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. 2011:2011:621905.
doi: 10.1155/2011/621905. Epub 2011 Jul 31.

A framework of vertebra segmentation using the active shape model-based approach

Mohammed Benjelloun  1 , Saïd Mahmoudi, Fabian Lecron
Affiliations

A framework of vertebra segmentation using the active shape model-based approach

Mohammed Benjelloun et al. Int J Biomed Imaging. 2011.

Abstract

We propose a medical image segmentation approach based on the Active Shape Model theory. We apply this method for cervical vertebra detection. The main advantage of this approach is the application of a statistical model created after a training stage. Thus, the knowledge and interaction of the domain expert intervene in this approach. Our application allows the use of two different models, that is, a global one (with several vertebrae) and a local one (with a single vertebra). Two modes of segmentation are also proposed: manual and semiautomatic. For the manual mode, only two points are selected by the user on a given image. The first point needs to be close to the lower anterior corner of the last vertebra and the second near the upper anterior corner of the first vertebra. These two points are required to initialize the segmentation process. We propose to use the Harris corner detector combined with three successive filters to carry out the semiautomatic process. The results obtained on a large set of X-ray images are very promising.

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Figures

Figure 1
Figure 1
The steps of the ASM framework.
Figure 2
Figure 2
Vertebra marking.
Figure 3
Figure 3
An example of alignment.
Figure 4
Figure 4
Reduction of the window search.
Figure 5
Figure 5
Procedure to detect corners of each vertebra.
Figure 6
Figure 6
Illustration of the effect of filtering out corners neighboring a contour (b) and the filtering of false corners (c).
Figure 7
Figure 7
The angle filter process.
Figure 8
Figure 8
Parameters used for the vertebra corners detection.
Figure 9
Figure 9
Illustration of the construction of the sequence S ⋆.
Figure 10
Figure 10
Normal of the contours at each point of the profile.
Figure 11
Figure 11
Influence of the number of landmarks.
Figure 12
Figure 12
Influence of the sample size on the mean error of segmentation.
Figure 13
Figure 13
Point-to-line distance between 2 contours.
Figure 14
Figure 14
Effects of variations along the principal directions of a column mode.
Figure 15
Figure 15
Effects of variations along the principal directions of a vertebra model.
Figure 16
Figure 16
Results of segmentation using the vertebra model.
Algorithm 1
Algorithm 1
Determine the sequence of the vertebra corners.
Algorithm 2
Algorithm 2
RecursiveFunction (S i).
Algorithm 3
Algorithm 3
ASM segmentation procedure.
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