High-throughput pixel-super-resolved coded ptychographic microscopy with a color image sensor.

Area of Science:

• Optics and Photonics
• Biomedical Imaging
• Computational Imaging

Background:

• Lensless on-chip microscopy offers advantages like simplicity, aberration-free imaging, and portability for biomedical applications.
• Color image sensors are attractive for on-chip imaging but face challenges with color filtering arrays (CFAs) causing spectral crosstalk under monochromatic illumination.

Purpose of the Study:

• To develop a high-throughput, pixel-super-resolved coded ptychographic microscopy method using a color image sensor.
• To address spectral crosstalk introduced by the CFA without physical removal, enabling full utilization of sensor data.

Main Methods:

• Implemented a gradient descent optimization method within iterative ptychographic phase retrieval to numerically estimate CFA transmittance.
• Utilized all three color channels of the sensor data, unlike single-channel methods, to prevent information loss.
• Developed a compact, field-portable on-chip microscopy prototype using a Raspberry Pi single-board computer.

Main Results:

• Achieved high-resolution and high-throughput bio-imaging using a standard color sensor.
• Demonstrated the effectiveness of the numerical CFA transmittance estimation in overcoming spectral crosstalk.
• Validated the potential of color sensors for advanced lensless on-chip imaging applications.

Conclusions:

• The proposed method successfully integrates color sensors into lensless on-chip imaging, enhancing throughput and resolution.
• This approach offers a cost-effective and portable solution for biomedical imaging, with open-sourced code for wider research adoption.