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Related Experiment Video

Updated: Jul 24, 2025

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

Published on: July 8, 2014

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.

Akshay Akshay^1,2, Mitali Katoch³, Masoud Abedi⁴

¹Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, Switzerland.

Biorxiv : the Preprint Server for Biology

|July 10, 2023

Summary

This summary is machine-generated.

Three-dimensional (3D) spheroid models offer a more accurate research environment. We developed SpheroScan, an automated tool using deep learning for 3D spheroid image analysis, improving reproducibility and throughput.

Keywords:

3D spheroids Deep learning High-throughput screening Image analysis Image segmentation Mask R-CNN

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Generation of 3D Tumor Spheroids for Drug Evaluation Studies

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Last Updated: Jul 24, 2025

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

Published on: July 8, 2014

A Robust Method for the Large-Scale Production of Spheroids for High-Content Screening and Analysis Applications

A Robust Method for the Large-Scale Production of Spheroids for High-Content Screening and Analysis Applications

Published on: December 28, 2021

Generation of 3D Tumor Spheroids for Drug Evaluation Studies

Generation of 3D Tumor Spheroids for Drug Evaluation Studies

Published on: February 24, 2023

Area of Science:

Biomedical Engineering
Cell Biology
Drug Discovery

Background:

Three-dimensional (3D) spheroid models mimic in vivo conditions, offering greater physiological relevance than 2D cultures.
3D spheroid assays enhance understanding of cellular behavior, drug efficacy, and toxicity.
Lack of automated tools for 3D spheroid image analysis hinders reproducibility and throughput.

Approach:

Developed SpheroScan, a web-based, automated tool for 3D spheroid image analysis.
Utilized a deep learning framework (Mask Regions with Convolutional Neural Networks - R-CNN) for image detection and segmentation.
Trained the deep learning model on images from diverse experimental conditions using IncuCyte and conventional microscopy.

Key Points:

SpheroScan provides automated, user-friendly analysis of numerous spheroid images.
The tool incorporates interactive visualization for deeper data insights.
Promising performance demonstrated through validation and testing datasets.

Conclusions:

SpheroScan significantly advances 3D spheroid image analysis.
The tool facilitates wider adoption of 3D spheroid models in research.
Open-source code and tutorials are available for SpheroScan.