Abstract
Localization of the dominant points of cervical spines in medical images is important for improving the medical automation in clinical head and neck applications. In order to automatically identify the dominant points of cervical vertebrae in neck CT images with precision, we propose a method based on multi-scale contour analysis to analyzing the deformable shape of spines. To extract the spine contour, we introduce a method to automatically generate the initial contour of the spine shape, and the distance field for level set active contour iterations can also be deduced. In the shape analysis stage, we at first coarsely segment the extracted contour with zero-crossing points of the curvature based on the analysis with curvature scale space, and the spine shape is modeled with the analysis of curvature scale space. Then, each segmented curve is analyzed geometrically based on the turning angle property at different scales, and the local extreme points are extracted and verified as the dominant feature points. The vertices of the shape contour are approximately derived with the analysis at coarse scale, and then adjusted precisely at fine scale. Consequently, the results of experiment show that we approach a success rate of 93.4% and accuracy of 0.37mm by comparing with the manual results.
Highlights
Anatomical landmarks and dominant points of cervical vertebrae are of considerable importance for many applications on orthopedics, neurology, and radiation therapy planning
In order to automatically find the dominant features points in cervical vertebrae, Rochies and Winter proposed researches about detection of anatomical landmarks and dominant points by matching feature sets derived from 2D wavelet and Gabor transform in computerized tomography (CT) and MRI images [8,9]
Let C0 be the initial contour for active contour iterations and g(x) denotes a monotonically stopping function which conducts the contour converge toward the boundary points based on the direction and magnitude of gradient
Summary
Anatomical landmarks and dominant points of cervical vertebrae are of considerable importance for many applications on orthopedics, neurology, and radiation therapy planning. Dominant feature points of cervical vertebrae include transverse foramens, spinous processes, and corners of lateral facets, etc. In neck CT images, the cervical vertebrae are significant landmarks for medical application but to automatically extract the precise feature points from the complex images is still a challenging task. We propose a method to automatically find the feature points of cervical spines in CT slices as shown in Fig 1 based on geometric analysis in companion with anatomical knowledge. As shown in Fig., the dominant points proposed to extract include the vertices at both sides of vertebral body, near transverse foramens and pedicles (points 1 and 2), the corners of the facets (points 3 and 4) and the corners of spinous process.
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