High-Resolution Scanning Microscopy Data Segmentation
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Solution Overview
Problem
Current high-resolution scanning microscopy methods, such as Airy scan microscopy, face challenges in processing large amounts of data and correcting artifacts, particularly during bidirectional scanning, which slows down the image generation process and requires significant computational effort and data transfer.
Innovation Solution
The method involves calculating pre-calculated raw line images immediately after recording and combining them line by line, allowing for the generation of sample images through Sheppard sums, with optional grouping of lines for correction and deconvolution, reducing data transfer and processing time by applying corrections directly during scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all raw image data sets are transmitted to the control and evaluation unit for artifact correction, then correction accuracy is improved, but data transfer time and processing time increase significantly
Solution Approach 1:
The patent segments the image data processing by dividing raw image data sets into complementary groups (first group and second group) that can be processed separately. This allows correction calculations to be performed on smaller data subsets rather than transmitting all data at once, reducing data transfer time while maintaining correction accuracy through subsequent combination of the grouped results.
Solution Approach 2:
The patent performs preliminary artifact correction calculations on segmented data groups before final image reconstruction. By calculating corrections on divided data sets in advance and storing intermediate results, the system reduces the computational burden and data transfer requirements for final image generation without compromising overall correction accuracy.
2Reliability
If complete data sets are processed for artifact correction, then correction completeness is improved, but processing speed decreases
Solution Approach 1:
The patent divides complete data sets into complementary groups that can be processed independently and in parallel. This segmentation enables faster processing by utilizing multiple processing channels simultaneously while ensuring correction completeness through the combination of results from all groups.
Solution Approach 2:
The patent processes partial data sets (complementary groups) separately rather than requiring complete data sets to be processed together. This partial action approach maintains correction reliability by ensuring all necessary data are eventually processed, while improving productivity through parallel processing of smaller subsets.
3Productivity
If bidirectional scanning is used to accelerate image acquisition, then scanning speed is improved, but scanner offsets cause artifacts that require complex correction
Solution Approach 1:
The patent segments bidirectional scan data into complementary groups (forward scanning lines and backward scanning lines) that can be processed separately. This segmentation simplifies artifact correction by treating each direction's data independently, reducing the complexity of correcting scanner offsets while maintaining the speed benefits of bidirectional scanning.
Solution Approach 2:
The patent performs preliminary correction calculations on segmented scan data from each direction before final image reconstruction. By calculating and storing correction factors for each complementary group in advance, the system reduces the complexity of final artifact correction while preserving the high scanning speed enabled by bidirectional acquisition.
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 accelerates the recording and processing of images, reduces data requirements, and allows for real-time preview generation, improving the efficiency of high-resolution image acquisition and correction, especially in multiplex and bidirectional scanning modes.
Implementation Method 1
the illuminating light is focused at a point in or on the sample to form a preferably diffraction-limited illumination spot
Implementation Method 2
The point is then imaged into a diffraction image on a pixel-based area detector
Data Source
Figure 1
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AI summary
The invention relates to a method for high-resolution scanning microscopy of a sample, wherein the sample (P) is illuminated with light (B) such that the light (B) is focused at a point in or on the sample (P) to form an illumination spot (3). The spot is imaged onto a diffraction pattern (15) on a planar detector (13) having detector elements (19), wherein the planar detector (13) has a spatial resolution through its detector elements (19) that resolves a diffraction pattern (16) of the diffraction pattern (15). The sample (P) is scanned row by row in a grid of rows and columns by moving the spot relative to the sample (P) to different scan positions with a step size that is smaller than the diameter of the illumination spot (3).The area detector (13) is read out, and an image of the sample (P) is generated from the data of the area detector (13) and from the scan positions assigned to this data. This image has a resolution that exceeds a resolution limit of the imaging process. According to the invention, a pre-processed raw line image is calculated for each line after acquisition. The pre-processed raw line images are combined into a raw image and unfolded to generate the image of the sample (P).