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MICCAI
2010
Springer

Fast Random Walker with Priors Using Precomputation for Interactive Medical Image Segmentation

10 years 8 months ago
Fast Random Walker with Priors Using Precomputation for Interactive Medical Image Segmentation
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.
Shawn Andrews, Ghassan Hamarneh, Ahmed Saad
Added 14 Feb 2011
Updated 14 Feb 2011
Type Journal
Year 2010
Where MICCAI
Authors Shawn Andrews, Ghassan Hamarneh, Ahmed Saad
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