Linear-Pixel X-Ray Imaging With Deconvolution Reconstruction
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Solution Overview
Problem
Existing imaging technologies struggle to produce high-resolution, accurate two-dimensional images of thick subjects like silicon wafers with semiconductor devices without destructive methods, particularly in transmission X-ray microscopes, due to limitations in sampling and image reconstruction techniques.
Innovation Solution
An imaging device using a one-dimensional detector with superconducting strips and a scanning mechanism, coupled with image processing to perform deconvolution, allows for high-resolution image reconstruction by scanning along the linear pixels without rotating the subject, thereby enhancing accuracy and simplifying the mechanical setup.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a one-dimensional detector with linear pixels is used for scanning, then the sampling interval can be reduced to achieve high resolution, but the mechanical scanning complexity increases
Solution Approach 1:
The patent replaces complex mechanical rotation mechanisms with a simple linear scanning mechanism. Instead of rotating the subject to capture images from different angles, the system scans the subject linearly along the length of the linear pixel, eliminating the need for precise rotational control while achieving the same imaging goal.
Solution Approach 2:
The patent divides the imaging process into sequential linear scans along the length of the linear pixel. Each scan captures data at different positions along the subject, and these segmented data points are then reconstructed into a complete two-dimensional image through computational methods.
2Device complexity
If conventional imaging methods are used, then the device structure is simpler, but the image reconstruction accuracy deteriorates
Solution Approach 1:
The patent introduces a window function as an intermediary element in the image reconstruction process. This window function acts as a mathematical mediator that models the detection characteristics and enables accurate deconvolution, improving reconstruction accuracy without adding physical complexity to the device.
Solution Approach 2:
The patent employs deconvolution algorithms that change the mathematical parameters of the imaging process. By adjusting and optimizing reconstruction parameters and using iterative deconvolution methods, the system achieves high accuracy images from the linear scan data without requiring complex mechanical structures.
3Adaptability or versatility
If the subject is rotated for imaging, then comprehensive view is achieved, but the mechanical precision requirements increase
Solution Approach 1:
Instead of rotating the subject to achieve comprehensive imaging coverage, the patent inverts the approach by keeping the subject stationary and scanning along it linearly. This inversion eliminates the need for high-precision rotation mechanisms while still achieving complete coverage of the subject.
Solution Approach 2:
The patent replaces the mechanical rotation system with a linear scanning mechanism. The scanning mechanism moves along the length of the linear pixel in a controlled manner, providing comprehensive imaging coverage without requiring the subject to be rotated with high precision.
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
The method achieves high-accuracy two-dimensional imaging with resolutions below the pixel length, reducing device complexity and cost by eliminating the need for precise rotation, and improving image fidelity through deconvolution techniques.
Implementation Method 1
a detector including a plurality of linear pixels having linear light receiving surfaces
Data Source
AI summary
An imaging device includes an image processor configured to: i) determine that a detection intensity distribution indicating detection intensity with respect to position coordinates of a stage is a convolution of an image intensity distribution on an extension line of a linear pixel and a window function; (ii) calculate an image intensity distribution for each linear pixel by deconvolution from the detection intensity distribution; and (iii) generate an image of the subject by disposing the image intensity distribution calculated in all the linear pixels in an arrangement direction of the linear pixels.