Cortical Bone Thickness and Density Estimation from Low-Resolution CT
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Solution Overview
Problem
Current methods for measuring cortical bone thickness and density, especially in regions thinner than 3 mm, are inaccurate due to limitations in 2D DXA projections and require regions of thick cortex for accurate estimation, which is not always present in medical images.
Innovation Solution
A method that models imaging data variations along a line crossing the cortical bone tissue, determining a thickness-density relationship using multiple measurements from reference high-resolution imaging data, allowing for accurate estimation of cortical bone thickness and density even in thin cortex regions, by optimizing parameters for blur, thickness, and density.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If model-based estimation methods are used to measure cortical thickness and density, then measurement precision is improved, but device complexity and calculation requirements increase
Solution Approach 1:
The patent pre-calculates and stores thickness-density relationship data from high-resolution reference images before actual measurement. This preliminary action creates a lookup table that stores optimal thickness and density values corresponding to different imaging parameter variations, eliminating the need for complex real-time calculations during actual measurements.
Solution Approach 2:
The patent creates a simplified copy of the complex thickness-density relationship by storing pre-computed values in a lookup table. Instead of performing complex model-based estimations during measurement, the system copies relevant thickness and density data from the pre-established relationship based on measured imaging parameter variations, significantly reducing computational complexity.
2Measurement precision
If region of thick cortex is used for constraining density value or determining thickness-density piecewise function, then optimal parameter estimation is improved, but adaptability to thin cortex regions deteriorates
Solution Approach 1:
The patent pre-establishes thickness-density relationships using high-resolution reference images that include both thin and thick cortex regions. This preliminary action captures the full range of thickness-density variations across different cortical thicknesses, creating a comprehensive lookup table that can be applied to any cortex thickness in subsequent measurements.
Solution Approach 2:
The patent creates a universal thickness-density relationship that applies to both thin and thick cortex regions. By deriving the relationship from reference data encompassing the full range of cortical thicknesses, the method becomes universally applicable to any cortical bone region regardless of thickness, eliminating the need for separate processing of thin versus thick cortex regions.
3Measurement precision
If multiple iterations and additional calculation steps are performed to determine constraining density value or thickness-density piecewise function, then measurement precision is improved, but productivity and processing time deteriorate
Solution Approach 1:
The patent performs all complex iterative calculations and thickness-density relationship determinations in advance using high-resolution reference images. The results are stored in a lookup table, transforming a computationally intensive multi-iteration process into a simple data retrieval operation during actual measurements.
Solution Approach 2:
The patent replaces complex real-time calculations with pre-computed data copying. Instead of performing multiple iterations to determine thickness-density relationships during measurement, the system directly copies appropriate thickness and density values from the pre-established lookup table based on measured imaging parameter variations, dramatically improving processing speed.
Data Source
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AI summary
The method comprises: modelling measured variations of an imaging parameter along a line crossing a cortical bone tissue structure of interest of a patient as a function having a thickness parameter, a first density parameter and a blur parameter; determining a thickness-density relationship between bone tissue structure density and bone tissue structure thickness from multiple thickness and density measurements made on a reference cortical bone tissue structure of a subject which is not the patient; and fitting said function to said measured variations while ensuring said first density parameter and thickness parameter follow said thickness-density relationship, to search for optimal values comprising data defining an estimate of the thickness and density of the cortical bone tissue structure of interest. The system and the computer program implement the method of the invention.