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Classification of Leukocytes

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Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
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Updated: Jun 17, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

Enhanced CellClassifier: a multi-class classification tool for microscopy images.

Benjamin Misselwitz¹, Gerhard Strittmatter, Balamurugan Periaswamy

¹Institute of Microbiology, ETH Zurich, Zürich, Switzerland. misselwitz@micro.biol.ethz.ch

BMC Bioinformatics

|January 16, 2010

Summary

This summary is machine-generated.

Enhanced CellClassifier offers biologists a user-friendly tool for analyzing microscopy images without coding. This software facilitates complex phenotype classification, improving automated high-content screening efficiency.

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Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

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Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

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Published on: January 27, 2023

Area of Science:

Cell biology
Biotechnology
Bioimage analysis

Background:

Light microscopy is crucial in cell biology, with automated high-content screening expanding its applications.
Evaluating microscopy data remains a bottleneck, often requiring programming skills for advanced analysis.
Existing open-source tools like CellProfiler have limitations for complex tasks.

Purpose of the Study:

To develop a user-friendly tool for advanced microscopy image analysis.
To enable multi-class classification of cellular phenotypes without programming knowledge.
To overcome limitations in current bioimage analysis software.

Main Methods:

Developed Enhanced CellClassifier, a tool that integrates with CellProfiler outputs.
Implemented multi-class classification using a Support Vector Machine algorithm.
Incorporated intuitive training modes directly on microscopy images and routine task support.

Main Results:

Enhanced CellClassifier allows for multi-class classification and elucidation of complex phenotypes.
The tool supports routine tasks like out-of-focus exclusion and well summaries.
Classification results can be integrated with other measurements for detailed image interpretation.

Conclusions:

Enhanced CellClassifier provides biologists with a simple, flexible image analysis solution.
The tool facilitates the differentiation of complex phenotypes and detailed image interpretation.
This facilitates the broader implementation of automated high-content screening in biological research.