Abstract

The knowledge of the location of the centers of vertebral bodies and intervertebral discs is valuable for the analysis of the spine. Existing methods for the detection and segmentation of vertebrae in images acquired by computed tomography (CT) and magnetic resonance (MR) imaging are usually applicable only to a specific image modality and require prior knowledge of the location of vertebrae, usually obtained by manual identification or statistical modeling. We propose a completely automated framework for the detection of the centers of vertebral bodies and intervertebral discs in CT and MR images. The image intensity and gradient magnitude profiles are first extracted in each image along the already obtained spinal centerline and therefore contain a repeating pattern representing the vertebral bodies and intervertebral discs. Based on the period of the repeating pattern and by using a function that approximates the shape of the vertebral body, a model of the vertebral body is generated. The centers of vertebral bodies and intervertebral discs are detected by measuring the similarity between the generated model and the extracted profiles. The method was evaluated on 29 CT and 13 MR images of lumbar spine with varying number of vertebrae. The overall mean distance between the obtained and the ground truth centers was 2.8 ± 1.9 mm, and no considerable differences were detected between the results for CT, T1-weighted MR or T2-weighted MR images, or among different vertebrae. The proposed method may therefore be valuable for initializing the techniques for the detection and segmentation of vertebrae.

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