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Related Concept Videos

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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Related Experiment Video

Updated: Sep 9, 2025

TACI: An ImageJ Plugin for 3D Calcium Imaging Analysis
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MCA: A Multicellular analysis Calcium Imaging toolbox for ImageJ.

John Hageter1, Audrey DelGaudio1, Maegan Leathery1

  • 1West Virginia University Department of Biology, Morgantown, WV, USA 26506.

Biorxiv : the Preprint Server for Biology
|September 2, 2025
PubMed
Summary
This summary is machine-generated.

MCA is a new toolkit for analyzing functional imaging data, simplifying complex experiments. This open-source software integrates with ImageJ, offering a user-friendly interface for researchers studying cellular dynamics.

Keywords:
calcium imagingfunctional imagingmodel systemsopen sourcesoftwarezebrafish

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Area of Science:

  • Neuroscience
  • Biotechnology
  • Computational Biology

Background:

  • Genetically encoded indicators like GCaMP are vital for in vivo functional imaging.
  • Analyzing large-scale or complex functional imaging data presents significant analytical challenges.
  • Existing analysis platforms often require proprietary software, have limited outputs, or demand advanced programming skills.

Purpose of the Study:

  • To develop an accessible and versatile toolkit for analyzing functional imaging data.
  • To address the limitations of existing analysis platforms by leveraging open-source software.
  • To provide a user-friendly interface for researchers to extract cellular dynamics from imaging experiments.

Main Methods:

  • Developed MCA (Multicellular Analysis toolkit) integrated with ImageJ, an open-source image analysis platform.
  • Implemented a visually intuitive interface with a graphical user interface (GUI) similar to native ImageJ plugins.
  • Incorporated rigid registration for motion correction, cell body prediction using a custom Cellpose 2.0 model, cell annotation, and data export functionalities.

Main Results:

  • MCA was validated against previously published zebrafish calcium imaging data, accurately reflecting visually evoked neuronal responses.
  • The toolkit demonstrated versatility across multiple sensory modalities, brain regions, and model organisms (zebrafish, *Drosophila*, mouse).
  • MCA successfully extracts calcium dynamics in a user-friendly environment, enhancing the utility of functional imaging.

Conclusions:

  • MCA provides a viable, user-friendly solution for extracting calcium dynamics from functional imaging data.
  • The toolkit's integration with ImageJ and its versatile application across species and modalities make it a valuable resource for neuroscientists.
  • MCA lowers the barrier to entry for complex functional imaging analysis, promoting wider adoption and discovery.