Particle Image Processing Transform Parameter Correction
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Solution Overview
Problem
Current imaging systems using CCD detectors in biotechnology applications face challenges in accurately processing multiple images of particles due to movement between images, leading to shifts or distortions that affect data accuracy.
Innovation Solution
Computer-implemented methods and systems that determine particle locations in a first image, calculate a transform parameter to estimate movement between images, and apply this parameter to correct for movement, using components like radial and constant transformations, and error calculations to refine particle location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple images of particles are taken close together in time, then the particles remain relatively stationary and imaging is efficient, but the particles may still appear to shift or move between images affecting data accuracy
Solution Approach 1:
The patent applies preliminary action by calculating transform parameters from a first image before processing the second image. The system determines particle locations in the first image, calculates transformation parameters that account for expected particle movement, and applies these parameters to the second image before final analysis. This preliminary transformation compensates for particle movement between images, maintaining measurement precision while preserving imaging efficiency.
2Measurement precision
If transform parameters are calculated to account for particle movement, then particle location accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex transformation problem into distinct computational stages: (1) determining particle locations in the first image, (2) calculating transform parameters based on those locations, (3) applying the transform parameters to the second image, and (4) determining final particle locations. This segmentation of the processing workflow makes the complex task more manageable and computationally efficient while maintaining accuracy.
Data Source
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AI summary
Embodiments of the computer-implemented methods, storage mediums, and systems may be configured to determine locations of particles within a first image of the particles. The particles may have fluorescence-material associated therewith. The embodiments may include calculating a transform parameter, and the transform parameter may define an estimated movement in the locations of the particles between the first image of the particles and a second image of the particles. The embodiments may further including applying the transform parameter to the locations of the particles within the first image to determine movement locations of the particles within the second image.