Highly Efficient Calibration-Free Color Compensation Algorithm for Imaging Flow Cytometry.

Area of Science:

• Biomedical imaging
• Cell biology
• Computational biology

Background:

• Multiplexed fluorescent imaging in imaging flow cytometry allows simultaneous detection of multiple biological targets within single cells.
• Spectral overlap between fluorophores causes signal spillover, leading to artifacts and inaccurate results.
• Current color compensation methods are laborious, time-consuming, and difficult to scale.

Purpose of the Study:

• To develop a simple, intuitive, and computationally efficient calibration-free algorithm for crosstalk removal in multiplexed imaging.
• To address overcorrection issues common in existing calibration-free algorithms when applied to single-cell images.
• To provide a versatile solution applicable to both imaging flow cytometry and microscopy.

Main Methods:

• Development of a novel calibration-free crosstalk removal algorithm.
• Algorithm designed to minimize overcorrection and computational inefficiency.
• Validation using simulated, 2D/3D imaging flow cytometry, and microscopy datasets.

Main Results:

• The algorithm effectively reduces overcorrection compared to existing methods.
• Demonstrated computational efficiency and stability during iterative processes.
• Successful validation across diverse imaging datasets, including spectrally and spatially overlapped channels.

Conclusions:

• The developed algorithm offers an effective solution for accurate multi-parameter single-cell image analysis.
• The calibration-free approach simplifies and enhances the reliability of multiplexed imaging.
• The algorithm's applicability extends to both imaging flow cytometry and microscopy, broadening its utility.