs preliminary analysis of complex growth factors and rehabilitation requirements during the initial treatment planning phase. The image recognition module identifies bone growth characteristics, age-related factors, and rehabilitation needs in advance, allowing the treatment plan to pre-compensate for these factors throughout the rehabilitation process, thereby ensuring high treatment outcome quality without complicating the actual treatment execution.
Data Source
AI summary
An intelligent orthopedic external fixing system based on a cloud platform, includes a cloud platform, an intelligent recognition unit and a Taylor spatial frame manufacturing module, wherein the intelligent recognition unit comprises an osteotrauma reconstruction module, a three-dimensional medical model registration module, a condition characteristic extraction module, an image recognition module, a personalized designed module and a basic module. According to the disclosure, the cloud platform integrates medical registration technology, computer image recognition technology, three-dimensional reconstruction technology and deep machine learning technology.