Multi-Angle Cell Imaging for Fast and Accurate Sorting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for cell analysis, such as microscopic imaging and manual analysis of cytology smears, are time-consuming, subjective, and prone to errors due to factors like cell orientation and contamination, making it difficult to detect rare cells or specific disease features.
Innovation Solution
A method and system for cell sorting that involves transporting cells through a flow channel, capturing images from multiple angles, and analyzing them using a deep learning algorithm to sort cells based on their characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual microscopic imaging and analysis of cytology smears is used, then cell type identification and disease diagnosis can be performed, but the process becomes time-consuming and subjective
Solution Approach 1:
The patent replaces manual mechanical microscopic analysis with an automated digital imaging system that captures multiple images of cells at different angles and uses machine learning algorithms for automatic analysis, eliminating the need for manual observation and measurement
Solution Approach 2:
The system enables self-service analysis where the machine automatically processes cell images, identifies cell types, and provides diagnostic information without requiring continuous human intervention, allowing the system to analyze cells autonomously
2Loss of information
If cells are analyzed from a single angle in traditional microscopy, then the analysis process is simple, but essential information is obscured due to cell orientation
Solution Approach 1:
The patent transitions from single-angle (2D) imaging to multi-angle (3D) imaging by capturing cell images from multiple orientations, adding the dimension of angular variation to comprehensively capture cell morphology and features that would be obscured in single-angle views
Solution Approach 2:
The imaging system is designed to perform multiple functions: capturing images from different angles, reconstructing 3D cell models, and providing comprehensive morphological analysis, making it a universal platform that handles various cell types and orientations effectively
3Reliability
If traditional smear preparation methods are used, then cell samples can be prepared for analysis, but contaminant cells are hard to avoid and make it difficult to detect rare cells
Solution Approach 1:
The system extracts and isolates individual cells from the complex smear background by capturing multiple images at different angles, allowing the analysis algorithm to distinguish target cells from contaminant cells and background noise, effectively separating useful information from harmful interference
Solution Approach 2:
The patent introduces computational algorithms as an intermediary between the raw multi-angle cell images and the final diagnostic conclusion, using machine learning to process the images, identify cell features, and make reliable detections even in the presence of contaminants
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
Enables accurate and efficient sorting of cells at high speeds, allowing for the detection of rare cells and specific features, reducing subjectivity and improving diagnostic accuracy.
Implementation Method 1
transporting a cell through a flow channel
Implementation Method 2
capturing a plurality of images of the cell
Implementation Method 3
capturing a plurality of images of the cell
Data Source
Figure 1A~1B
Figure 2~3
Figure 4~6A
AI summary
The present disclosure provides systems and methods for sorting a cell. The system may comprise a flow channel configured to transport a cell through the channel. The system may comprise an imaging device configured to capture an image of the cell from a plurality of different angles as the cell is transported through the flow channel. The system may comprise a processor configured to analyze the image using a deep learning algorithm to enable sorting of the cell.