A rapid 2-D centerline extraction method based on tensor voting

Centerline extraction is widely used in medical image processing. It can benefit applications such as building the connectivity map of neurons from microscopic images as well as examining retina vessels for preventing blindness. Many methods have been developed to extract centerlines from 2-D images. An algorithm based on 2-D rapid tensor voting is proposed in this paper. This method uses the Canny edge detector and a simple ridge finding algorithm to roughly extract centerlines, which is fast, does not require any seeds and allows the object to be disconnected. Then efficient 2-D tensor voting is applied to enhance the centerline, which can rapidly bridge the gaps caused by the earlier step and reject artifacts due to noise. We demonstrate the robustness of the algorithm and compare with existing methods. The result shows good computational efficiency as well as accuracy.

[1]  Luc Florack,et al.  An Efficient Method for Tensor Voting Using Steerable Filters , 2006, ECCV.

[2]  G Valli,et al.  An algorithm for real-time vessel enhancement and detection. , 1997, Computer methods and programs in biomedicine.

[3]  Mi-Suen Lee,et al.  A Computational Framework for Segmentation and Grouping , 2000 .

[4]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  D. Mastronarde,et al.  A Computational Framework for Ultrastructural Mapping of Neural Circuitry , 2009, PLoS biology.

[6]  Charles V. Stewart,et al.  Retinal Vessel Centerline Extraction Using Multiscale Matched Filters, Confidence and Edge Measures , 2006, IEEE Transactions on Medical Imaging.

[7]  Gérard G. Medioni,et al.  Inferring global perceptual contours from local features , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Bram van Ginneken,et al.  Comparative study of retinal vessel segmentation methods on a new publicly available database , 2004, SPIE Medical Imaging.

[9]  Eric L. Miller,et al.  3-D CENTERLINE EXTRACTION OF AXONS IN MICROSCOPIC STACKS FOR THE STUDY OF MOTOR NEURON BEHAVIOR IN DEVELOPING MUSCLES , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[10]  Hong Shen,et al.  Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms , 1999, IEEE Transactions on Information Technology in Biomedicine.