Image Processing System for Microscope 3D Reconstruction
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Solution Overview
Problem
High-magnification microscope images often have a shallow depth of field, leading to inaccurate in-focus evaluation due to changes in the optical system's band, which can be exacerbated by noise not related to the object structure, hindering the creation of accurate all-in-focus or 3D reconstructed images.
Innovation Solution
An image processing system that includes a cutoff frequency acquisition unit to determine the optical system's cutoff frequency and a candidate value modification unit for data correction and interpolation, allowing for improved evaluation and synthesis of in-focus images by accounting for the optical system's parameters and noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-magnification microscopy is used to achieve detailed imaging, then image resolution is improved, but depth of field becomes shallow leading to inaccurate in-focus evaluation
Solution Approach 1:
The patent divides the image processing into multiple stages: acquiring multiple images at different focal depths, evaluating in-focus states for each image, selecting best-in-focus images, and performing optimization processing. This segmentation allows high-resolution imaging while maintaining accurate in-focus evaluation through systematic multi-step processing.
Solution Approach 2:
The patent performs preliminary in-focus evaluation and selection before final image synthesis. By pre-evaluating the in-focus state of multiple images and selecting the best ones, the system ensures accurate in-focus assessment is established before creating the final high-resolution output.
2Device complexity
If optical system band changes are not compensated for, then processing simplicity is maintained, but in-focus evaluation accuracy deteriorates due to noise unrelated to object structure
Solution Approach 1:
The patent dynamically adjusts processing parameters based on the optical system's band characteristics. By acquiring band information and modifying evaluation parameters accordingly, the system compensates for optical system variations without requiring overly complex hardware modifications.
Solution Approach 2:
The patent implements feedback mechanisms where band information from the optical system is continuously monitored and used to adjust processing parameters. This feedback loop ensures that in-focus evaluation remains accurate even when optical system characteristics change, without requiring complete system redesign.
3Reliability
If multiple images at different focal planes are acquired to create all-in-focus images, then image coverage is improved, but processing complexity and time increase
Solution Approach 1:
The patent acquires multiple images at different focal planes (excessive action) to ensure complete coverage of the sample volume, then uses efficient evaluation and selection algorithms to process only the necessary portions. This approach guarantees comprehensive image coverage while minimizing unnecessary processing through optimized selection criteria.
Solution Approach 2:
The patent performs preliminary evaluation of in-focus states for all acquired images before final synthesis. By pre-identifying the best-in-focus images and their corresponding depth information, the system reduces the complexity of subsequent optimization processing and accelerates overall workflow.
4Productivity
If in-focus evaluation is performed without considering optical system band, then processing speed is maintained, but estimation errors increase due to noise and band variations
Solution Approach 1:
The patent modifies evaluation parameters based on the optical system's band characteristics to optimize the balance between processing speed and accuracy. By adapting parameters such as frequency thresholds and evaluation criteria to match the actual optical band, the system maintains high processing speed while eliminating estimation errors caused by band-mismatched evaluation.
Data Source
AI summary
An image processing system includes an acquisition unit, a candidate value estimation unit, a cutoff frequency acquisition unit and a candidate value modification unit. The acquisition unit is configured to acquire an image of a sample taken via an optical system. The candidate value estimation unit is configured to estimate a candidate value of a 3D shape of the sample based on the image. The cutoff frequency acquisition unit is configured to acquire a cutoff frequency of the optical system based on information of the optical system. The candidate value modification unit is configured to perform at least one of data correction and data interpolation for the candidate value based on the cutoff frequency and calculate a modified candidate value.