Image Deformation Processor for Microscopy and Mass Spectrometry Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current imaging data processing devices face inefficiencies and operator burden in aligning optical microscopic images with mass spectrometric images due to positional deviations and deformation issues, requiring manual trial-and-error adjustments for accurate superimposition.
Innovation Solution
An imaging data processing device with an input unit and display unit that allows users to specify and adjust image deformation ranges and grid point spacings for precise alignment of images from different measurement methods, enabling nonlinear image deformation and improved alignment efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual image alignment operations are performed to correct positional deviations between optical microscopic images and mass spectrometric images, then alignment accuracy is improved, but operator burden and time consumption increase significantly
Solution Approach 1:
The system automatically performs image alignment by utilizing common structures visible in both optical microscopic images and mass spectrometric images. The alignment process serves itself by automatically detecting corresponding features, calculating transformation parameters, and applying corrections without requiring manual operator intervention, thus resolving the contradiction between alignment accuracy and time consumption
Solution Approach 2:
The manual mechanical operation of aligning images by operators is replaced with an automated computational system. The system uses image processing algorithms to detect common structures, calculate positional deviations, and automatically transform images to achieve alignment, substituting the mechanical manual adjustment process with an automated digital system that reduces both time and operator burden
2Measurement precision
If manual trial-and-error adjustments are performed to achieve accurate superimposition of deformed images, then alignment precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects common structures between images, calculates the optimal transformation parameters, and applies the necessary deformation and alignment corrections without requiring manual trial-and-error adjustments. This self-service approach maintains high alignment precision while dramatically improving ease of operation by eliminating repetitive manual adjustments
Solution Approach 2:
The system uses common structures visible in both images as feedback references to automatically determine the correct alignment transformation. By detecting corresponding features and using them as reference points, the system can precisely calculate and apply the necessary image deformation and positioning adjustments without manual intervention
3Measurement precision
If the entire image is deformed to correct positional deviations, then alignment accuracy is improved, but device complexity increases due to comprehensive image processing requirements
Solution Approach 1:
The image alignment process is segmented into distinct steps: detecting common structures, calculating positional deviations based on those structures, and then applying transformation only to the necessary portions of the image. This segmentation reduces processing complexity by breaking down the comprehensive image deformation into manageable, targeted operations rather than processing the entire image uniformly
Data Source
AI summary
At the time of superimposing and aligning a stained image and a mass spectrometric (MS) image obtained for the same sample, an image display processor displays, on the superimposed images, grid lines (62) at the spacing corresponding to an operation of a grid spacing adjustment slider (63). When an operator depresses an image deformation range “SET” button (64), specifies an arbitrary area on the superimposed images with a mouse, and then depresses a “SELECT” button (65), an image deformation range specification receiving section determines an image deformation range. When the operator selects an intersection (grid point) of the grid lines (62) within the image deformation range and performs an operation of moving the intersection point to an arbitrary position, an image deformation processor deforms an image included in the image deformation range in accordance with the operation. The image deformation range can be set irrespective of the grid-line spacing, so that it is possible to perform accurate image deformation in accordance with the amount and range of deformation for each site on the image, and improve work efficiency.