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MitoTex (Mitochondria Texture Analysis User Interface): Open-Source Framework for Textural Characterization and

Amulya Kaianathbhatta1,2, Malak Al Daraawi2,3, Natasha N Kunchur1,2

  • 1Department of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.

International Journal of Molecular Sciences
|February 13, 2026
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Summary
This summary is machine-generated.

This study introduces a new image analysis pipeline to quantify mitochondrial shapes, aiding in understanding cell metabolism and disease. The open-source tool objectively classifies mitochondrial structures for research applications.

Keywords:
machine learningmicroscopymitochondriatexture analysis

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Area of Science:

  • Cell Biology
  • Biophysics
  • Computational Biology

Background:

  • Mitochondria are vital organelles regulating cellular metabolism, energy production, and signaling pathways.
  • Assessing mitochondrial morphology is crucial for monitoring cellular metabolic activity and function.
  • Changes in mitochondrial structure can offer insights into disease mechanisms and treatment efficacy.

Purpose of the Study:

  • To develop and validate a novel, quantitative image analysis pipeline for characterizing and classifying dynamic mitochondrial morphologies.
  • To enable objective differentiation of key mitochondrial structures (fibers, puncta, rods) indicative of cellular metabolic states.

Main Methods:

  • Utilized high-resolution confocal microscopy.
  • Integrated first-order statistics (FOS) and various gray-level texture analyses (GLCM, GLRLM, GLDM, GLSZM, NGTDM).
  • Employed machine learning algorithms for classification.

Main Results:

  • Demonstrated the pipeline's efficacy in objectively differentiating mitochondrial structures.
  • Provided robust quantitative metrics for characterizing mitochondrial variation.
  • Successfully classified key mitochondrial morphologies linked to cellular metabolic and activation states.

Conclusions:

  • The developed open-source pipeline offers a robust method for quantitative analysis of mitochondrial morphology.
  • This tool can significantly advance the study of cellular metabolism, disease pathogenesis, and therapeutic responses.
  • Objective characterization of mitochondrial dynamics is essential for biological and medical research.