Maskless and on-chip LED-array microscope with spatially varying angle calibration for centimeter-scale phase imaging

Area of Science:

• Biomedical Optics
• Computational Imaging
• Microscopy

Background:

• Conventional microscopes face a resolution-field-of-view (FOV) trade-off, limiting imaging throughput.
• On-chip phase imaging with LED arrays offers cost-effective, large FOV imaging but suffers from twin-image ambiguity and illumination angle variations.
• Existing solutions like mask-based modulation increase system complexity.

Purpose of the Study:

• To develop a computational framework for mask-free, on-chip phase imaging with adaptive calibration of spatially varying illumination angles.
• To overcome the limitations of twin-image ambiguity and illumination angle variations in large FOV phase imaging.
• To enable simple, low-cost, and scalable label-free imaging of biological tissues at the centimeter scale.

Main Methods:

• A computational framework divides the sensor FOV into subregions, approximating LED illumination as planar within each.
• LED illumination angles are geometrically initialized and refined during phase retrieval using a soft optical transparency prior.
• Reconstructed phase maps from subregions are merged to create a high-quality, large-FOV phase image.

Main Results:

• Achieved centimeter-scale on-chip phase imaging (up to 2.7 × 1.7 cm²) with micron-scale resolution.
• Demonstrated successful phase reconstruction across various biological tissue sections without mask-based modulation.
• Successfully calibrated spatially varying LED illumination angles adaptively.

Conclusions:

• The presented computational framework enables mask-free, large-FOV phase imaging with improved resolution and throughput.
• This approach offers a simple, cost-effective, and scalable solution for label-free imaging of biological samples.
• The method effectively addresses twin-image ambiguity and illumination angle variations in on-chip imaging systems.