Confocal Microscope Scan Coordinate Correction
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Solution Overview
Problem
Confocal scanning microscopes face challenges in creating precise images, particularly at image edges, due to distortions caused by approximate scan coordinate calculations and optical effects of the microscope's elements, which can lead to mismatched images when composing multiple views or superimposing with wide field images.
Innovation Solution
The method involves determining spherical scan coordinate values using a coordinate transformation of Cartesian image coordinate values, allowing precise assignment of pixel positions to the scanning unit, and incorporating zoom levels to maintain precision across different magnifications. This is achieved through a coordinate transformation and the use of a reference sample for correction, enabling accurate image creation and correction of scan coordinate values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If approximate scan coordinate calculations are used, then the device complexity is reduced, but the manufacturing precision of image coordinates deteriorates
Solution Approach 1:
The patent pre-calculates and stores correction values in a lookup table before actual image acquisition. These correction values compensate for distortions at different field positions. During scanning, the system simply retrieves pre-computed correction values based on measured scan coordinates, avoiding complex real-time calculations while maintaining high precision.
Solution Approach 2:
The patent introduces an intermediate correction table that maps between ideal scan coordinates and actual scan coordinates. This lookup table acts as a mediator that translates approximate scan coordinates into corrected coordinates, eliminating the need for complex real-time distortion correction calculations.
2Manufacturing precision
If spherical scan coordinate values are determined through coordinate transformation, then the manufacturing precision of image edges is improved, but the device complexity increases
Solution Approach 1:
The patent performs the complex spherical coordinate transformation and distortion correction in advance, storing the results in a lookup table. During actual operation, the system only needs to perform simple table lookups and interpolations, rather than executing complex coordinate transformations in real-time.
Solution Approach 2:
The patent replaces complex real-time mathematical coordinate transformation calculations with a pre-computed lookup table approach. This substitution of computational mechanics with data retrieval mechanics significantly reduces processing complexity while maintaining transformation accuracy.
3Area of stationary object
If multiple images are stitched together to create composite images, then the area of coverage is increased, but the manufacturing precision deteriorates due to edge misalignment
Solution Approach 1:
The patent measures actual scan coordinates during image acquisition and uses this feedback to determine correction values. When stitching multiple images, the system applies position-specific corrections to each image based on its location in the composite, ensuring precise edge alignment across the entire composite image.
Solution Approach 2:
The patent applies different correction values to different regions of the image based on their position. Each local region has its own optimized correction parameters stored in the lookup table, allowing precise correction of edge distortions in composite images while maintaining overall coverage area.
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 ensures precise image matching at image edges and maintains image precision across various zoom levels, effectively reducing distortions and improving the accuracy of image composition and superimposition.
Implementation Method 1
spherical scan coordinate values are determined in a spherical coordinate system, depending on the Cartesian image coordinate values of pixels of an image to be created from a sample, by means of a coordinate transformation of the Cartesian image coordinate values
Data Source
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AI summary
To determine scan coordinate values (ϕn, θn) for operating a scan unit (28) of a confocal scanning microscope (20), spherical scan coordinate values (ϕn, θn) are determined based on Cartesian image coordinate values (Xn, Yn) of pixels of an image (60) to be created from a sample (32) by means of a coordinate transformation of the Cartesian image coordinate values (Xn, Yn) into a spherical coordinate system. The scan unit (28) is operated based on the spherical scan coordinate values (ϕn, θn).