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Related Experiment Video

Updated: Jun 25, 2025

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

A generative benchmark for evaluating the performance of fluorescent cell image segmentation.

Jun Tang^1,2, Wei Du², Zhanpeng Shu³

¹State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, 200237, China.

Synthetic and Systems Biotechnology

|May 27, 2024

Summary

This study introduces a new framework for generating diverse cell images, improving cell segmentation evaluation. CellProfiler demonstrated superior accuracy in segmenting cell cytoplasm and nuclei.

Keywords:

Biological image analysis Cell segmentation Fluorescent images Generative adversarial networks

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Rapid Analysis and Exploration of Fluorescence Microscopy Images

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

Area of Science:

Cell biology
Bioimage analysis
Computational imaging

Background:

Fluorescent cell imaging generates vast data vital for understanding cellular processes.
Accurate cell segmentation is critical for quantitative analysis but challenging due to evaluation limitations.

Purpose of the Study:

To develop a novel framework for generating diverse, graded-density cell images for improved segmentation evaluation.
To systematically assess and compare the performance of leading cell segmentation methods.

Main Methods:

Developed a framework using StyleGAN2 for contour generation and Pix2PixHD for image rendering.
Created a dataset of diverse, graded-density cell images.
Evaluated DeepCell, CellProfiler, and CellPose using the generated dataset.

Main Results:

CellProfiler exhibited higher accuracy in segmenting both cytoplasm and nuclei compared to DeepCell and CellPose.
The novel framework successfully generated varied and graded cell image data.

Conclusions:

The developed framework enhances cell image data diversity and addresses limitations in cell segmentation evaluation.
CellProfiler is recommended for accurate cytoplasm and nuclei segmentation in fluorescent cell images.