DryMass

DryMass analyzes quantitative phase microscopy (QPI) images to extract quantitative parameters such as dry mass, radius, and average refractive index of cell-sized and other spherical objects for marker-free optical characterization.

Key Features:

• Universal analysis of spherical phase objects: Performs comprehensive analysis of quantitative phase images of spherical objects including cells in suspension, microgel beads, and liquid droplets.
• Automated analysis pipeline: Automates steps from loading experimental data to computing phase images and generating ensemble statistics.
• Multi-format data loading: Supports multiple file formats to accommodate various experimental setups.
• Automated hologram analysis and phase computation: Includes automated hologram analysis for phase data extraction.
• Phase background correction: Provides offset, tilt, and second-order polynomial corrections for phase background.
• Scattering model fitting: Fits spherical phase objects using light projection, the Rytov approximation, and Mie simulations.
• Quantitative parameter extraction: Extracts dry mass, radius, and average refractive index from single QPI images via model fitting.
• High-throughput ensemble statistics: Enables high-throughput measurement rates and generation of ensemble statistics for large sample populations.

Scientific Applications:

• Marker-free quantitative characterization: Enables classification and quantitative characterization of biological samples from QPI data without fluorescent or chemical labels.
• Cellular biology and single-cell analysis: Supports measurements of dry mass, size, and refractive index for cells in suspension.
• Biophysics: Facilitates optical property and scattering-based analyses using Rytov and Mie model fitting.
• Materials science: Applies to characterization of microgel beads and liquid droplets via quantitative phase metrics.

Methodology:

Data loading from multiple file formats; automated hologram analysis to compute phase data; phase background correction using offset, tilt, and second-order polynomial corrections; model fitting of spherical objects using light projection, the Rytov approximation, and Mie simulations to extract dry mass, radius, and average refractive index; generation of ensemble statistics.