High-resolution single-shot phase-shifting interference microscopy using deep neural network for quantitative phase...

Area of Science:

• Optical Microscopy
• Quantitative Phase Imaging
• Computational Imaging

Background:

• White light phase-shifting interference microscopy (WL-PSIM) is crucial for high-resolution quantitative phase imaging (QPI).
• Traditional WL-PSIM requires multiple interferograms with precise phase shifts for accurate phase measurement.
• This limits its application in dynamic or sensitive biological samples.

Purpose of the Study:

• To develop a single-shot phase-shifting interferometric technique for accurate phase measurement.
• To reduce the number of required interferograms from multiple to one.
• To enhance the applicability of QPI in dynamic and sensitive environments.

Main Methods:

• Filtered white light phase-shifting interference microscopy (F-WL-PSIM) was combined with a deep neural network (DNN).
• The DNN was trained to generate four phase-shifted frames and direct phase from a single interferogram.
• The framework was trained and validated using an optical waveguide and MG63 osteosarcoma cells.

Main Results:

• The F-WL-PSIM+DNN framework successfully generated accurate phase maps from single interferograms.
• Phase maps derived from DNN-generated frames closely matched those from experimentally recorded frames.
• The method demonstrated effective phase recovery for both engineered and biological samples.

Conclusions:

• The presented single-shot F-WL-PSIM+DNN approach significantly simplifies QPI acquisition.
• This technique offers high-resolution phase recovery with reduced data requirements.
• It holds potential for advancing various biomedical applications requiring rapid and accurate phase imaging.