3D medical image segmentation approach based on multi-label front propagation

Many practical applications in the field of medical image processing require robust and valid 3D image segmentation results. In this paper, we present a semi-automatic iterative segmentation approach for 3D medical image by combining a 2D boundary tracking algorithm and a boundary mapping process. Upon each of the consecutive slice, the boundary tracking process is accomplished in an alternate procedure of the morphological dilatation and the multi-label front propagation. The multi-label front propagation method is developed based on the minimal path theory and fast sweeping evolution method to ensure the efficiency, and speed of the boundary tracking algorithm. This 3D image segmentation approach can easily extract the close and smooth boundary of the desired object from a 2D medical image series. This approach is efficient and reliable, and requires very limited user intervention. Some experimental results are also presented to demonstrate the efficiency of this approach.