Semantic segmentation of micro-CT images to analyze bone ingrowth into biodegradable scaffolds.
File(s)
Accepted version
Author(s)
Type
Conference Paper
Abstract
The healing of bone fractures is a complex and well-orchestrated physiological process, but normal healing is compromised when the fracture is large. These large non-union fractures often require a template with surgical intervention for healing. The standard treatment, autografting, has drawbacks such as donor site pain and limited availability. Biodegradable scaffolds developed using biomaterials such as bioactive glass are a potential solution. Investigation of bone ingrowth into biodegradable scaffolds is an important aspect of their development. Micro-CT (μ-CT) imaging is widely used to evaluate and quantify tissue ingrowth into scaffolds in 3D. Existing segmentation techniques have low accuracy in differentiating bone and scaffold, and need improvements to accurately quantify the bone in-growth into the scaffold using μ-CT scans. This study proposes a novel 3-stage pipeline for better outcome. The first stage of the pipeline is based on a convolutional neural network for the segmentation of the scaffold, bone, and pores from μ-CT images to investigate bone ingrowth. A 3D rigid image registration procedure was employed in the next stage to extract the volume of interest (VOI) for the analysis. In the final stage, algorithms were developed to quantitatively analyze bone ingrowth and scaffold degradation. The best model for segmentation produced a dice similarity coefficient score of 90.1, intersection over union score of 83.9, and pixel accuracy of 93.1 for unseen test data.
Date Issued
2022-09-08
Date Acceptance
2022-09-01
Citation
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2022, 2022, pp.3830-3833
ISSN
1557-170X
Publisher
IEEE
Start Page
3830
End Page
3833
Journal / Book Title
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Volume
2022
Copyright Statement
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
National Institute for Health Research
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/36086069
Grant Number
GHR Project: 16/137/45
Source
44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Subjects
Biocompatible Materials
Bone and Bones
Semantics
Wound Healing
X-Ray Microtomography
Publication Status
Published
Start Date
2022-07-11
Finish Date
2022-07-15
Coverage Spatial
United States
Date Publish Online
2022-09-08