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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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Related Experiment Video

Updated: Mar 7, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

Dictionary-enhanced imaging cytometry.

Antony Orth^1,2, Diane Schaak¹, Ethan Schonbrun¹

¹The Rowland Institute at Harvard, Cambridge, MA, 02141, USA.

Scientific Reports

|February 23, 2017

Summary

This summary is machine-generated.

Large image datasets enable automated cell classification and denoising, even with noisy white blood cell (WBC) images. This approach can improve microscope sensitivity and resolution beyond hardware limits.

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High-plex Imaging using Spectral Confocal Microscopy to Minimize Non-specific Tissue Fluorescence

High-plex Imaging using Spectral Confocal Microscopy to Minimize Non-specific Tissue Fluorescence

Published on: October 28, 2025

Area of Science:

Biomedical Imaging
Computational Biology
Cell Biology

Background:

High-throughput microscopy generates vast image data.
Automated analysis is crucial for large datasets.
Cellular protein expression analysis is vital in diagnostics.

Purpose of the Study:

To investigate automated cell classification and denoising using large image datasets.
To assess the feasibility of replicating protein expression gating from nucleus images alone.
To explore image recovery from noisy data for enhanced microscopy.

Main Methods:

Acquisition of a large image library (>250,000 white blood cell nuclei) with CD15/CD16 protein expression data.
Development of automated cell classification and denoising algorithms.
Comparison of nucleus images with a reference dictionary for image recovery.

Main Results:

White blood cell nucleus images alone successfully replicated CD expression-based gating, despite significant noise.
Accurate white blood cell images were recovered from extremely noisy data.
Demonstrated potential for dose-limited imaging in restricted cell classes.

Conclusions:

Large image libraries can enhance microscope capabilities beyond hardware specifications.
Automated analysis of extensive cell image data enables robust classification and denoising.
Crowdsourcing large cell line image libraries is recommended for future research.