Enhanced Image Processing of Implanted Hydrogel Scaffold Images Using Propagation-Based Imaging Computed Tomography

Authors

  • Xiao Fan Ding University of Saskatchewan
  • Zahra Khoz University of Saskatchewan
  • Daniel Chen University of Saskatchewan
  • Ning Zhu Canadian Light Source Inc.

Keywords:

Synchrotron Imaging, Image Processing, Deep Learning, Hydrogel Scaffolds, Ex Vivo

Abstract

This study showed how effective masking of

dense components (i.e., bone) in propagation-based imaging

computed tomography (PBI-CT) scans of biological samples can

enhance the outcomes of deep learning denoising techniques.

This was performed on ex vivo scans of hydrogel scaffolds im-

planted into animal hind limb and suppressing the overwhelm-

ing signal from the bone allowed for clearer and more distinct

visualization of hydrogel scaffolds. This proved essential for ob-

serving the interactions of hydrogel within the physiological en-

vironment. The detailed image processing steps offer to improve

the practical application of PBI-CT in tissue engineering and

regenerative medicine research.

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Published

2025-05-23

How to Cite

[1]
X. F. Ding, Z. Khoz, D. . Chen, and N. . Zhu, “Enhanced Image Processing of Implanted Hydrogel Scaffold Images Using Propagation-Based Imaging Computed Tomography”, CMBES Proc., vol. 47, no. 1, May 2025.

Issue

Vol. 47 No. 1 (2025): CMBEC 47

Section

Academic