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Updated: Mar 9, 2026

Hybrid µCT-FMT imaging and image analysis
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A Novel Mouse Segmentation Method Based on Dynamic Contrast Enhanced Micro-CT Images.

Dongmei Yan1,2, Zhihong Zhang1,2, Qingming Luo1,2

  • 1Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China.

Plos One
|January 7, 2017
PubMed
Summary
This summary is machine-generated.

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This study presents a novel method for segmenting mouse organs from micro-CT images using dynamic contrast enhancement. The technique accurately identifies organs like the kidney and spleen, improving preclinical research capabilities.

Area of Science:

  • Medical Imaging
  • Preclinical Research
  • Biomedical Engineering

Background:

  • Micro-computed tomography (micro-CT) is crucial for preclinical research, but soft tissue segmentation remains challenging due to low contrast.
  • Hybrid imaging requires accurate structural priors from micro-CT for functional imaging reconstruction.

Purpose of the Study:

  • To develop and validate a robust segmentation scheme for mouse soft tissue organs from dynamic contrast-enhanced micro-CT images.
  • To improve the accuracy of organ segmentation for applications in drug metabolism and abnormality localization.

Main Methods:

  • Acquisition of dynamic contrast-enhanced micro-CT images before and after iohexol injection.
  • Extraction of voxel feature vectors based on signal intensities at multiple time points.

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  • Classification and segmentation of organs (heart, liver, spleen, lung, kidney) using machine learning (SVM, Random Forest) and morphological processing; bone segmentation via thresholding.

    • Main Results:

    • The proposed method achieved high segmentation accuracy for multiple mouse organs.
    • Dice similarity coefficients ranged from 0.709 ± 0.078 (spleen) to 0.929 ± 0.006 (kidney), outperforming previous methods.
    • Validation against manual segmentation confirmed the method's reliability.

    Conclusions:

    • Dynamic contrast-enhanced micro-CT imaging combined with machine learning offers an effective solution for mouse soft tissue organ segmentation.
    • This technique enhances the utility of micro-CT in preclinical studies, particularly for quantitative analysis of organ structure and function.