Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT
This addresses the problem of accurate vertebral segmentation for diagnosis and treatment in patients with spinal pathologies, but it is incremental as it applies an existing multi-atlas technique to a specific clinical dataset.
The paper tackled the challenge of segmenting osteoporotic and compression fractured vertebrae on CT images using a multi-atlas joint label fusion method, achieving Dice coefficients of 90.9±3.0% for fractured vertebrae and 2.7±4.5% for osteoporotic vertebrae with corresponding surface distances.
The precise and accurate segmentation of the vertebral column is essential in the diagnosis and treatment of various orthopedic, neurological, and oncological traumas and pathologies. Segmentation is especially challenging in the presence of pathology such as vertebral compression fractures. In this paper, we propose a method to produce segmentations for osteoporotic compression fractured vertebrae by applying a multi-atlas joint label fusion technique for clinical CT images. A total of 170 thoracic and lumbar vertebrae were evaluated using atlases from five patients with varying degrees of spinal degeneration. In an osteoporotic cohort of bundled atlases, registration provided an average Dice coefficient and mean absolute surface distance of 2.7$\pm$4.5% and 0.32$\pm$0.13mm for osteoporotic vertebrae, respectively, and 90.9$\pm$3.0% and 0.36$\pm$0.11mm for compression fractured vertebrae.