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Related Experiment Video

Updated: Jul 16, 2025

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning.

Mahyar Salek¹, Nianzhen Li², Hou-Pu Chou²

¹Deepcell Inc; 4025 Bohannon Dr., Menlo Park, CA, 94025, USA. yar@deepcellbio.com.

Communications Biology

|September 22, 2023

Summary

This summary is machine-generated.

Computational Sorting and Mapping of Single Cells (COSMOS) uses AI and microfluidics to sort cells by morphology from brightfield images. This platform enables efficient purification of unlabeled cells based on visual characteristics.

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Published on: October 4, 2024

Area of Science:

Cell biology
Bioinformatics
Artificial Intelligence

Background:

Understanding cellular heterogeneity is vital for biological and medical research.
Current methods for cell characterization and sorting often rely on specific labels or dyes, limiting real-time analysis.
Morphological analysis provides a label-free way to assess cell characteristics.

Purpose of the Study:

To develop an AI-powered platform for real-time characterization and sorting of single cells using brightfield microscopy.
To enable label-free cell sorting based on morphological features.
To address the technical gap in deep learning-based cell assessment and sorting.

Main Methods:

Development of Computational Sorting and Mapping of Single Cells (COSMOS) platform integrating microfluidics and AI.
Application of supervised deep learning models for morphological analysis of high-resolution brightfield images.
Utilizing high-dimensional embedding vectors of morphology for cell characterization and sorting without biomarkers or stains.

Main Results:

Demonstrated COSMOS capabilities on multiple human cell lines and tissue samples.
Showcased the ability of neural network embedding space to capture deep visual characteristics of cells.
Successfully purified unlabeled viable cells with desired morphological traits in real-time.

Conclusions:

COSMOS platform effectively characterizes and sorts single cells based on morphology using AI and brightfield imaging.
The approach enables efficient, label-free purification of cells with specific visual traits.
This technology offers a novel solution for real-time deep learning-based cell analysis and sorting.