Microscopy-MS Image Correlation for Faster Substance Identification
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Solution Overview
Problem
Conventional data processing techniques for multi-dimensional analysis data from different measurement techniques are cumbersome and often fail to accurately identify substances of interest, as they require extensive time and labor to locate significant mass-to-charge ratios, and may not provide useful information due to the complexity of multivariate analyses.
Innovation Solution
A data processing device that adjusts the position and spatial resolution of image data from different measurement techniques, such as mass spectrometric imaging and optical microscopy, to calculate an index value indicating similarity or difference in signal intensity distribution, allowing for efficient identification of substances by correlating pixel data across images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multivariate analyses are used to extract significant mass-to-charge ratios from mass spectrometric imaging data, then the analysis comprehensiveness is improved, but the time and labor required for analysis increases significantly
Solution Approach 1:
The patent segments the analysis process into distinct stages: first performing position adjustment and spatial resolution equalization on image data from different measurement techniques, then conducting statistical analysis to calculate index values. This segmentation allows the system to process data systematically in manageable steps, reducing overall analysis time while maintaining comprehensive substance identification.
Solution Approach 2:
The patent performs preliminary position adjustment and spatial resolution equalization before the actual statistical analysis. By pre-processing the image data to ensure proper alignment and resolution matching, the system eliminates time-consuming adjustments during the analysis phase, thereby reducing total analysis time without compromising identification accuracy.
2Loss of information
If conventional multivariate analysis techniques are applied to locate mass-to-charge ratios with characteristic distributions, then the analysis depth is improved, but the operational complexity increases
Solution Approach 1:
The patent introduces an intermediary statistical analysis process that calculates index values based on pixel data from different image datasets. This intermediary step translates complex multivariate relationships into more interpretable index values, maintaining deep substance characterization while simplifying the operational interface and making the analysis more user-friendly.
Solution Approach 2:
The patent replaces manual, operator-intensive multivariate analysis operations with an automated computational system that performs position adjustment, resolution equalization, and statistical calculations. This substitution maintains comprehensive analysis depth while dramatically improving ease of operation by eliminating the need for operators to manually navigate complex analytical procedures.
3Productivity
If image data from different measurement techniques are processed without position adjustment and resolution equalization, then the processing speed is improved, but the measurement precision deteriorates
Solution Approach 1:
The patent performs position adjustment and spatial resolution equalization as preliminary steps before statistical analysis. By completing these alignment operations upfront, the system ensures high spatial alignment accuracy is achieved before processing begins, while the subsequent statistical analysis proceeds efficiently without requiring repeated adjustments, thus maintaining both precision and productivity.
4Measurement precision
If extensive multivariate analyses are performed to identify substances, then the identification accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent segments the complex analysis system into distinct functional modules: a position adjustment unit, a resolution equalization unit, and a statistical analysis unit. Each module performs a specific function, making the overall system more manageable and easier to implement while maintaining high substance identification accuracy through the coordinated operation of these specialized components.
Data Source
AI summary
An analysis operator checks an optical microscopic image obtained with an imaging mass microscope and indicates a color characteristic of an area which the analysis operator is focusing on. An optical microscopic image feature extractor calculates luminance distribution data in the indicated color. An image position adjustment processor performs a position adjustment process on a luminance distribution image derived from the optical microscopic image and an MS imaging graphic, while a resolution adjuster equalizes their spatial resolutions. A statistical analysis processor calculates a coefficient of spatial correlation between the luminance distribution image and the MS imaging graphic for each mass-to-charge ratio. Based on the calculated correlation coefficients, an analysis result display processor extracts a mass-to-charge ratio which shows an ion intensity distribution similar to the luminance distribution image. and displays it on a display unit.