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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Updated: Mar 17, 2026

Multicolor Flow Cytometry-based Quantification of Mitochondria and Lysosomes in T Cells

Multicolor Flow Cytometry-based Quantification of Mitochondria and Lysosomes in T Cells

Published on: January 9, 2019

Masks in imaging flow cytometry.

Venina Dominical¹, Leigh Samsel¹, J Philip McCoy¹

¹National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, United States.

Methods (San Diego, Calif.)

|July 28, 2016

Summary

This summary is machine-generated.

Accurate masking is essential for reliable imaging flow cytometry data analysis. This study discusses mask types, selection, and assessment to ensure robust morphological analysis of cellular images.

Keywords:

Data analysis Features ImageStream Imaging flow cytometry Mask

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Last Updated: Mar 17, 2026

Multicolor Flow Cytometry-based Quantification of Mitochondria and Lysosomes in T Cells

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Published on: January 9, 2019

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Qualitative and Quantitative Analysis of the Immune Synapse in the Human System Using Imaging Flow Cytometry

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Published on: January 7, 2019

Area of Science:

* Biomedical imaging analysis
* Cellular morphology assessment
* Quantitative biology

Background:

* Imaging flow cytometry (IFC) combines flow cytometry with image analysis for detailed cellular characterization.
* Accurate segmentation of cellular images using masks is a critical prerequisite for downstream analysis in IFC.
* Inaccurate masks can significantly compromise the reliability and validity of IFC data.

Purpose of the Study:

* To elucidate the importance of mask creation in imaging flow cytometry data analysis.
* To review different types of masks and their applications in IFC.
* To provide guidance on selecting and evaluating optimal masks for specific IFC experiments.

Main Methods:

* Discussion of various mask types used in image segmentation for IFC.
* Review of manufacturer-provided versus user-generated custom masks.
* Exploration of criteria for assessing mask accuracy and suitability.

Main Results:

* Mask accuracy directly impacts the quality of morphological feature extraction in IFC.
* Custom masks offer flexibility for specialized applications but require careful validation.
* Systematic approaches to mask selection and assessment are crucial for reproducible results.

Conclusions:

* Careful attention to mask generation and validation is paramount for successful imaging flow cytometry analysis.
* Understanding mask types and selection criteria enhances the reliability of cellular image analysis.
* Optimizing mask selection improves the accuracy and interpretability of IFC data.