研究目的
To develop a low-cost computational microscope using Fourier Ptychographic Microscopy (FPM) to achieve high-resolution and wide field-of-view imaging for applications in education and biomedicine.
研究成果
The preliminary experiments demonstrate that a low-cost FPM system can successfully produce high-resolution, wide field-of-view images, even with inexpensive components. The integration of auto-calibration for LED alignment and pupil aberrations is crucial for robustness. The goal is to develop a user-friendly kit for educational use, with ongoing improvements to reduce costs and enhance ease of configuration.
研究不足
The system's performance is highly dependent on accurate LED matrix alignment; misalignments (e.g., offset or tilt) can degrade image quality. The computational time is significant (e.g., 56 hours for calibration), and current components may not be optimized for cost or speed. Future work aims to use cheaper cameras and objectives and integrate with Raspberry Pi for lower cost and simplicity.
1：Experimental Design and Method Selection:
The experiment is designed to implement Fourier Ptychographic Microscopy (FPM) using low-cost components. The method involves capturing multiple low-resolution images with varying LED illumination angles and computationally synthesizing a high-resolution image through iterative algorithms that include phase retrieval and LED position calibration.
2：Sample Selection and Data Sources:
A micrometric ruler transparency on a 0.1x0.1mm grid is used as the target sample. Data consists of 49 images captured from an 8x8 LED matrix.
3：1x1mm grid is used as the target sample. Data consists of 49 images captured from an 8x8 LED matrix.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Includes a 10x and 0.25 NA objective lens, an 8x8 LED matrix with 4mm pitch, a Blackfly 0.5 MP monochromatic camera, a Raspberry Pi for computation, 3D-printed parts, and a notebook with specific hardware for algorithm processing.
4：25 NA objective lens, an 8x8 LED matrix with 4mm pitch, a Blackfly 5 MP monochromatic camera, a Raspberry Pi for computation, 3D-printed parts, and a notebook with specific hardware for algorithm processing.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The setup involves placing the sample on a microscope stage, illuminating it with LEDs at different angles, capturing images, and processing them through a calibration stage (50 iterations for pupil aberrations and LED alignment) followed by an FPM reconstruction stage (15 iterations).
5：Data Analysis Methods:
Data is analyzed using MATLAB-based algorithms for Fourier transforms, phase retrieval, and iterative reconstruction, with performance metrics like root mean square error (rmse) for alignment issues.
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