Portable Imaging Flow Cytometer With Deep Learning Phase Recovery
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Solution Overview
Problem
Existing imaging flow cytometers face limitations in throughput, image quality, and cost due to the use of microscope objectives, which restrict field-of-view and depth-of-field, making them expensive and less suitable for high-resolution, high-throughput analysis of plankton and microorganisms in water samples.
Innovation Solution
A compact, cost-effective, and portable in-line holographic imaging flow cytometer using deep learning-enabled phase recovery and holographic reconstruction, capable of capturing high-resolution, color images of label-free objects in real-time at a throughput of ~100 mL/h, without fluorescence triggering or hydrodynamic focusing, utilizing a microfluidic chip and a computing device for image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a microscope objective lens is used to image plankton in flow, then image resolution is improved, but volumetric throughput is limited to a few mL per hour
Solution Approach 1:
The patent removes the microscope objective lens from the optical path, extracting the imaging function from traditional flow cytometry. This allows direct imaging of the flow channel without the resolution-throughput trade-off imposed by objectives, enabling both high resolution and high throughput simultaneously
Solution Approach 2:
The patent transitions from point-by-point scanning imaging (traditional microscopy) to planar parallel imaging by capturing the entire flow channel cross-section in a single camera frame. This dimensional change from 1D scanning to 2D parallel acquisition enables throughput increase while maintaining resolution
2Measurement precision
If a microscope objective lens is used, then image quality is improved, but device cost increases
Solution Approach 1:
The patent replaces expensive, precision-engineered microscope objective lenses with inexpensive, off-the-shelf components including a simple camera and transparent plate. This substitution dramatically reduces device cost while maintaining adequate image quality for plankton identification
Solution Approach 2:
The patent creates a direct optical copy of the flow channel contents onto the camera sensor without requiring complex objective lenses. The transparent plate serves as a simple interface that copies the microscopic scene directly to the sensor plane, eliminating the need for expensive optical components
3Measurement precision
If hydrodynamic focusing is used to confine sample to focal point, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent eliminates the need for complex hydrodynamic focusing systems by allowing plankton to pass through the imaging region in natural flow. The transparent plate creates a defined imaging plane that works with natural flow patterns, requiring no additional focusing channels or pressure control mechanisms
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
The device achieves high-throughput imaging of microorganisms, including plankton and parasites, with improved image quality and cost-effectiveness, enabling continuous monitoring of water bodies, and is validated by field tests showing good agreement with independent measurements.
Implementation Method 1
A light source (e.g., LED) is disposed within the housing or enclosure and used to provide illumination
Implementation Method 2
an image sensor disposed adjacent to the microfluidic channel and within an optical path that receives light from the light source that passes through the microfluidic channel, the image sensor configured to capture a plurality of image frames containing raw hologram images of the objects
Data Source
Figure 1~2
Figure 3
Figure 4A
AI summary
An imaging flow cytometer device includes a housing holding a multi-color illumination source configured for pulsed or continuous wave operation. A microfluidic channel is disposed in the housing and is fluidically coupled to a source of fluid containing objects that flow through the microfluidic channel. A color image sensor is disposed adjacent to the microfluidic channel and receives light from the illumination source that passes through the microfluidic channel. The image sensor captures image frames containing raw hologram images of the moving objects passing through the microfluidic channel. The image frames are subject to image processing to reconstruct phase and/or intensity images of the moving objects for each color. The reconstructed phase and/or intensity images are then input to a trained deep neural network that outputs a phase recovered image of the moving objects. The trained deep neural network may also be trained to classify object types.