Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

Area of Science:

• Microscopy
• Image Processing
• Camera Technology

Background:

• Scientific CMOS (sCMOS) cameras are crucial for widefield fluorescence microscopy.
• Pixel variations in sCMOS cameras cause artifacts and hinder quantitative analysis.
• Existing correction methods require complex camera characterization.

Purpose of the Study:

• To develop an automated pipeline for camera characterization using only thermal signals.
• To implement this pipeline in open-source software (Micro-Manager and ImageJ/Fiji).
• To enable accurate quantitative interpretation and high-quality imaging in microscopy.

Main Methods:

• Developed a fully automated pipeline for camera characterization.
• Utilized solely thermally generated signal for characterization.
• Integrated the pipeline into Micro-Manager and ImageJ/Fiji software.

Main Results:

• The pipeline provides noise, offset, gain, dark current, and thermal noise maps as functions of exposure time.
• Successfully corrected structural bias in single-molecule localization microscopy (SMLM).
• Enabled high-quality 3D super-resolution and live-cell imaging with industry-grade cameras.

Conclusions:

• The automated pipeline simplifies camera characterization, making advanced correction algorithms accessible.
• This approach improves quantitative accuracy and image quality in fluorescence microscopy.
• Facilitates high-performance microscopy with both specialized and affordable cameras.