Microscopic Imaging Area Expansion for Pathological Sample Detection
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Solution Overview
Problem
Current digital microscope systems face challenges in accurately detecting pathological samples, particularly with fat tissue, special staining, and minute samples, leading to image detection leakage and increased time and data requirements due to limitations in macro-photography resolution.
Innovation Solution
An image acquisition apparatus and method that includes macro-photographing, judgment units for identifying sample areas, and an area expansion unit to generate expanded photographing areas based on luminance differences and sectional area counts, ensuring comprehensive microscopic imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If macro-photographing is performed at high resolution to detect all pathological samples, then detection accuracy improves, but imaging time and data volume increase significantly
Solution Approach 1:
The slide image is divided into multiple sectional areas, and the system selectively performs microscopic photographing only on sections judged to contain pathological samples, rather than photographing the entire slide at high resolution. This segmentation approach maintains detection accuracy for relevant areas while reducing overall imaging time and data volume.
Solution Approach 2:
The system applies different photographing strategies to different regions: macro-photographing for areas judged to be sample-free and high-resolution microscopic photographing only for areas containing pathological samples. This local quality differentiation optimizes the balance between detection accuracy and imaging efficiency.
2Measurement precision
If macro-photographing resolution is increased to detect minute samples, then detection accuracy improves, but the ability to detect fat cells and special staining remains insufficient
Solution Approach 1:
The system performs macro-photographing as a preliminary step to identify candidate sections containing pathological samples, then performs microscopic photographing on those sections. This two-stage approach ensures that minute samples, fat cells, and special staining are not missed while avoiding the need for high-resolution macro-photographing of the entire slide.
Solution Approach 2:
The judgment unit acts as an intermediary between macro-photographing and microscopic photographing, using multiple indices (luminance value, edge component, color information) to accurately identify sections containing pathological samples. This intermediary step ensures reliable detection across different sample types before committing to high-resolution imaging.
3Productivity
If selective microscopic photographing is performed based on macro-photographing judgment, then imaging time and data volume are reduced, but detection leakage occurs for fat tissue and special staining
Solution Approach 1:
The system uses feedback from multiple judgment indices (luminance value, edge component index, color information) to improve the accuracy of identifying pathological sample sections. This multi-index feedback mechanism reduces detection leakage for fat tissue, special staining, and minute samples while maintaining imaging efficiency through selective microscopic photographing.
Solution Approach 2:
The judgment mechanism combines multiple types of information (luminance, edge components, color data) into a composite assessment of whether a section contains a pathological sample. This composite approach improves detection reliability across diverse sample types while preserving the efficiency benefits of selective imaging.
Data Source
AI summary
An image acquisition apparatus includes: a macro-photographing unit that performs macro-photographing of an image of at least a sample mounting area of a slide, on which a pathological sample is mounted, at a first magnification; a microscopic photographing unit that microscopically photographs a designated photographing area at a second magnification larger than the first magnification; a first judgment unit that judges whether there is an image of the pathological sample in each of a plurality of sectional areas sectioning the image obtained by the macro-photographing; a second judgment unit that judges, as a sample image area, a set of at least one of the plurality of sectional areas judged to be including the image of the pathological sample; and an area expansion unit that generates an expanded area by expanding the sample image area and causes the microscopic photographing unit to photograph the expanded area as the photographing area.