Flow Channel Cell Tracking With Zone-Based Speed Control
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Solution Overview
Problem
Tracking biological cells is challenging due to their random motions and varying speeds, especially when label-free methods are used, which complicates accurate identification and sorting.
Innovation Solution
A device with a flow channel configured to modify cell movement based on cell category, using zones with specific coatings or obstacles, combined with an imaging sensor that detects interference patterns and adjusts frame rates to cell speed variations, enabling label-free tracking and sorting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If label-free tracking methods are used, then cells can be tracked without being affected by labels, but tracking accuracy deteriorates due to random motions and varying speeds
Solution Approach 1:
The system performs preliminary actions by adjusting frame rates before cells enter different speed zones. The imaging sensor is configured to operate at a first frame rate in a first zone and a second frame rate in a second zone, anticipating speed changes before they occur. This preliminary adjustment ensures that tracking accuracy is maintained throughout the cell's journey through the flow channel, even without labels.
Solution Approach 2:
The system dynamically adjusts the frame rate of the imaging sensor based on the cell's position and speed. The frame rate changes from a first frame rate in the first zone to a second frame rate in the second zone, allowing the system to adapt to varying cell speeds. This dynamic adjustment compensates for random motions and speed variations, maintaining tracking accuracy without requiring labels.
2Measurement precision
If frame rate is increased to track fast-moving cells, then tracking accuracy improves, but processing requirements and power consumption increase
Solution Approach 1:
The system applies local quality by using different frame rates in different zones of the flow channel. In zones where cells move slower, a lower frame rate is sufficient, reducing processing requirements. In zones where cells move faster, a higher frame rate is applied only where needed. This localized adjustment of frame rate maintains tracking accuracy while minimizing overall processing power consumption.
Solution Approach 2:
The system changes the frame rate parameter dynamically based on the cell's position and speed. By adjusting this key parameter, the system optimizes the balance between tracking accuracy and processing requirements. The frame rate is increased only when necessary to track fast-moving cells in specific zones, and decreased in other zones to reduce processing load and power consumption.
3Device complexity
If uniform frame rate is used throughout the flow channel, then system complexity is reduced, but tracking accuracy deteriorates for cells moving at different speeds
Solution Approach 1:
The flow channel is segmented into multiple zones, each with its own optimal frame rate. The first zone uses a first frame rate, while the second zone uses a second frame rate. This segmentation allows the system to optimize tracking accuracy for cells at different speeds without requiring a uniformly high frame rate throughout, thus managing complexity while improving precision.
4Measurement precision
If high frame rate is used to capture fast-moving cells, then tracking accuracy improves, but false positives increase due to random motions
Solution Approach 1:
The system performs preliminary adjustment of frame rate before cells enter high-speed zones. By anticipating speed changes and adjusting the frame rate in advance, the system captures cells at optimal intervals, reducing the impact of random motions. This preliminary action helps distinguish true cell movements from random fluctuations, thereby reducing false positives while maintaining tracking accuracy.
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, high-throughput tracking and sorting of biological cells by detecting modified movements, reducing false positives and eliminating the need for labels, while minimizing processing requirements and power consumption.
Implementation Method 1
an imaging sensor configured to detect an interference pattern by receiving object light, which is incident on the imaging sensor after having interacted with the biological cells, and reference light, which is incident on the imaging sensor without having interacted with the biological cells
Data Source
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AI summary
According to an aspect of the present inventive concept there is provided a device for tracking cells comprising: a flow channel, the flow channel comprises at least one zone, associated with a cell category, configured to modify movement of the cell in dependence of the cell belonging to the cell category; an imaging sensor being configured to detect the flow of liquid in the flow channel in a plurality of regions, to track the cells through the plurality of regions; wherein the imaging sensor is configured to sequentially image the cell, wherein the cell in consecutive images has moved a distance below a threshold value, wherein the imaging sensor is configured to acquire frames, wherein a frame rate associated with the first region is set such that, between consecutive frames, a distance travelled by a supposed cell moving at the second speed is larger than the threshold value.