Trabecular Bone Density Analysis via Geometric Figure Generation
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Solution Overview
Problem
Current methods for detecting osteoporosis, such as Dual X-ray absorptiometry (DXA), are costly and burdensome, and existing automated systems face high computational complexity, making early and accurate detection of osteoporosis challenging, especially in populations that do not undergo regular medical examinations.
Innovation Solution
A method and system that generate a bone density value by classifying X-ray image pixels to distinguish trabeculae and non-trabeculae tissue, processing these pixels to create geometrical figures representing the space between trabeculae, and calculating bone density based on these figures, reducing computational load and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DXA is used to measure bone density, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses 2D digital X-ray images as a simplified copy representation of the 3D bone structure, eliminating the need for bulky DXA equipment. By extracting trabecular bone parameters from these 2D images through image processing and geometric analysis, the system achieves bone density measurement without requiring complex volumetric scanning hardware.
2Productivity
If automated bone analysis is implemented, then productivity is improved, but computational complexity increases
Solution Approach 1:
The patent extracts only the essential trabecular bone features from digital X-ray images, such as trabecular thickness, spacing, and orientation, rather than performing comprehensive 3D reconstruction and analysis. This selective extraction of key parameters significantly reduces computational requirements while maintaining diagnostic value for osteoporosis detection.
Solution Approach 2:
The patent employs simple geometric figures (circles, ellipses) and basic image processing operations that can be executed quickly on standard computing hardware. These computationally inexpensive methods provide sufficient accuracy for clinical screening, avoiding the need for complex algorithms that would require powerful computing resources.
3Measurement precision
If comprehensive bone analysis is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs partial analysis by focusing specifically on trabecular bone regions within the visual field rather than analyzing the entire bone structure in detail. By concentrating computational resources on the most diagnostically relevant areas (trabecular patterns in the jawbone), the system achieves sufficient precision for osteoporosis detection while minimizing analysis time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early and accurate detection of osteoporosis with reduced computational complexity and lower costs, facilitating a more efficient and automated analysis of bone health.
Implementation Method 1
generating a set of digital image data pixels depending upon an X-ray image corresponding to at least a part of said bone
Data Source
AI summary
The present description relates to a method for generating a bone density value. The method can include generating digital image data depending upon an X-ray image corresponding to at least a part of the bone; transmitting a digital image data signal comprising the digital image data; and processing said digital image data signal. The processing step can include generating a trabeculae model depending upon said processed digital image data signal; generating at least one geometrical figure depending upon the generated trabeculae model, wherein the generated geometrical figure is provided essentially within a space at least partly defined by center lines of the generated trabeculae; and calculating the bone density value depending upon the at least one generated geometrical figure. Devices and storage for the method(s) are also described.