Computational approaches in 3D quantitative phase Imaging: Current and future trends in cellular imaging

Area of Science:

• Computational Imaging
• Optics
• Biomedical Imaging

Background:

• Phase retrieval is crucial for high-resolution, non-invasive imaging.
• Quantitative Phase Imaging (QPI) relies on accurate phase recovery.
• Existing methods include Shack-Hartmann, Pyramid wavefront sensors, and iterative algorithms like Gerchberg-Saxton (GS).

Purpose of the Study:

• To review the Transport of Intensity Equation (TIE) for Quantitative Phase Imaging (QPI).
• To compare TIE with other phase retrieval techniques.
• To highlight advancements and future directions of TIE in computational imaging.

Main Methods:

• Focus on the Transport of Intensity Equation (TIE) for phase retrieval.
• Comparison with Shack-Hartmann and Pyramid wavefront sensors.
• Evaluation alongside iterative methods such as the Gerchberg-Saxton (GS) algorithm.

Main Results:

• TIE provides a rapid, low-cost alternative to iterative methods for real-time phase recovery.
• Advancements using spatial light modulators (SLMs) and electrically tunable lenses (ETLs) enable nanometer-scale sensitivity in milliseconds.
• TIE demonstrates potential in cellular morphology analysis and dynamic studies.

Conclusions:

• TIE is a powerful tool for real-time phase recovery in computational imaging.
• Despite clinical translation challenges, TIE offers significant advantages in speed and cost.
• Future research should focus on overcoming limitations for broader applications.