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Segmentation of lumbar vertebrae using part-based graphs and active appearance models.
Martin G Roberts1, Tim F Cootes, Elisa Pacheco
1School of Imaging Science, University of Manchester, UK. martin.roberts@manchester.ac.uk
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|April 30, 2010
Summary
This study presents an automated method for segmenting vertebrae in spinal radiographs, crucial for diagnosing osteoporosis and grading fractures. The technique accurately identifies vertebral structures, aiding clinical assessments and research.
Area of Science:
- Medical imaging analysis
- Radiology
- Computer vision
Background:
- Accurate vertebral segmentation is vital for diagnosing osteoporosis via vertebral fracture assessment and grading fractures in clinical trials.
- Manual segmentation is time-consuming and subject to inter-observer variability.
- A fully automatic method is needed to improve efficiency and consistency in spinal radiograph analysis.
Purpose of the Study:
- To develop and evaluate a fully automatic method for segmenting vertebrae in spinal radiographs.
- To assess the clinical relevance of automated vertebral segmentation for osteoporosis diagnosis and fracture grading.
Main Methods:
- A parts-based model using small vertebral patches (e.g., corners) was employed.
- Multi-resolution normalized correlation was used for global candidate searching.
- A graphical model with geometric constraints and loopy belief propagation resolved ambiguities, followed by active appearance model search.
Main Results:
- The method was successfully applied to a clinical dataset of lumbar spine computed radiography images.
- The accuracy of the automated segmentation was evaluated against manual annotations by expert radiologists.
Conclusions:
- The developed fully automatic method shows promise for accurate vertebral segmentation in spinal radiographs.
- This technique has significant potential to aid in the diagnosis of osteoporosis and grading of vertebral fractures.