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Related Experiment Video

Updated: May 30, 2026

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
13:09

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography

Published on: April 4, 2012

Automatic abdominal fat assessment in obese mice using a segmental shape model.

Yang Tang1, Priyank Sharma, Marvin D Nelson

  • 1Department of Radiology, Children's Hospital Los Angeles, University of Southern California, Los Angeles, California 90027, USA.

Journal of Magnetic Resonance Imaging : JMRI
|July 20, 2011
PubMed
Summary

A new computerized method accurately quantifies abdominal fat in obese mice using 7T MRI. This automated approach for analyzing visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) shows high correlation with manual segmentation.

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Area of Science:

  • Medical imaging
  • Computational biology
  • Obesity research

Background:

  • Obesity is a complex metabolic disorder.
  • Accurate assessment of abdominal fat distribution is crucial for understanding obesity-related health risks.
  • Current methods for fat quantification can be labor-intensive.

Purpose of the Study:

  • To develop an automated image analysis technique for quantifying abdominal fat in obese (ob/ob) mice.
  • To adapt the method for high-resolution 7 Tesla (7T) magnetic resonance imaging (MRI).

Main Methods:

  • A novel segmental shape model was developed to differentiate visceral adipose tissue (VAT) from subcutaneous adipose tissue (SAT).
  • The model utilizes shape and distance constraints to segment fat tissues.
  • Adaptive fuzzy C-means clustering was employed to handle image intensity variations.

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Related Experiment Videos

Last Updated: May 30, 2026

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
13:09

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography

Published on: April 4, 2012

Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging
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Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging

Published on: July 1, 2021

Body Composition and Metabolic Caging Analysis in High Fat Fed Mice
10:28

Body Composition and Metabolic Caging Analysis in High Fat Fed Mice

Published on: May 24, 2018

Main Results:

  • The automated method demonstrated high accuracy, with correlation coefficients for total adipose tissue (TAT), SAT, and VAT sizes ranging from 0.907 to 0.950.
  • Dice coefficients for the positional accuracy of TAT, SAT, and VAT were between 0.920 and 0.941.
  • Validation was performed against manual segmentations on 109 MRI slices from 7 obese mice.

Conclusions:

  • The developed computerized image analysis method provides reliable quantification and distribution assessment of abdominal fat tissues.
  • The automated approach shows strong agreement with manual segmentations.
  • This method has the potential to enhance laboratory automation in obesity research.