Spinal Implant Alignment via Medical Image Spline Analysis
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Solution Overview
Problem
Current surgical treatments for spinal disorders, such as degenerative disc disease and osteoporosis, face challenges in accurately determining the precise alignment and positioning of spinal implants to effectively redirect stresses and support vertebral members, which is crucial for successful surgical outcomes.
Innovation Solution
A system and method utilizing medical imaging and machine learning models to analyze medical images of the spine, overlay marks to identify key points, generate splines, and adjust marks for precise vertebrae endpoint locations, enabling accurate planning and execution of spinal treatments by analyzing pixel differences for precise corner identification and modifying mark positions and shapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to determine spinal implant positioning, then the process is simple and quick, but the alignment precision and measurement accuracy are insufficient
Solution Approach 1:
The patent introduces a computing device as an intermediary between the medical image and the surgeon. This computing device processes medical images, generates anatomical markers, and provides alignment guidance, thereby achieving high measurement precision without requiring complex manual measurements by the surgeon directly
Solution Approach 2:
The patent replaces manual mechanical measurement methods with automated image processing and computational analysis. The system uses algorithms to detect anatomical landmarks and calculate implant positioning, substituting the mechanical measurement process with digital image analysis to achieve superior precision
2Measurement precision
If automated image processing is used to identify vertebrae endpoints, then measurement precision improves, but the device complexity and processing time increase
Solution Approach 1:
The system performs preliminary processing by pre-generating anatomical markers and reference information from medical images before the actual implant positioning task. This preliminary action prepares the data in advance, reducing the time required during the critical positioning phase while maintaining high precision
Solution Approach 2:
The medical image itself contains the necessary anatomical information needed for precise endpoint identification. The system extracts this information directly from the image data without requiring additional external measurements or interventions, allowing the image data to serve its own analysis needs efficiently
Data Source
AI summary
Systems, instruments, and methods for medical treatment are disclosed. The methods comprise, by a computing device: receiving information identifying at least one first point on a body part shown in a medical image; overlaying a first mark on the medical image for the at least one first point; generating a spline based at least on the first mark; overlaying a second mark for the spline on the medical image; identifying a location of at least one second point on the body part shown in the medical image based on the first and second marks; overlaying a third mark for the at least one second point on the medical image; and using at least the third mark to facilitate the medical treatment of an individual whose body part is shown in the medical image.