Automated Cell Identification System Using Rotational Imaging and Learned Models
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Solution Overview
Problem
The low success rate of generating usable induced pluripotent stem cells (iPS cells) due to the labor-intensive and costly manual sorting process of identifying good cells, which hampers the efficiency and cost-effectiveness of iPS cell generation.
Innovation Solution
A cell identification system comprising an imaging device with a well plate and rotation mechanism, coupled with a processing circuitry that uses a learned model for automated identification of good iPS cells by imaging and analyzing cells rotated within the wells, reducing the need for manual operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual sorting by researchers is used to identify good iPS cells, then cell identification can be performed with simple equipment, but the process becomes labor-intensive and costly
Solution Approach 1:
The patent replaces manual mechanical observation and sorting by researchers with an automated imaging system that captures cell images and an identification unit that automatically determines cell quality. This substitution eliminates labor-intensive manual operations while maintaining equipment simplicity through the use of standard imaging devices combined with automated processing algorithms.
2Ease of manufacture
If manual sorting by researchers is used to identify good iPS cells, then equipment costs remain low, but operational costs increase significantly
Solution Approach 1:
The system enables self-service automation where the imaging device and identification unit work autonomously to capture cell images, analyze them using predetermined criteria, and determine cell quality without requiring researcher intervention. This automation reduces operational costs by eliminating the need for skilled researcher time while keeping equipment costs low through the use of commercially available imaging devices.
3Productivity
If automated identification using imaging devices is implemented, then productivity and efficiency of cell sorting improve, but device complexity increases
Solution Approach 1:
The patent segments the cell identification system into distinct functional modules: an imaging device that captures cell images, an identification unit that processes images, and a determination unit that outputs results. This modular segmentation allows each component to perform its specific function independently, improving overall productivity while managing device complexity through functional separation and standardized interfaces.
4Loss of energy
If automated identification using imaging devices is implemented, then operational costs are reduced, but device complexity and initial investment increase
Solution Approach 1:
The patent employs a universal imaging device that can capture images of multiple cells simultaneously, and an identification unit that applies predetermined identification criteria to various cell types. This multi-functionality reduces operational costs by enabling high-throughput automated analysis while managing initial investment through the use of versatile, commercially available equipment rather than specialized custom-built systems.
Data Source
AI summary
According to one embodiment, a cell identification system includes an imaging device and an identification device. The imaging device includes a well plate, a rotation mechanism, and an imaging part. The well plate is provided with a plurality of wells capable of accommodating cells. The rotation mechanism rotates the cells. The imaging part images the cells. The identification device includes processing circuitry. The processing circuitry controls the rotation mechanism to rotate the cells, controls the imaging part to image the cells each time the cells are rotated by the rotation mechanism, and inputs an image for the cells captured by the imaging part to a learned model so as to identify a cell in a good state from among the cells.