Cell Image Analysis Using Bright-Field Defocused Imaging and Region Correction
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Solution Overview
Problem
Existing cell image analysis methods using phase contrast microscopes face challenges in accurately determining cell region areas due to narrow imaging fields and the need for expensive device configurations, with methods relying on defocused images often requiring manual focus position and region correction settings that can vary by cell type and size, and may not be suitable for measuring cell growth behaviors like iPS cell colonies.
Innovation Solution
A cell image analysis method that acquires multiple images at different imaging distances, determines the optimal imaging distance based on index information change rates, extracts cell regions, and applies region correction to achieve accurate area measurement, using a combination of image acquisition, index information acquisition, imaging distance determination, region extraction, and region correction steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase contrast microscope is used to acquire morphological information of cell, then contour of cell can be clearly observed, but device configuration becomes expensive and imaging field of view becomes narrow
Solution Approach 1:
The patent uses bright-field imaging to capture defocused images that copy the cell morphology information, eliminating the need for expensive phase contrast microscope hardware while achieving similar measurement capabilities through computational processing of multiple focal plane images
Solution Approach 2:
The patent replaces the optical mechanical system (phase contrast lenses and condensers) with a computational approach that uses bright-field imaging at multiple focal planes combined with image processing algorithms to extract cell contour information
2Device complexity
If defocused images are used to extract cell region, then simpler processing is achieved, but accurate focus position and region correction parameters are difficult to determine
Solution Approach 1:
The patent implements self-service through automated algorithms that calculate the optimal focus position and region correction parameters based on image analysis, eliminating the need for manual determination and making the process adaptive to different cell types and imaging conditions
Solution Approach 2:
The patent uses feedback mechanisms where the system evaluates image quality metrics (such as contrast or gradient information) from defocused images to automatically determine the optimal focus position and adjustment parameters, creating a closed-loop system that adapts to the specific imaging scenario
3Measurement precision
If multiple defocused images are captured to extract cell region, then region extraction accuracy is improved, but processing complexity and time increase
Solution Approach 1:
The patent extracts only the essential information needed for cell region determination from the multiple defocused images, using selective image processing and analysis techniques that focus computational resources on the most relevant features rather than processing all image data equally
Solution Approach 2:
The patent applies partial action by using a limited number of defocused images at strategically selected focal planes rather than processing all possible focal depths, achieving sufficient accuracy with reduced computational burden through selective sampling of the focal stack
4Extent of automation
If focus position is determined by image contrast, then automated determination is achieved, but accuracy for area measurement is compromised
Solution Approach 1:
The patent implements a dynamic approach where the focus determination criterion changes based on the measurement objective - using contrast-based automation for general focus acquisition but switching to area-stability-based optimization for precise area measurements, allowing the system to adapt its strategy to the specific task requirements
Data Source
AI summary
The cell image analysis method includes: an image acquisition step of acquiring a plurality of images of a cell captured at a plurality of imaging distances that are different from each other in the bright field; an index information acquisition step of acquiring index information that is information regarding an index for evaluating a difference between the plurality of images acquired in the image acquisition step; an imaging distance determination step of determining such an imaging distance that a rate of a change in the index information with respect to a change in the imaging distance is equal to or less than a predetermined threshold value; a region extraction step of extracting a cell region included in an image captured at the imaging distance determined in the imaging distance determination step; and a region correction step of performing correction on the cell region extracted in the region extraction step.