Microscope System Virtual Slide Image Generation for Cytology
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Solution Overview
Problem
Cytologic examination in microscopy is laborious and prone to errors due to reliance on human expertise, leading to variations in accuracy and potential false negatives, especially in identifying abnormal cells amidst numerous cells.
Innovation Solution
A microscope system that generates virtual slide images of specimens, allowing for automated identification and classification of abnormal cells based on geometric and luminance features, and creates three-dimensional images for detailed analysis, reducing human error and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual screening of cells by cytotechnologist is performed, then detailed observation and determination can be made, but labor intensity increases and false negatives occur due to fatigue and human error
Solution Approach 1:
The patent replaces the manual mechanical screening process performed by cytotechnologists with an automated image processing system. The system uses computer algorithms to detect, extract, and classify abnormal cells from microscope images, eliminating human fatigue and error while maintaining high diagnostic accuracy. The automated system processes images through multiple stages including abnormal cell detection, extraction, and classification without manual intervention.
2Measurement precision
If high magnification is used to observe cell structure in detail, then diagnostic precision improves, but the field of view decreases making comprehensive screening more difficult
Solution Approach 1:
The patent divides the screening process into two distinct stages with different magnifications. First, low magnification is used to survey the entire specimen and locate abnormal cells. Second, high magnification is applied only to extracted abnormal cell regions for detailed observation and classification. This segmentation allows the system to maintain both wide field of view for comprehensive screening and high precision for detailed analysis without the trade-off present in manual microscopy.
3Productivity
If automated abnormal cell extraction is performed, then screening efficiency improves, but determination accuracy may vary depending on algorithm performance
Solution Approach 1:
The patent replaces subjective human determination with an automated classification system that uses objective image analysis algorithms. The system extracts geometric features, luminance characteristics, and texture patterns from abnormal cells and classifies them using predetermined criteria. This substitution eliminates variability in human judgment while maintaining consistent, reproducible determination accuracy across all screenings.
Data Source
AI summary
A microscope system has a VS image generation means for generating a virtual slide image of a specimen which is constructed by mutually connecting a plurality of microscope images with a first photomagnification photographed and acquired whenever an objective lens and the specimen are relatively moved in a direction perpendicular to the optical axis and which represents the entire image of the specimen, an object-of-interest set means setting an object of interest with respect to the entire image of the specimen represented by the VS image, and a three-dimensional VS image generation means for generating a three-dimensional VS image which is constructed by connecting the microscope images at different focal positions in accordance with the same focal position and which is constructed from the microscope images with a second photomagnification higher than the first photomagnification and represents the image of the object of interest.