Nematode Image Recognition Using Overlap Pattern Matching
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Solution Overview
Problem
Conventional methods for counting nematodes, especially when they overlap in a detection target image, suffer from low efficiency and accuracy due to the labor-intensive process and difficulties in distinguishing individual nematodes during assays.
Innovation Solution
An image recognition program and device that utilize detection target image acquisition, extraction, storage, and recognition means to accurately count overlapping nematodes by comparing images with stored pattern databases, including single-body and multiple-bodies patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional counting methods are used for nematodes in liquid recess, then the counting process can be performed, but the accuracy is poor due to overlapping nematodes and high-speed swimming motion
Solution Approach 1:
The patent segments the complex task of counting overlapping nematodes into distinct phases: extracting detection target presence areas, comparing with pattern images showing different numbers of nematodes, and identifying the best match. This segmentation allows the system to handle overlapping nematodes systematically by breaking down the image analysis into manageable comparison steps against pre-stored patterns.
Solution Approach 2:
The patent performs preliminary action by pre-storing multiple pattern images in the storage unit, each showing different numbers of overlapping nematodes in various configurations. These pre-prepared patterns serve as reference templates that enable rapid and accurate counting during actual measurement without requiring complex real-time analysis of overlapping structures.
2Productivity
If manual counting of nematodes is performed, then the counting can be done, but the efficiency is low due to labor-intensive process
Solution Approach 1:
The patent replaces the mechanical manual counting process with an automated image recognition system. The computer executes programs that automatically acquire images, extract detection target areas, compare them with stored patterns, and determine nematode counts. This substitution eliminates manual labor and significantly improves assay efficiency while reducing counting time.
Solution Approach 2:
The patent uses copying by creating digital replicas of nematode patterns at different overlap configurations and storing them as reference images. Instead of manually analyzing each new image, the system compares captured images against these stored copies, enabling rapid automated counting without repeated manual intervention.
3Ease of operation
If anesthetics are used to trap nematodes for counting, then the nematodes can be immobilized, but the assay process becomes more complex and time-consuming
Solution Approach 1:
The patent extracts the nematodes from their natural crawling environment on solid medium and confines them to liquid recesses where their movement patterns are more predictable and contained. This extraction to a controlled liquid environment simplifies the imaging and counting process by limiting nematode movement to a confined space, eliminating the need for anesthetics to immobilize them.
Data Source
AI summary
Provided are an image recognition program capable of accurately counting the population of nematodes that are detection targets even when a plurality of detection targets overlap each other, an image recognition device using the same, a detection target population counting method, and a model image creation device for image recognition learning to be used therefor.An image recognition program causes a control unit 11 and a storage unit 12 of an image recognition device 1 to function as detection target image acquisition means for acquiring a detection target image showing a plurality of nematodes 3, extraction means for extracting from the detection target image a detection target presence area that possibly includes an image of the nematodes 3, storage means for storing a plurality of pattern images including a single-body pattern image showing one of the nematodes 3 and a multiple-bodies pattern image corresponding to an image showing two or more of the nematodes 3 overlapping each other, and recognition means for recognizing the population of nematodes 3 included in the detection target presence area by detecting a degree of concordance between an image of the detection target presence area and each of the pattern images.