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Related Experiment Video

Updated: Feb 19, 2026

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

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Published on: January 19, 2024

ABLE: An Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data.

Stephanie Reynolds^1,2, Therese Abrahamsson³, Renaud Schuck^2,4

¹Department of Electrical and Electronic Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.

|November 1, 2017

Summary

This summary is machine-generated.

This study introduces ABLE, an algorithm for cell detection in two-photon calcium imaging. It effectively demixes overlapping cells and identifies diverse cell types without prior information, achieving a 67.5% success rate on mouse datasets.

Keywords:

active contour calcium imaging fluorescence microscopy level set method segmentation

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Area of Science:

Neuroscience
Computational Biology
Biophysics

Background:

Two-photon calcium imaging is crucial for monitoring neural activity.
Accurate cell detection is essential for analyzing imaging data.
Overlapping cells and diverse cellular properties pose significant challenges in cell identification.

Purpose of the Study:

To develop and present a novel algorithm for robust cell detection in two-photon calcium imaging data.
To address the challenge of demixing overlapping cells.
To create a flexible framework capable of identifying cells with varied morphologies and activity patterns.

Main Methods:

A coupled active contours model guided by a model-based cost function.
Independent contour evolution with coupled behavior for overlapping regions.
No prior information on cell morphology or temporal activity is incorporated.

Main Results:

The algorithm successfully demixes overlapping cells in real imaging data.
Demonstrated performance on challenging in vitro mouse datasets with synchronously spiking cells.
Achieved a 67.5% success rate on a manually labeled in vivo mouse dataset.

Conclusions:

The proposed algorithm, ABLE, offers a flexible and effective solution for cell detection in two-photon calcium imaging.
Its ability to handle overlapping cells and diverse cell properties makes it valuable for neuroscience research.
ABLE demonstrates significant potential for advancing the analysis of neural activity.