Cell Nucleus Detection via Edge Continuity Analysis
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Solution Overview
Problem
Current image processing techniques for pathological diagnosis often incorrectly detect cell nuclei, either as multiple nuclei when a single nucleus is sparsely stained or as a single nucleus when multiple nuclei are contiguous, due to uneven staining of advanced cancer cells.
Innovation Solution
An image processing device and program that includes a region-extracting unit, a judging unit, and a correcting unit to accurately detect cell nuclei by extracting candidate regions and correcting them based on region and edge information, integrating or dividing regions as necessary to prevent incorrect detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing is used on sparsely stained cell nuclei, then processing speed is maintained, but detection accuracy deteriorates due to incorrect identification of single nuclei as multiple nuclei
Solution Approach 1:
The patent segments the cell nucleus detection process into multiple stages: initial candidate region extraction using simple thresholding, followed by selective merging of adjacent regions based on edge continuity analysis. This segmentation allows the system to maintain simplicity for initial processing while adding complexity only where needed to resolve staining issues.
Solution Approach 2:
The patent performs preliminary edge extraction and continuity analysis before final nucleus identification. By pre-processing the image to identify edge regions and their continuity, the system prepares data structures that enable accurate merging decisions without requiring complex real-time computation during the final detection phase.
2Measurement precision
If conventional image processing is used on contigous cell nuclei, then processing speed is maintained, but detection accuracy deteriorates due to incorrect merging of multiple nuclei into single nuclei
Solution Approach 1:
The patent segments adjacent candidate regions and analyzes the edges between them to determine continuity. By examining edge continuity rather than relying solely on intensity thresholds, the system can distinguish between truly separate nuclei and contigous nuclei that should be merged, maintaining accuracy without excessive complexity.
Solution Approach 2:
The patent introduces edge continuity as an intermediary criterion between candidate regions. This intermediary analysis layer allows the system to make informed merging decisions by evaluating the intermediate edge structures, enabling accurate differentiation between separate and contigous nuclei without requiring overly complex processing.
3Measurement precision
If staining intensity is increased to improve detection, then detection capability improves, but tissue damage and artifacts increase
Solution Approach 1:
The patent applies partial action by using moderate staining intensity combined with selective processing. Instead of requiring strong staining throughout, the system extracts candidate regions based on local intensity variations and merges them based on edge continuity, achieving accurate detection without excessive staining that would cause tissue damage.
Solution Approach 2:
The patent substitutes mechanical/staining-based detection with computational detection methods. By replacing reliance on strong chemical staining with image processing techniques that analyze edge continuity and regional characteristics, the system achieves detection capability without the harmful effects of intensified staining procedures.
Data Source
AI summary
An image processing device extracts a candidate region and region information of the cell nucleus from a cell image (S20), judges whether or not to correct the candidate region of the cell nucleus on the basis of the region information of the cell nucleus, and corrects the candidate region of the cell nucleus on the basis of the judged result (S40).