Automated Cell Region Extraction Using Fluorescent and Morphological Image Analysis
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Solution Overview
Problem
Current pathological diagnosis methods are time-consuming and prone to errors due to the manual extraction of cell regions of interest from morphological images, which complicates the identification of specific structures like cell nuclei alongside cell membranes.
Innovation Solution
An image processing apparatus and program that automatically extracts regions of interest from cells by analyzing fluorescent and morphological images, using fluorescent bright points to accurately determine cell boundaries and shapes, thereby reducing the number of steps in the diagnostic process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual extraction of cell regions is performed by operators, then measurement precision can be maintained, but productivity is low and errors occur
Solution Approach 1:
The patent replaces manual mechanical extraction operations with automated image processing algorithms. The system uses fluorescence image analysis to automatically identify cell membranes and extract cell regions, eliminating the need for manual observation and drawing operations while maintaining measurement precision.
Solution Approach 2:
The system enables self-service by automatically performing cell region extraction without requiring operator intervention. The automated algorithm processes images independently, extracting cell regions based on fluorescence signal characteristics, thereby eliminating manual labor while maintaining accuracy.
2Measurement precision
If multiple images are captured for different structures, then measurement precision improves, but the number of steps increases
Solution Approach 1:
The patent merges the identification of multiple cell structures into a single image capture and processing step. By analyzing fluorescence images that simultaneously show cell membranes and nuclear regions, the system identifies both structures in one operation, eliminating the need for separate image capture steps for each structure.
Solution Approach 2:
The fluorescence image serves multiple functions simultaneously: it identifies cell membranes, locates nuclear regions, and provides morphological information. This multi-functional image eliminates the need for separate specialized images for each structure, reducing the overall number of processing steps.
3Ease of operation
If circular regions are used to represent cells, then ease of operation improves, but measurement precision deteriorates
Solution Approach 1:
The patent applies local quality by determining cell region boundaries based on local fluorescence signal characteristics rather than using uniform circular shapes. The system identifies cell membranes and nuclear regions based on local intensity gradients and signal patterns, allowing each cell to be represented by its actual irregular shape rather than a standardized circle.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient and accurate automatic extraction of cell regions of interest, enhancing the speed and accuracy of pathological diagnosis without increasing the number of steps, allowing for precise identification of specific biological substances and structures within tissue sections.
Implementation Method 1
the position of cell membrane is specified on the basis of the light emission from the fluorescent substance which is used for staining cell membrane
Data Source
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AI summary
The present invention provides an image processing apparatus and an image processing program with which it is possible to automatically extract a cell area of interest without increasing the number of conventional steps of pathological diagnosis. This image processing apparatus 2A is characterized in being provided with: an input means for inputting a fluorescent image in which fluorescent bright spots represent the expression of a specific biological substance in a sample in which the biological substance appearing in a first structure of a cell is dyed using a fluorescent substance, and a morphological image in which the morphology of a second structure of the cell in the sample is represented, the morphological image including the same range as the fluorescent image; a feature amount extraction means for extracting the feature amount of the second structure from the morphological image; a bright-spot extraction means for extracting the fluorescent bright spots from the fluorescent image; and an area-of-interest determination means for determining an area of interest on the basis of the feature amount of the second structure and the distribution of the fluorescent bright spots.