DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects

Area of Science:

• Biophysics
• Optical Microscopy
• Quantitative Phase Imaging

Background:

• Quantitative Phase Imaging (QPI) enables marker-free characterization of biological samples.
• Spherical objects like cells can be analyzed for radius and refractive index from single QPI images.
• High-throughput analysis of large sample populations is a key advantage of QPI.

Purpose of the Study:

• To develop a universal, automated software for QPI analysis of spherical objects.
• To address the lack of standardized software for QPI data processing and ensemble statistics.
• To facilitate high-throughput quantitative characterization of biological samples using QPI.

Main Methods:

• Developed DryMass, a software tool for QPI data analysis.
• Implemented automated hologram analysis for phase data computation.
• Integrated phase background corrections (offset, tilt, polynomial) and scattering model fitting (light projection, Rytov, Mie).

Main Results:

• DryMass supports multiple experimental data formats and automates hologram analysis.
• The software performs accurate phase background corrections and fits scattering models to extract dry mass, radius, and refractive index.
• DryMass provides a user-friendly, reliable, and reproducible automated pipeline for diverse QPI datasets.

Conclusions:

• DryMass significantly advances QPI data analysis by simplifying visualization and reproduction of results.
• The software democratizes QPI analysis, enabling use by researchers without programming or specialized phase imaging expertise.
• DryMass enhances the accessibility and efficiency of quantitative phase imaging for biological sample characterization.