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Published on: March 14, 2018
Statistical atlases of bone anatomy: construction, iterative improvement and validation
Gouthami Chintalapani1, Lotta M Ellingsen, Ofri Sadowsky
1Johns Hopkins University, Baltimore, USA. greddy@cs.jhu.edu
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|December 7, 2007
Summary
This study introduces an iterative framework for creating statistical atlases of bony anatomy from CT scans. The developed statistical atlas of the human pelvis achieves high accuracy in shape approximation using principal modes of variation.
Area of Science:
- Medical Imaging
- Computational Anatomy
- Biomedical Engineering
Background:
- Statistical atlases are crucial for understanding anatomical variations.
- Creating robust atlases requires advanced image registration and segmentation techniques.
- Previous methods may suffer from initial template bias and limited stability.
Purpose of the Study:
- To develop an iterative bootstrapping framework for creating and analyzing statistical atlases of bony anatomy.
- To generate a high-fidelity statistical atlas of the human pelvis from a large dataset of CT scans.
- To establish a validation framework for statistical models of anatomical structures.
Main Methods:
- Utilized a tetrahedral mesh representation for initial anatomy.
- Employed deformable intensity-based registration for atlas creation and refinement.
- Iterated the registration/segmentation process to minimize bias and enhance model stability.
- Developed a framework for validating the statistical models.
Main Results:
- Successfully created a statistical atlas of full pelvis anatomy using 110 healthy patient CT scans.
- Demonstrated that pelvis shape can be approximated with an average accuracy of 1.5036 mm using the first 15 principal modes of variation.
- The iterative approach improved the stability and consistency of mean shape and variational modes.
Conclusions:
- The proposed iterative bootstrapping framework effectively generates accurate and stable statistical atlases of bony anatomy.
- The developed human pelvis atlas provides a valuable tool for quantitative anatomical analysis.
- The methodology is adaptable to various registration techniques, suggesting broad applicability.
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