Microscope-Cockpit

Microscope-Cockpit controls bespoke microscopy hardware and coordinates imaging workflows for high-precision optical experiments.

Key Features:

• Python-Microscope integration: Integrates the Python-Microscope framework to provide coordinated control over diverse microscopy hardware.
• Hardware device management: Controls complex devices such as deformable mirrors for aberration correction and spatial light modulators used in structured illumination microscopy.
• Abstracted device models: Uses abstract device models to enable seamless integration of varied hardware configurations across standard widefield and advanced adaptive-optics or structured-illumination setups.
• Extensible Python-based architecture: Provides an extensible Python architecture that supports incorporation of machine learning algorithms for automated decision-making and custom computational extensions.

Scientific Applications:

• Adaptive optics experiments: Aberration correction workflows using deformable mirrors and adaptive optics.
• Structured illumination microscopy: Implementation of structured illumination using spatial light modulators for enhanced-resolution imaging.
• Automated microscopy and machine learning: Training and deployment of machine learning algorithms for automated decision-making and imaging automation.
• Bespoke biomedical imaging systems: Control and coordination of bespoke microscopy systems in biomedical research requiring precise hardware synchronization.

Methodology:

Hardware control is abstracted through Python-Microscope using abstract device models to coordinate devices such as deformable mirrors and spatial light modulators.