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. 2015 Mar 20:9413:941318.
doi: 10.1117/12.2082255.

A supervoxel-based segmentation method for prostate MR images

Zhiqiang Tian  1 , LiZhi Liu  1 , Baowei Fei  2
Affiliations

A supervoxel-based segmentation method for prostate MR images

Zhiqiang Tian et al. Proc SPIE Int Soc Opt Eng. .

Abstract

Accurate segmentation of the prostate has many applications in prostate cancer diagnosis and therapy. In this paper, we propose a "Supervoxel" based method for prostate segmentation. The prostate segmentation problem is considered as assigning a label to each supervoxel. An energy function with data and smoothness terms is used to model the labeling process. The data term estimates the likelihood of a supervoxel belongs to the prostate according to a shape feature. The geometric relationship between two neighboring supervoxels is used to construct a smoothness term. A three-dimensional (3D) graph cut method is used to minimize the energy function in order to segment the prostate. A 3D level set is then used to get a smooth surface based on the output of the graph cut. The performance of the proposed segmentation algorithm was evaluated with respect to the manual segmentation ground truth. The experimental results on 12 prostate volumes showed that the proposed algorithm yields a mean Dice similarity coefficient of 86.9%±3.2%. The segmentation method can be used not only for the prostate but also for other organs.

Keywords: 3D graph cut; 3D level set; Magnetic resonance imaging (MRI); prostate cancer; segmentation; supervoxel.

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Figures

Figure 1
Figure 1
The framework of the proposed method.
Figure 2
Figure 2
Supervoxels and their geometric relations in the 3D medical image volume.
Figure 3
Figure 3
Qualitative evaluation results of the proposed method. The first row is one slice from a typical MR volume, while the second row is the adjacent slice of the same volume. The first column is the original slice. The second column is the supervoxel demonstration. Same color between two slices means the same supervoxel. The blue supervoxels are the segmented prostate obtained from the graph cut. In the third column, the blue boundaries of supervoxels that belong to the prostate are superposed on the original slices to demonstrate the good adherence of the superpvoxel to the boundaries of the prostate. The red curves in the fourth column are the final segmentation obtained by using the 3D level set method. The blue curves are the manual segmented ground truth.
Figure 4
Figure 4
Qualitative results of the proposed method.
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