Material Thickness Estimation in Radiological Projection Images
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Solution Overview
Problem
Current radiological projection image analysis methods struggle to accurately differentiate between changes in tissue thickness and iodine concentration, particularly in mammography, leading to incomplete material decomposition and artifacts in 'water' images.
Innovation Solution
A procedure involving the decomposition of multiple projection images taken at different energies into thickness cards, followed by a second decomposition using main thickness cards, to accurately estimate material thickness and composition, thereby correcting for beam hardening and improving material separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If weighted logarithmic subtraction algorithm is used to visualize iodine concentration, then iodine concentration can be visualized, but areas of varying thickness result in inhomogeneous background intensity
Solution Approach 1:
The patent segments the material decomposition into multiple independent thickness maps, each representing a specific material (glandular tissue, adipose tissue, iodine, bone). By separating the decomposition into distinct material-specific components rather than a single subtracted image, the method can independently analyze and correct for thickness variations in each material type, thereby maintaining background homogeneity while preserving iodine concentration information.
Solution Approach 2:
The patent changes the parameter representation from intensity-based logarithmic subtraction to thickness-based decomposition. Instead of working with logarithmic intensity values that conflate thickness and concentration effects, the method transforms the data into physical thickness maps for each material type. This parameter transformation allows separate estimation of thickness and concentration, resolving the inhomogeneity issue while maintaining measurement precision.
2Measurement precision
If dual-energy approach is used to estimate material thickness, then two different materials can be differentiated, but areas of varying thickness create ambiguity between thickness change and true material concentration
Solution Approach 1:
The patent extends the dual-energy approach by segmenting the decomposition into four distinct thickness maps corresponding to four different materials (glandular tissue, adipose tissue, iodine, bone). This multi-material segmentation allows the system to independently track thickness variations for each material type, thereby distinguishing between actual thickness changes and true material concentration changes that would be ambiguous in a standard dual-energy two-material decomposition.
Solution Approach 2:
The patent adds an additional dimension to the decomposition by incorporating a fourth material component beyond the traditional two-material dual-energy approach. This dimensional expansion from 2D to 4D material space provides sufficient constraints to independently resolve thickness and concentration for each material type, eliminating the ambiguity that plagues conventional dual-energy methods.
3Measurement precision
If conventional decomposition is used to separate bone and water, then bone and water can be separated, but presence of fat or other materials leads to incomplete decomposition and bone artifacts in the water image
Solution Approach 1:
The patent segments the decomposition into distinct material-specific thickness maps, including separate maps for bone, water (soft tissue), and fat (adipose tissue). By providing dedicated decomposition components for each material type rather than forcing a two-material separation, the method achieves complete decomposition even in the presence of multiple materials, eliminating bone artifacts in the water image that result from incomplete decomposition.
Solution Approach 2:
The patent changes the decomposition parameters from a two-material model to a four-material model, adding explicit parameters for fat and iodine alongside bone and water. This parameter expansion allows the decomposition algorithm to properly account for all present materials, preventing the misattribution of fat or other materials to the water or bone components that causes artifacts in conventional approaches.
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
This approach effectively separates materials in radiological images by accurately accounting for tissue thickness variations, reducing artifacts, and enhancing the visibility of iodine concentrations and other materials.
Implementation Method 1
a radiation source (3) designed for the emission of a spectrum comprising N different recording energies
Implementation Method 2
correcting for beam hardening
Implementation Method 3
performing a first decomposition of the N projection images into N thickness maps, each representing the thickness of N areas with different materials
Data Source
Figure 1~2
Figure 3
AI summary
The invention relates to a method for estimating material thicknesses in radiological projection images, comprising the steps of: - providing a plurality of N projection images at different acquisition energies, - performing a first decomposition of the N projection images into N thickness maps, each representing the thickness of N areas with different materials, - performing a second decomposition of a number of main thickness maps based on the N thickness maps and/or on corresponding measurements and a number of the N projection images, into N result thickness maps, each representing the thickness of the N areas with different materials. The invention further comprises a device and an imaging instrument.