Abstract
Updating segmentation results in real-time based on repeated user input is a reliable way to guarantee accuracy, paramount in medical imaging applications, while making efficient use of an expert’s time. The random walker algorithm with priors is a robust method able to find a globally optimal probabilistic segmentation with an intuitive method for user input. However, like many other segmentation algorithms, it can be too slow for real-time user interaction. We propose a speedup to this popular algorithm based on offline precomputation, taking advantage of the time images are stored on servers prior to an analysis session. Our results demonstrate the benefits of our approach. For example, the segmentations found by the original random walker and by our new precomputation method for a given 3D image have a Dice’s similarity coefficient of 0.975, yet our method runs in 1/25th of the time.
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Keywords
- Active Contour Model
- Medical Image Analysis
- Online Phase
- Random Walker Algorithm
- Interactive Segmentation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Grady, L., Kemal Sinop, L.: Fast approximation random walker segmentation using eigenvector precomputation. IEEE Trans. PAMI (2008)
Armstrong, C.J., Price, B.L., Barrett, W.A.: Interactive segmentation of image volumes with live surface. Computers & Graphics 31(2), 212–229 (2007)
Olabarriaga, S.D., Smeulders, A.W.M.: Interaction in the segmentation of medical images: A survey. Medical Image Analysis 5(2), 127–142 (2001)
Kang, Y., Engelke, K., Kalender, W.A.: Interactive 3D editing tools for image segmentation. Medical Image Analysis 8(1), 35–46 (2004)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. Int’l. J. on Computer Vision 1(4), 321–331 (1987)
Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Trans. on Image Processing 10(2), 266–277 (2001)
Cohen, L., Kimmel, R.: Global minimum for active contour models: A minimal path approach. International Journal of Computer Vision 24, 57–78 (1997)
Barrett, W., Mortensen, E.: Interactive live-wire boundary extraction. Medical Image Analysis 1, 331–341 (1997)
Boykov, Y., Jolly, M.P.: Interactive graph cuts for optimal boundary and region segmentation of objects in n-D images. In: Proc. ICCV, pp. 105–112 (2001)
Grady, L.: Random walks for image segmentation. IEEE TPAMI 28(11), 1768–1783 (2006)
Grady, L.: Multilabel random walker image segmentation using prior models. In: IEEE Conf. CVPR, vol. 1, pp. 763–770 (June 2005)
Andrews, S., Hamarneh, G., Saad, A.: Fast random walker with priors using precomputation. Technical Report TR 2010-07, Simon Fraser University (June 2010)
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Andrews, S., Hamarneh, G., Saad, A. (2010). Fast Random Walker with Priors Using Precomputation for Interactive Medical Image Segmentation. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. MICCAI 2010. Lecture Notes in Computer Science, vol 6363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15711-0_2
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DOI: https://doi.org/10.1007/978-3-642-15711-0_2
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